• Research Report: Definition, Types + [Writing Guide]


One of the reasons for carrying out research is to add to the existing body of knowledge. Therefore, when conducting research, you need to document your processes and findings in a research report. 

With a research report, it is easy to outline the findings of your systematic investigation and any gaps needing further inquiry. Knowing how to create a detailed research report will prove useful when you need to conduct research.  

What is a Research Report?

A research report is a well-crafted document that outlines the processes, data, and findings of a systematic investigation. It is an important document that serves as a first-hand account of the research process, and it is typically considered an objective and accurate source of information.

In many ways, a research report can be considered as a summary of the research process that clearly highlights findings, recommendations, and other important details. Reading a well-written research report should provide you with all the information you need about the core areas of the research process.

Features of a Research Report 

So how do you recognize a research report when you see one? Here are some of the basic features that define a research report. 

  • It is a detailed presentation of research processes and findings, and it usually includes tables and graphs. 
  • It is written in a formal language.
  • A research report is usually written in the third person.
  • It is informative and based on first-hand verifiable information.
  • It is formally structured with headings, sections, and bullet points.
  • It always includes recommendations for future actions. 

Types of Research Report 

The research report is classified based on two things; nature of research and target audience.

Nature of Research

  • Qualitative Research Report

This is the type of report written for qualitative research . It outlines the methods, processes, and findings of a qualitative method of systematic investigation. In educational research, a qualitative research report provides an opportunity for one to apply his or her knowledge and develop skills in planning and executing qualitative research projects.

A qualitative research report is usually descriptive in nature. Hence, in addition to presenting details of the research process, you must also create a descriptive narrative of the information.

  • Quantitative Research Report

A quantitative research report is a type of research report that is written for quantitative research. Quantitative research is a type of systematic investigation that pays attention to numerical or statistical values in a bid to find answers to research questions. 

In this type of research report, the researcher presents quantitative data to support the research process and findings. Unlike a qualitative research report that is mainly descriptive, a quantitative research report works with numbers; that is, it is numerical in nature. 

Target Audience

Also, a research report can be said to be technical or popular based on the target audience. If you’re dealing with a general audience, you would need to present a popular research report, and if you’re dealing with a specialized audience, you would submit a technical report. 

  • Technical Research Report

A technical research report is a detailed document that you present after carrying out industry-based research. This report is highly specialized because it provides information for a technical audience; that is, individuals with above-average knowledge in the field of study. 

In a technical research report, the researcher is expected to provide specific information about the research process, including statistical analyses and sampling methods. Also, the use of language is highly specialized and filled with jargon. 

Examples of technical research reports include legal and medical research reports. 

  • Popular Research Report

A popular research report is one for a general audience; that is, for individuals who do not necessarily have any knowledge in the field of study. A popular research report aims to make information accessible to everyone. 

It is written in very simple language, which makes it easy to understand the findings and recommendations. Examples of popular research reports are the information contained in newspapers and magazines. 

Importance of a Research Report 

  • Knowledge Transfer: As already stated above, one of the reasons for carrying out research is to contribute to the existing body of knowledge, and this is made possible with a research report. A research report serves as a means to effectively communicate the findings of a systematic investigation to all and sundry.  
  • Identification of Knowledge Gaps: With a research report, you’d be able to identify knowledge gaps for further inquiry. A research report shows what has been done while hinting at other areas needing systematic investigation. 
  • In market research, a research report would help you understand the market needs and peculiarities at a glance. 
  • A research report allows you to present information in a precise and concise manner. 
  • It is time-efficient and practical because, in a research report, you do not have to spend time detailing the findings of your research work in person. You can easily send out the report via email and have stakeholders look at it. 

Guide to Writing a Research Report

A lot of detail goes into writing a research report, and getting familiar with the different requirements would help you create the ideal research report. A research report is usually broken down into multiple sections, which allows for a concise presentation of information.

Structure and Example of a Research Report

This is the title of your systematic investigation. Your title should be concise and point to the aims, objectives, and findings of a research report. 

  • Table of Contents

This is like a compass that makes it easier for readers to navigate the research report.

An abstract is an overview that highlights all important aspects of the research including the research method, data collection process, and research findings. Think of an abstract as a summary of your research report that presents pertinent information in a concise manner. 

An abstract is always brief; typically 100-150 words and goes straight to the point. The focus of your research abstract should be the 5Ws and 1H format – What, Where, Why, When, Who and How. 

  • Introduction

Here, the researcher highlights the aims and objectives of the systematic investigation as well as the problem which the systematic investigation sets out to solve. When writing the report introduction, it is also essential to indicate whether the purposes of the research were achieved or would require more work.

In the introduction section, the researcher specifies the research problem and also outlines the significance of the systematic investigation. Also, the researcher is expected to outline any jargons and terminologies that are contained in the research.  

  • Literature Review

A literature review is a written survey of existing knowledge in the field of study. In other words, it is the section where you provide an overview and analysis of different research works that are relevant to your systematic investigation. 

It highlights existing research knowledge and areas needing further investigation, which your research has sought to fill. At this stage, you can also hint at your research hypothesis and its possible implications for the existing body of knowledge in your field of study. 

  • An Account of Investigation

This is a detailed account of the research process, including the methodology, sample, and research subjects. Here, you are expected to provide in-depth information on the research process including the data collection and analysis procedures. 

In a quantitative research report, you’d need to provide information surveys, questionnaires and other quantitative data collection methods used in your research. In a qualitative research report, you are expected to describe the qualitative data collection methods used in your research including interviews and focus groups. 

In this section, you are expected to present the results of the systematic investigation. 

This section further explains the findings of the research, earlier outlined. Here, you are expected to present a justification for each outcome and show whether the results are in line with your hypotheses or if other research studies have come up with similar results.

  • Conclusions

This is a summary of all the information in the report. It also outlines the significance of the entire study. 

  • References and Appendices

This section contains a list of all the primary and secondary research sources. 

Tips for Writing a Research Report

  • Define the Context for the Report

As is obtainable when writing an essay, defining the context for your research report would help you create a detailed yet concise document. This is why you need to create an outline before writing so that you do not miss out on anything. 

  • Define your Audience

Writing with your audience in mind is essential as it determines the tone of the report. If you’re writing for a general audience, you would want to present the information in a simple and relatable manner. For a specialized audience, you would need to make use of technical and field-specific terms. 

  • Include Significant Findings

The idea of a research report is to present some sort of abridged version of your systematic investigation. In your report, you should exclude irrelevant information while highlighting only important data and findings. 

  • Include Illustrations

Your research report should include illustrations and other visual representations of your data. Graphs, pie charts, and relevant images lend additional credibility to your systematic investigation.

  • Choose the Right Title

A good research report title is brief, precise, and contains keywords from your research. It should provide a clear idea of your systematic investigation so that readers can grasp the entire focus of your research from the title. 

  • Proofread the Report

Before publishing the document, ensure that you give it a second look to authenticate the information. If you can, get someone else to go through the report, too, and you can also run it through proofreading and editing software. 

How to Gather Research Data for Your Report  

  • Understand the Problem

Every research aims at solving a specific problem or set of problems, and this should be at the back of your mind when writing your research report. Understanding the problem would help you to filter the information you have and include only important data in your report. 

  • Know what your report seeks to achieve

This is somewhat similar to the point above because, in some way, the aim of your research report is intertwined with the objectives of your systematic investigation. Identifying the primary purpose of writing a research report would help you to identify and present the required information accordingly. 

  • Identify your audience

Knowing your target audience plays a crucial role in data collection for a research report. If your research report is specifically for an organization, you would want to present industry-specific information or show how the research findings are relevant to the work that the company does. 

  • Create Surveys/Questionnaires

A survey is a research method that is used to gather data from a specific group of people through a set of questions. It can be either quantitative or qualitative. 

A survey is usually made up of structured questions, and it can be administered online or offline. However, an online survey is a more effective method of research data collection because it helps you save time and gather data with ease. 

You can seamlessly create an online questionnaire for your research on Formplus . With the multiple sharing options available in the builder, you would be able to administer your survey to respondents in little or no time. 

Formplus also has a report summary too l that you can use to create custom visual reports for your research.

Step-by-step guide on how to create an online questionnaire using Formplus  

  • Sign into Formplus

In the Formplus builder, you can easily create different online questionnaires for your research by dragging and dropping preferred fields into your form. To access the Formplus builder, you will need to create an account on Formplus. 

Once you do this, sign in to your account and click on Create new form to begin. 

  • Edit Form Title : Click on the field provided to input your form title, for example, “Research Questionnaire.”
  • Edit Form : Click on the edit icon to edit the form.
  • Add Fields : Drag and drop preferred form fields into your form in the Formplus builder inputs column. There are several field input options for questionnaires in the Formplus builder. 
  • Edit fields
  • Click on “Save”
  • Form Customization: With the form customization options in the form builder, you can easily change the outlook of your form and make it more unique and personalized. Formplus allows you to change your form theme, add background images, and even change the font according to your needs. 
  • Multiple Sharing Options: Formplus offers various form-sharing options, which enables you to share your questionnaire with respondents easily. You can use the direct social media sharing buttons to share your form link to your organization’s social media pages.  You can also send out your survey form as email invitations to your research subjects too. If you wish, you can share your form’s QR code or embed it on your organization’s website for easy access. 


Always remember that a research report is just as important as the actual systematic investigation because it plays a vital role in communicating research findings to everyone else. This is why you must take care to create a concise document summarizing the process of conducting any research. 

In this article, we’ve outlined essential tips to help you create a research report. When writing your report, you should always have the audience at the back of your mind, as this would set the tone for the document. 


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Home Market Research

Research Reports: Definition and How to Write Them

Research Reports

Reports are usually spread across a vast horizon of topics but are focused on communicating information about a particular topic and a niche target market. The primary motive of research reports is to convey integral details about a study for marketers to consider while designing new strategies.

Certain events, facts, and other information based on incidents need to be relayed to the people in charge, and creating research reports is the most effective communication tool. Ideal research reports are extremely accurate in the offered information with a clear objective and conclusion. These reports should have a clean and structured format to relay information effectively.

What are Research Reports?

Research reports are recorded data prepared by researchers or statisticians after analyzing the information gathered by conducting organized research, typically in the form of surveys or qualitative methods .

A research report is a reliable source to recount details about a conducted research. It is most often considered to be a true testimony of all the work done to garner specificities of research.

The various sections of a research report are:

  • Background/Introduction
  • Implemented Methods
  • Results based on Analysis
  • Deliberation

Learn more: Quantitative Research

Components of Research Reports

Research is imperative for launching a new product/service or a new feature. The markets today are extremely volatile and competitive due to new entrants every day who may or may not provide effective products. An organization needs to make the right decisions at the right time to be relevant in such a market with updated products that suffice customer demands.

The details of a research report may change with the purpose of research but the main components of a report will remain constant. The research approach of the market researcher also influences the style of writing reports. Here are seven main components of a productive research report:

  • Research Report Summary: The entire objective along with the overview of research are to be included in a summary which is a couple of paragraphs in length. All the multiple components of the research are explained in brief under the report summary.  It should be interesting enough to capture all the key elements of the report.
  • Research Introduction: There always is a primary goal that the researcher is trying to achieve through a report. In the introduction section, he/she can cover answers related to this goal and establish a thesis which will be included to strive and answer it in detail.  This section should answer an integral question: “What is the current situation of the goal?”.  After the research design was conducted, did the organization conclude the goal successfully or they are still a work in progress –  provide such details in the introduction part of the research report.
  • Research Methodology: This is the most important section of the report where all the important information lies. The readers can gain data for the topic along with analyzing the quality of provided content and the research can also be approved by other market researchers . Thus, this section needs to be highly informative with each aspect of research discussed in detail.  Information needs to be expressed in chronological order according to its priority and importance. Researchers should include references in case they gained information from existing techniques.
  • Research Results: A short description of the results along with calculations conducted to achieve the goal will form this section of results. Usually, the exposition after data analysis is carried out in the discussion part of the report.

Learn more: Quantitative Data

  • Research Discussion: The results are discussed in extreme detail in this section along with a comparative analysis of reports that could probably exist in the same domain. Any abnormality uncovered during research will be deliberated in the discussion section.  While writing research reports, the researcher will have to connect the dots on how the results will be applicable in the real world.
  • Research References and Conclusion: Conclude all the research findings along with mentioning each and every author, article or any content piece from where references were taken.

Learn more: Qualitative Observation

15 Tips for Writing Research Reports

Writing research reports in the manner can lead to all the efforts going down the drain. Here are 15 tips for writing impactful research reports:

  • Prepare the context before starting to write and start from the basics:  This was always taught to us in school – be well-prepared before taking a plunge into new topics. The order of survey questions might not be the ideal or most effective order for writing research reports. The idea is to start with a broader topic and work towards a more specific one and focus on a conclusion or support, which a research should support with the facts.  The most difficult thing to do in reporting, without a doubt is to start. Start with the title, the introduction, then document the first discoveries and continue from that. Once the marketers have the information well documented, they can write a general conclusion.
  • Keep the target audience in mind while selecting a format that is clear, logical and obvious to them:  Will the research reports be presented to decision makers or other researchers? What are the general perceptions around that topic? This requires more care and diligence. A researcher will need a significant amount of information to start writing the research report. Be consistent with the wording, the numbering of the annexes and so on. Follow the approved format of the company for the delivery of research reports and demonstrate the integrity of the project with the objectives of the company.
  • Have a clear research objective: A researcher should read the entire proposal again, and make sure that the data they provide contributes to the objectives that were raised from the beginning. Remember that speculations are for conversations, not for research reports, if a researcher speculates, they directly question their own research.
  • Establish a working model:  Each study must have an internal logic, which will have to be established in the report and in the evidence. The researchers’ worst nightmare is to be required to write research reports and realize that key questions were not included.

Learn more: Quantitative Observation

  • Gather all the information about the research topic. Who are the competitors of our customers? Talk to other researchers who have studied the subject of research, know the language of the industry. Misuse of the terms can discourage the readers of research reports from reading further.
  • Read aloud while writing. While reading the report, if the researcher hears something inappropriate, for example, if they stumble over the words when reading them, surely the reader will too. If the researcher can’t put an idea in a single sentence, then it is very long and they must change it so that the idea is clear to everyone.
  • Check grammar and spelling. Without a doubt, good practices help to understand the report. Use verbs in the present tense. Consider using the present tense, which makes the results sound more immediate. Find new words and other ways of saying things. Have fun with the language whenever possible.
  • Discuss only the discoveries that are significant. If some data are not really significant, do not mention them. Remember that not everything is truly important or essential within research reports.

Learn more: Qualitative Data

  • Try and stick to the survey questions. For example, do not say that the people surveyed “were worried” about an research issue , when there are different degrees of concern.
  • The graphs must be clear enough so that they understand themselves. Do not let graphs lead the reader to make mistakes: give them a title, include the indications, the size of the sample, and the correct wording of the question.
  • Be clear with messages. A researcher should always write every section of the report with an accuracy of details and language.
  • Be creative with titles – Particularly in segmentation studies choose names “that give life to research”. Such names can survive for a long time after the initial investigation.
  • Create an effective conclusion: The conclusion in the research reports is the most difficult to write, but it is an incredible opportunity to excel. Make a precise summary. Sometimes it helps to start the conclusion with something specific, then it describes the most important part of the study, and finally, it provides the implications of the conclusions.
  • Get a couple more pair of eyes to read the report. Writers have trouble detecting their own mistakes. But they are responsible for what is presented. Ensure it has been approved by colleagues or friends before sending the find draft out.

Learn more: Market Research and Analysis


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Research report guide: Definition, types, and tips

Last updated

5 March 2024

Reviewed by

Short on time? Get an AI generated summary of this article instead

From successful product launches or software releases to planning major business decisions, research reports serve many vital functions. They can summarize evidence and deliver insights and recommendations to save companies time and resources. They can reveal the most value-adding actions a company should take.

However, poorly constructed reports can have the opposite effect! Taking the time to learn established research-reporting rules and approaches will equip you with in-demand skills. You’ll be able to capture and communicate information applicable to numerous situations and industries, adding another string to your resume bow.

  • What are research reports?

A research report is a collection of contextual data, gathered through organized research, that provides new insights into a particular challenge (which, for this article, is business-related). Research reports are a time-tested method for distilling large amounts of data into a narrow band of focus.

Their effectiveness often hinges on whether the report provides:

Strong, well-researched evidence

Comprehensive analysis

Well-considered conclusions and recommendations

Though the topic possibilities are endless, an effective research report keeps a laser-like focus on the specific questions or objectives the researcher believes are key to achieving success. Many research reports begin as research proposals, which usually include the need for a report to capture the findings of the study and recommend a course of action.

A description of the research method used, e.g., qualitative, quantitative, or other

Statistical analysis

Causal (or explanatory) research (i.e., research identifying relationships between two variables)

Inductive research, also known as ‘theory-building’

Deductive research, such as that used to test theories

Action research, where the research is actively used to drive change

  • Importance of a research report

Research reports can unify and direct a company's focus toward the most appropriate strategic action. Of course, spending resources on a report takes up some of the company's human and financial resources. Choosing when a report is called for is a matter of judgment and experience.

Some development models used heavily in the engineering world, such as Waterfall development, are notorious for over-relying on research reports. With Waterfall development, there is a linear progression through each step of a project, and each stage is precisely documented and reported on before moving to the next.

The pace of the business world is faster than the speed at which your authors can produce and disseminate reports. So how do companies strike the right balance between creating and acting on research reports?

The answer lies, again, in the report's defined objectives. By paring down your most pressing interests and those of your stakeholders, your research and reporting skills will be the lenses that keep your company's priorities in constant focus.

Honing your company's primary objectives can save significant amounts of time and align research and reporting efforts with ever-greater precision.

Some examples of well-designed research objectives are:

Proving whether or not a product or service meets customer expectations

Demonstrating the value of a service, product, or business process to your stakeholders and investors

Improving business decision-making when faced with a lack of time or other constraints

Clarifying the relationship between a critical cause and effect for problematic business processes

Prioritizing the development of a backlog of products or product features

Comparing business or production strategies

Evaluating past decisions and predicting future outcomes

  • Features of a research report

Research reports generally require a research design phase, where the report author(s) determine the most important elements the report must contain.

Just as there are various kinds of research, there are many types of reports.

Here are the standard elements of almost any research-reporting format:

Report summary. A broad but comprehensive overview of what readers will learn in the full report. Summaries are usually no more than one or two paragraphs and address all key elements of the report. Think of the key takeaways your primary stakeholders will want to know if they don’t have time to read the full document.

Introduction. Include a brief background of the topic, the type of research, and the research sample. Consider the primary goal of the report, who is most affected, and how far along the company is in meeting its objectives.

Methods. A description of how the researcher carried out data collection, analysis, and final interpretations of the data. Include the reasons for choosing a particular method. The methods section should strike a balance between clearly presenting the approach taken to gather data and discussing how it is designed to achieve the report's objectives.

Data analysis. This section contains interpretations that lead readers through the results relevant to the report's thesis. If there were unexpected results, include here a discussion on why that might be. Charts, calculations, statistics, and other supporting information also belong here (or, if lengthy, as an appendix). This should be the most detailed section of the research report, with references for further study. Present the information in a logical order, whether chronologically or in order of importance to the report's objectives.

Conclusion. This should be written with sound reasoning, often containing useful recommendations. The conclusion must be backed by a continuous thread of logic throughout the report.

  • How to write a research paper

With a clear outline and robust pool of research, a research paper can start to write itself, but what's a good way to start a research report?

Research report examples are often the quickest way to gain inspiration for your report. Look for the types of research reports most relevant to your industry and consider which makes the most sense for your data and goals.

The research report outline will help you organize the elements of your report. One of the most time-tested report outlines is the IMRaD structure:


...and Discussion

Pay close attention to the most well-established research reporting format in your industry, and consider your tone and language from your audience's perspective. Learn the key terms inside and out; incorrect jargon could easily harm the perceived authority of your research paper.

Along with a foundation in high-quality research and razor-sharp analysis, the most effective research reports will also demonstrate well-developed:

Internal logic

Narrative flow

Conclusions and recommendations

Readability, striking a balance between simple phrasing and technical insight

How to gather research data for your report

The validity of research data is critical. Because the research phase usually occurs well before the writing phase, you normally have plenty of time to vet your data.

However, research reports could involve ongoing research, where report authors (sometimes the researchers themselves) write portions of the report alongside ongoing research.

One such research-report example would be an R&D department that knows its primary stakeholders are eager to learn about a lengthy work in progress and any potentially important outcomes.

However you choose to manage the research and reporting, your data must meet robust quality standards before you can rely on it. Vet any research with the following questions in mind:

Does it use statistically valid analysis methods?

Do the researchers clearly explain their research, analysis, and sampling methods?

Did the researchers provide any caveats or advice on how to interpret their data?

Have you gathered the data yourself or were you in close contact with those who did?

Is the source biased?

Usually, flawed research methods become more apparent the further you get through a research report.

It's perfectly natural for good research to raise new questions, but the reader should have no uncertainty about what the data represents. There should be no doubt about matters such as:

Whether the sampling or analysis methods were based on sound and consistent logic

What the research samples are and where they came from

The accuracy of any statistical functions or equations

Validation of testing and measuring processes

When does a report require design validation?

A robust design validation process is often a gold standard in highly technical research reports. Design validation ensures the objects of a study are measured accurately, which lends more weight to your report and makes it valuable to more specialized industries.

Product development and engineering projects are the most common research-report examples that typically involve a design validation process. Depending on the scope and complexity of your research, you might face additional steps to validate your data and research procedures.

If you’re including design validation in the report (or report proposal), explain and justify your data-collection processes. Good design validation builds greater trust in a research report and lends more weight to its conclusions.

Choosing the right analysis method

Just as the quality of your report depends on properly validated research, a useful conclusion requires the most contextually relevant analysis method. This means comparing different statistical methods and choosing the one that makes the most sense for your research.

Most broadly, research analysis comes down to quantitative or qualitative methods (respectively: measurable by a number vs subjectively qualified values). There are also mixed research methods, which bridge the need for merging hard data with qualified assessments and still reach a cohesive set of conclusions.

Some of the most common analysis methods in research reports include:

Significance testing (aka hypothesis analysis), which compares test and control groups to determine how likely the data was the result of random chance.

Regression analysis , to establish relationships between variables, control for extraneous variables , and support correlation analysis.

Correlation analysis (aka bivariate testing), a method to identify and determine the strength of linear relationships between variables. It’s effective for detecting patterns from complex data, but care must be exercised to not confuse correlation with causation.

With any analysis method, it's important to justify which method you chose in the report. You should also provide estimates of the statistical accuracy (e.g., the p-value or confidence level of quantifiable data) of any data analysis.

This requires a commitment to the report's primary aim. For instance, this may be achieving a certain level of customer satisfaction by analyzing the cause and effect of changes to how service is delivered. Even better, use statistical analysis to calculate which change is most positively correlated with improved levels of customer satisfaction.

  • Tips for writing research reports

There's endless good advice for writing effective research reports, and it almost all depends on the subjective aims of the people behind the report. Due to the wide variety of research reports, the best tips will be unique to each author's purpose.

Consider the following research report tips in any order, and take note of the ones most relevant to you:

No matter how in depth or detailed your report might be, provide a well-considered, succinct summary. At the very least, give your readers a quick and effective way to get up to speed.

Pare down your target audience (e.g., other researchers, employees, laypersons, etc.), and adjust your voice for their background knowledge and interest levels

For all but the most open-ended research, clarify your objectives, both for yourself and within the report.

Leverage your team members’ talents to fill in any knowledge gaps you might have. Your team is only as good as the sum of its parts.

Justify why your research proposal’s topic will endure long enough to derive value from the finished report.

Consolidate all research and analysis functions onto a single user-friendly platform. There's no reason to settle for less than developer-grade tools suitable for non-developers.

What's the format of a research report?

The research-reporting format is how the report is structured—a framework the authors use to organize their data, conclusions, arguments, and recommendations. The format heavily determines how the report's outline develops, because the format dictates the overall structure and order of information (based on the report's goals and research objectives).

What's the purpose of a research-report outline?

A good report outline gives form and substance to the report's objectives, presenting the results in a readable, engaging way. For any research-report format, the outline should create momentum along a chain of logic that builds up to a conclusion or interpretation.

What's the difference between a research essay and a research report?

There are several key differences between research reports and essays:

Research report:

Ordered into separate sections

More commercial in nature

Often includes infographics

Heavily descriptive

More self-referential

Usually provides recommendations

Research essay

Does not rely on research report formatting

More academically minded

Normally text-only

Less detailed

Omits discussion of methods

Usually non-prescriptive 

Should you be using a customer insights hub?

Do you want to discover previous research faster?

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Research Method

Home » Purpose of Research – Objectives and Applications

Purpose of Research – Objectives and Applications

Table of Contents

Purpose of Research

Purpose of Research


The purpose of research is to systematically investigate and gather information on a particular topic or issue, with the aim of answering questions, solving problems, or advancing knowledge.

The purpose of research can vary depending on the field of study, the research question, and the intended audience. In general, research can be used to:

  • Generate new knowledge and theories
  • Test existing theories or hypotheses
  • Identify trends or patterns
  • Gather information for decision-making
  • Evaluate the effectiveness of programs, policies, or interventions
  • Develop new technologies or products
  • Identify new opportunities or areas for further study.

Objectives of Research

The objectives of research may vary depending on the field of study and the specific research question being investigated. However, some common objectives of research include:

  • To explore and describe a phenomenon: Research can be conducted to describe and understand a phenomenon or situation in greater detail.
  • To test a hypothesis or theory : Research can be used to test a specific hypothesis or theory by collecting and analyzing data.
  • To identify patterns or trends: Research can be conducted to identify patterns or trends in data, which can provide insights into the behavior of a system or population.
  • To evaluate a program or intervention: Research can be used to evaluate the effectiveness of a program or intervention, such as a new drug or educational intervention.
  • To develop new knowledge or technology : Research can be conducted to develop new knowledge or technologies that can be applied to solve practical problems.
  • To inform policy decisions: Research can provide evidence to inform policy decisions and improve public policy.
  • To improve existing knowledge: Research can be conducted to improve existing knowledge and fill gaps in the current understanding of a topic.

Applications of Research

Research has a wide range of applications across various fields and industries. Here are some examples:

  • Medicine : Research is critical in developing new treatments and drugs for diseases. Researchers conduct clinical trials to test the safety and efficacy of new medications and therapies. They also study the underlying causes of diseases to find new ways to prevent or treat them.
  • Technology : Research is crucial in developing new technologies and improving existing ones. Researchers work to develop new software, hardware, and other technological innovations that can be used in various industries such as healthcare, manufacturing, and telecommunications.
  • Education : Research is essential in the field of education to develop new teaching methods and strategies. Researchers conduct studies to determine the effectiveness of various educational approaches and to identify factors that influence student learning.
  • Business : Research is critical in helping businesses make informed decisions. Market research can help businesses understand their target audience and identify trends in the market. Research can also help businesses improve their products and services.
  • Environmental Science : Research is crucial in the field of environmental science to understand the impact of human activities on the environment. Researchers conduct studies to identify ways to reduce pollution, protect natural resources, and mitigate the effects of climate change.

Goal of Research

The ultimate goal of research is to advance our understanding of the world and to contribute to the development of new theories, ideas, and technologies that can be used to improve our lives. Some more common Goals are follows:

  • Explore and discover new knowledge : Research can help uncover new information and insights that were previously unknown.
  • Test hypotheses and theories : Research can be used to test and validate theories and hypotheses, allowing researchers to refine and develop their ideas.
  • Solve practical problems: Research can be used to identify solutions to real-world problems and to inform policy and decision-making.
  • Improve understanding : Research can help improve our understanding of complex phenomena and systems, such as the human body, the natural world, and social systems.
  • Develop new technologies and innovations : Research can lead to the development of new technologies, products, and innovations that can improve our lives and society.
  • Contribute to the development of academic fields : Research can help advance academic fields by expanding our knowledge and understanding of important topics and areas of inquiry.

Importance of Research

The importance of research lies in its ability to generate new knowledge and insights, to test existing theories and ideas, and to solve practical problems.

Some of the key reasons why research is important are:

  • Advancing knowledge: Research is essential for advancing knowledge and understanding in various fields. It enables us to explore and discover new concepts, ideas, and phenomena that can contribute to scientific and technological progress.
  • Solving problems : Research can help identify and solve practical problems and challenges in various domains, such as health care, agriculture, engineering, and social policy.
  • Innovation : Research is a critical driver of innovation, as it enables the development of new products, services, and technologies that can improve people’s lives and contribute to economic growth.
  • Evidence-based decision-making : Research provides evidence and data that can inform decision-making in various fields, such as policy-making, business strategy, and healthcare.
  • Personal and professional development : Engaging in research can also contribute to personal and professional development, as it requires critical thinking, problem-solving, and communication skills.

When to use Research

Research should be used in situations where there is a need to gather new information, test existing theories, or solve problems. Some common scenarios where research is often used include:

  • Scientific inquiry : Research is essential for advancing scientific knowledge and understanding, and for exploring new concepts, theories, and phenomena.
  • Business and market analysis: Research is critical for businesses to gather data and insights about the market, customer preferences, and competition, to inform decision-making and strategy development.
  • Social policy and public administration: Research is often used in social policy and public administration to evaluate the effectiveness of programs and policies, and to identify areas where improvements are needed.
  • Healthcare: Research is essential in healthcare to develop new treatments, improve existing ones, and to understand the causes and mechanisms of diseases.
  • Education : Research is critical in education to evaluate the effectiveness of teaching methods and programs, and to develop new approaches to learning.

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  • Writing a Research Report

.pdf version of this page

This review covers the basic elements of a research report. This is a general guide for what you will see in journal articles or dissertations. This format assumes a mixed methods study, but you can leave out either quantitative or qualitative sections if you only used a single methodology.

This review is divided into sections for easy reference. There are five MAJOR parts of a Research Report:

1.    Introduction 2.    Review of Literature 3.    Methods 4.    Results 5.    Discussion

As a general guide, the Introduction, Review of Literature, and Methods should be about 1/3 of your paper, Discussion 1/3, then Results 1/3.

Section 1 : Cover Sheet (APA format cover sheet) optional, if required.

Section 2: Abstract (a basic summary of the report, including sample, treatment, design, results, and implications) (≤ 150 words) optional, if required.

Section 3 : Introduction (1-3 paragraphs) •    Basic introduction •    Supportive statistics (can be from periodicals) •    Statement of Purpose •    Statement of Significance

Section 4 : Research question(s) or hypotheses •    An overall research question (optional) •    A quantitative-based (hypotheses) •    A qualitative-based (research questions) Note: You will generally have more than one, especially if using hypotheses.

Section 5: Review of Literature ▪    Should be organized by subheadings ▪    Should adequately support your study using supporting, related, and/or refuting evidence ▪    Is a synthesis, not a collection of individual summaries

Section 6: Methods ▪    Procedure: Describe data gathering or participant recruitment, including IRB approval ▪    Sample: Describe the sample or dataset, including basic demographics ▪    Setting: Describe the setting, if applicable (generally only in qualitative designs) ▪    Treatment: If applicable, describe, in detail, how you implemented the treatment ▪    Instrument: Describe, in detail, how you implemented the instrument; Describe the reliability and validity associated with the instrument ▪    Data Analysis: Describe type of procedure (t-test, interviews, etc.) and software (if used)

Section 7: Results ▪    Restate Research Question 1 (Quantitative) ▪    Describe results ▪    Restate Research Question 2 (Qualitative) ▪    Describe results

Section 8: Discussion ▪    Restate Overall Research Question ▪    Describe how the results, when taken together, answer the overall question ▪    ***Describe how the results confirm or contrast the literature you reviewed

Section 9: Recommendations (if applicable, generally related to practice)

Section 10: Limitations ▪    Discuss, in several sentences, the limitations of this study. ▪    Research Design (overall, then info about the limitations of each separately) ▪    Sample ▪    Instrument/s ▪    Other limitations

Section 11: Conclusion (A brief closing summary)

Section 12: References (APA format)

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About research rundowns.

Research Rundowns was made possible by support from the Dewar College of Education at Valdosta State University .

  • Experimental Design
  • What is Educational Research?
  • Writing Research Questions
  • Mixed Methods Research Designs
  • Qualitative Coding & Analysis
  • Qualitative Research Design
  • Correlation
  • Effect Size
  • Instrument, Validity, Reliability
  • Mean & Standard Deviation
  • Significance Testing (t-tests)
  • Steps 1-4: Finding Research
  • Steps 5-6: Analyzing & Organizing
  • Steps 7-9: Citing & Writing

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11.1 The Purpose of Research Writing

Learning objectives.

  • Identify reasons to research writing projects.
  • Outline the steps of the research writing process.

Why was the Great Wall of China built? What have scientists learned about the possibility of life on Mars? What roles did women play in the American Revolution? How does the human brain create, store, and retrieve memories? Who invented the game of football, and how has it changed over the years?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Whether you are a scientist, an artist, a paralegal, or a parent, you probably perform research in your everyday life. When your boss, your instructor, or a family member asks you a question that you do not know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process, and in this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer any question no matter how challenging.

Reasons for Research

When you perform research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you (and other people) have about the world. This is one of the most basic reasons for performing research.

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper . A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. And you may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

No matter what field of study you are interested in, you will most likely be asked to write a research paper during your academic career. For example, a student in an art history course might write a research paper about an artist’s work. Similarly, a student in a psychology course might write a research paper about current findings in childhood development.

Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires a lot of time, effort, and organization. However, writing a research paper can also be a great opportunity to explore a topic that is particularly interesting to you. The research process allows you to gain expertise on a topic of your choice, and the writing process helps you remember what you have learned and understand it on a deeper level.

Research Writing at Work

Knowing how to write a good research paper is a valuable skill that will serve you well throughout your career. Whether you are developing a new product, studying the best way to perform a procedure, or learning about challenges and opportunities in your field of employment, you will use research techniques to guide your exploration. You may even need to create a written report of your findings. And because effective communication is essential to any company, employers seek to hire people who can write clearly and professionally.

Writing at Work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

  • Medical laboratory technician
  • Small business owner
  • Information technology professional
  • Freelance magazine writer

A medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Think about the job of your dreams. How might you use research writing skills to perform that job? Create a list of ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job. How might these skills help you obtain that job?

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

  • Choose a topic.
  • Plan and schedule time to research and write.
  • Conduct research.
  • Organize research and ideas.
  • Draft your paper.
  • Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

As you may recall from Chapter 8 “The Writing Process: How Do I Begin?” , to narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question —a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis . You may use your research question and your working thesis to create a research proposal . In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Before you start researching your topic, take time to plan your researching and writing schedule. Research projects can take days, weeks, or even months to complete. Creating a schedule is a good way to ensure that you do not end up being overwhelmed by all the work you have to do as the deadline approaches.

During this step of the process, it is also a good idea to plan the resources and organizational tools you will use to keep yourself on track throughout the project. Flowcharts, calendars, and checklists can all help you stick to your schedule. See Chapter 11 “Writing from Research: What Will I Learn?” , Section 11.2 “Steps in Developing a Research Proposal” for an example of a research schedule.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources . Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper. You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported.

Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Now you are ready to combine your research findings with your critical analysis of the results in a rough draft. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis or purpose statement.

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism , or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

In the final step of the research writing process, you will revise and polish your paper. You might reorganize your paper’s structure or revise for unity and cohesion, ensuring that each element in your paper flows into the next logically and naturally. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting. When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written paper you can be proud of!

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

  • In which steps of the research writing process are you allowed to change your thesis?
  • In step 2, which types of information should you include in your project schedule?
  • What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

  • People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
  • The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

Writing for Success Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.


  • Research Report
  • Post last modified: 11 January 2022
  • Reading time: 25 mins read
  • Post category: Research Methodology

purpose of report in research

What is Research Report?

Research reporting is the oral or written presentation of the findings in such detail and form as to be readily understood and assessed by the society, economy or particularly by the researchers.

As earlier said that it is the final stage of the research process and its purpose is to convey to interested persons the whole result of the study. Report writing is common to both academic and managerial situations. In academics, a research report is prepared for comprehensive and application-oriented learning. In businesses or organisations, reports are used for the basis of decision making.

Table of Content

  • 1 What is Research Report?
  • 2 Research Report Definition
  • 3.1 Preliminary Part
  • 3.2 Introduction of the Report
  • 3.3 Review of Literature
  • 3.4 The Research Methodology
  • 3.5 Results
  • 3.6 Concluding Remarks
  • 3.7 Bibliography
  • 4 Significance of Report Writing
  • 5 Qualities of Good Report
  • 6.1 Analysis of the subject matter
  • 6.2 Research outline
  • 6.3 Preparation of rough draft
  • 6.4 Rewriting and polishing
  • 6.5 Writing the final draft
  • 7 Precautions for Writing Research Reports
  • 8.1.1 Technical Report
  • 8.1.2 Popular Report
  • 8.2.1 Written Report
  • 8.2.2 Oral Report

Research Report Definition

According to C. A. Brown , “A report is a communication from someone who has information to someone who wants to use that information.”

According to Goode and Hatt , “The preparation of report is the final stage of research, and it’s purpose is to convey to the interested persons the whole result of the study, in sufficient detail and so arranged as to enable each reader to comprehend the data and to determine for himself the validity of the conclusions.”

It is clear from the above definitions of a research report, it is a brief account of the problem of investigation, the justification of its selection and the procedure of analysis and interpretation. It is only a summary of the entire research proceedings.

In other words, it can be defined as written documents, which presents information in a specialized and concise manner.

Contents of Research Report

Although no hard and fast rules can be laid down, the report must contain the following points.

  • Acknowledgement
  • Table of contents
  • List of tables
  • List of graphs
  • Introduction
  • Background of the research study
  • Statement of the problem
  • Brief outline of the chapters
  • Books review
  • Review of articles published in books, journals, periodicals, etc
  • Review of articles published in leading newspapers
  • Working papers / discusssion paper / study reports
  • Articles on authorised websites
  • A broad conclusion and indications for further research
  • The theoretical framework (variables)
  • Model / hypothesis
  • Instruments for data collection
  • Data collection
  • Pilot study
  • Processing of data
  • Hypothesis / model testing
  • Data analysis and interpretation
  • Tables and figures
  • Conclusions
  • Shortcomings
  • Suggestions to the problems
  • Direction for further research

Preliminary Part

The preliminary part may have seven major components – cover, title, preface, acknowledgement, table of contents, list of tables, list of graphs. Long reports presented in book form have a cover made up of a card sheet. The cover contains title of the research report, the authority to whom the report is submitted, name of the author, etc.

The preface introduces the report to the readers. It gives a very brief introduction of the report. In the acknowledgements author mention names of persons and organisations that have extended co-operation and helped in the various stages of research. Table of contents is essential. It gives the title and page number of each chapter.

Introduction of the Report

The introduction of the research report should clearly and logically bring out the background of the problem addressed in the research. The purpose of the introduction is to introduce the research project to the readers. A clear statement of the problem with specific questions to be answered is presented in the introduction. It contains a brief outline of the chapters.

Review of Literature

The third section reviews the important literature related to the study. A comprehensive review of the research literature referred to must be made. Previous research studies and the important writings in the area under study should be reviewed. Review of literature is helpful to provide a background for the development of the present study.

The researcher may review concerned books, articles published in edited books, journals and periodicals. Researcher may also take review of articles published in leading newspapers. A researcher should study working papers/discussion papers/study reports. It is essential for a broad conclusion and indications for further research.

The Research Methodology

Research methodology is an integral part of the research. It should clearly indicate the universe and the selection of samples, techniques of data collection, analysis and interpretation, statistical techniques, etc.

Results contain pilot study, processing of data, hypothesis/model testing, data analysis and interpretation, tables and figures, etc. This is the heart of the research report. If a pilot study is planned to be used, it’s purpose should be given in the research methodology.

The collected data and the information should be edited, coded, tabulated and analysed with a view to arriving at a valid and authentic conclusion. Tables and figures are used to clarify the significant relationship. The results obtained through tables, graphs should be critically interpreted.

Concluding Remarks

The concluding remarks should discuss the results obtained in the earlier sections, as well as their usefulness and implications. It contains findings, conclusions, shortcomings, suggestions to the problem and direction for future research. Findings are statements of factual information based upon the data analysis.

Conclusions must clearly explain whether the hypothesis have been established and rejected. This part requires great expertise and preciseness. A report should also refer to the limitations of the applicability of the research inferences. It is essential to suggest the theoretical, practical and policy implications of the research. The suggestions should be supported by scientific and logical arguments. The future direction of research based on the work completed should also be outlined.


The bibliography is an alphabetic list of books, journal articles, reports, etc, published or unpublished, read, referred to, examined by the researcher in preparing the report. The bibliography should follow standard formats for books, journal articles, research reports.

The end of the research report may consist of appendices, listed in respect of all technical data. Appendices are for the purpose of providing detailed data or information that would be too cumbersome within the main body of the research report.

Significance of Report Writing

Report writing is an important communication medium in organisations. The most crucial findings might have come out through a research report. Report is common to academics and managers also. Reports are used for comprehensive and application oriented learning in academics. In organisations, reports are used for the basis of decision making. The importance of report writing can be discussed as under.

Through research reports, a manager or an executive can quickly get an idea of a current scenario which improves his information base for making sound decisions affecting future operations of the company or enterprise. The research report acts as a means of communication of various research findings to the interested parties, organisations and general public.

Good report writing play, a significant role of conveying unknown facts about the phenomenon to the concerned parties. This may provide new insights and new opportunities to the people. Research report plays a key role in making effective decisions in marketing, production, banking, materials, human resource development and government also. Good report writing is used for economic planning and optimum utilisation of resources for the development of a nation.

Report writing facilitates the validation of generalisation. A research report is an end product of research. As earlier said that report writing provides useful information in arriving at rational decisions that may reform the business and society. The findings, conclusions, suggestions and recommendations are useful to academicians, scholars and policymakers. Report writing provides reference material for further research in the same or similar areas of research to the concerned parties.

While preparing a research report, a researcher should take some proper precautions. Report writing should be simple, lucid and systematic. Report writing should be written speedily without interrupting the continuity of thought. The report writing should sustain the interest of readers.

Qualities of Good Report

Report writing is a highly skilled job. It is a process of analysing, understanding and consolidating the findings and projecting a meaningful view of the phenomenon studied. A good report writing is essential for effective communication.

Following are the essential qualities of good report:

  • A research report is essentially a scientific documentation. It should have a suggestive title, headings and sub-headings, paragraphs arranged in a logical sequence.
  • Good research report should include everything that is relevant and exclude everything that is irrelevant. It means that it should contain the facts rather than opinion.
  • The language of the report should be simple and unambiguous. It means that it should be free from biases of the researchers derived from the past experience. Confusion, pretentiousness and pomposity should be carefully guarded against. It means that the language of the report should be simple, employing appropriate words, idioms and expressions.
  • The report must be free from grammatical mistakes. It must be grammatically accurate. Faulty construction of sentences makes the meaning of the narrative obscure and ambiguous.
  • The report has to take into consideration two facts. Firstly, for whom the report is meant and secondly, what is his level of knowledge. The report has to look to the subject matter of the report and the fact as to the level of knowledge of the person for whom it is meant. Because all reports are not meant for research scholars.

Steps in Writing Research Report

Report writing is a time consuming and expensive exercise. Therefore, reports have to be very sharply focused in purpose content and readership. There is no single universally acceptable method of writing a research report.

Following are the general steps in writing a research report:

Analysis of the subject matter

Research outline, preparation of rough draft, rewriting and polishing, writing the final draft.

This is the first and important step in writing a research report. It is concerned with the development of a subject. Subject matter should be written in a clear, logical and concise manner. The style adopted should be open, straightforward and dignified and folk style language should be avoided.

The data, the reliability and validity of the results of the statistical analysis should be in the form of tables, figures and equations. All redundancy in the data or results presented should be eliminated.

The research outline is an organisational framework prepared by the researcher well in advance. It is an aid to logical organisation of material and a reminder of the points to be stressed in the report. In the process of writing, if need be, outline may be revised accordingly.

Time and place of the study, scope and limitations of the study, study design, summary of pilot study, methods of data collection, analysis interpretation, etc., may be included in a research outline.

Having prepared the primary and secondary data, the researcher has to prepare a rough draft. While preparing the rough draft, the researcher should keep the objectives of the research in mind, and focus on one objective at a time. The researcher should make a checklist of the important points that are necessary to be covered in the manuscript. A researcher should use dictionary and relevant reference materials as and when required.

This is an important step in writing a research report. It takes more time than a rough draft. While rewriting and polishing, a researcher should check the report for weakness in logical development or presentation. He should take breaks in between rewriting and polishing since this gives the time to incubate the ideas.

The last and important step is writing the final draft. The language of the report should be simple, employing appropriate words and expressions and should avoid vague expressions such as ‘it seems’ and ‘there may be’ etc.

It should not used personal pronouns, such as I, We, My, Us, etc and should substitute these by such expressions as a researcher, investigator, etc. Before the final drafting of the report, it is advisable that the researcher should prepare a first draft for critical considerations and possible improvements. It will be helpful in writing the final draft. Finally, the report should be logically outlined with the future directions of the research based on the work completed.

Precautions for Writing Research Reports

A research report is a means of conveying the research study to a specific target audience. The following precautions should be taken while preparing a research report:

  • Its hould belong enough to cover the subject and short enough to preserve interest.
  • It should not be dull and complicated.
  • It should be simple, without the usage of abstract terms and technical jargons.
  • It should offer ready availability of findings with the help of charts, tables and graphs, as readers prefer quick knowledge of main findings.
  • The layout of the report should be in accordance with the objectives of the research study.
  • There should be no grammatical errors and writing should adhere to the techniques of report writing in case of quotations, footnotes and documentations.
  • It should be original, intellectual and contribute to the solution of a problem or add knowledge to the concerned field.
  • Appendices should been listed with respect to all the technical data in the report.
  • It should be attractive, neat and clean, whether handwritten or typed.
  • The report writer should refrain from confusing the possessive form of the word ‘it’ is with ‘it’s.’ The accurate possessive form of ‘it is’ is ‘its.’ The use of ‘it’s’ is the contractive form of ‘it is.
  • A report should not have contractions. Examples are ‘didn’t’ or ‘it’s.’ In report writing, it is best to use the non-contractive form. Therefore, the examples would be replaced by ‘did not’ and ‘it is.’ Using ‘Figure’ instead of ‘Fig.’ and ‘Table’ instead of ‘Tab.’ will spare the reader of having to translate the abbreviations, while reading. If abbreviations are used, use them consistently throughout the report. For example, do not switch among ‘versus,’ and ‘vs’.
  • It is advisable to avoid using the word ‘very’ and other such words that try to embellish a description. They do not add any extra meaning and, therefore, should be dropped.
  • Repetition hampers lucidity. Report writers must avoid repeating the same word more than once within a sentence.
  • When you use the word ‘this’ or ‘these’ make sure you indicate to what you are referring. This reduces the ambiguity in your writing and helps to tie sentences together.
  • Do not use the word ‘they’ to refer to a singular person. You can either rewrite the sentence to avoid needing such a reference or use the singular ‘he or she.’

Types of Research Report

Research reports are designed in order to convey and record the information that will be of practical use to the reader. It is organized into distinct units of specific and highly visible information. The kind of audience addressed in the research report decides the type of report.

Research reports can be categorized on the following basis:

Classification on the Basis of Information

Classification on the basis of representation.

Following are the ways through which the results of the research report can be presented on the basis of information contained:

Technical Report

A technical report is written for other researchers. In writing the technical reports, the importance is mainly given to the methods that have been used to collect the information and data, the presumptions that are made and finally, the various presentation techniques that are used to present the findings and data.

Following are main features of a technical report:

  • Summary: It covers a brief analysis of the findings of the research in a very few pages. 
  • Nature: It contains the reasons for which the research is undertaken, the analysis and the data that is required in order to prepare a report. 
  • Methods employed: It contains a description of the methods that were employed in order to collect the data. 
  • Data: It covers a brief analysis of the various sources from which the data has been collected with their features and drawbacks 
  • Analysis of data and presentation of the findings: It contains the various forms through which the data that has been analysed can be presented. 
  • Conclusions: It contains a brief explanation of findings of the research. 
  • Bibliography: It contains a detailed analysis of the various bibliographies that have been used in order to conduct a research. 
  • Technical appendices: It contains the appendices for the technical matters and for questionnaires and mathematical derivations. 
  • Index: The index of the technical report must be provided at the end of the report.

Popular Report

A popular report is formulated when there is a need to draw conclusions of the findings of the research report. One of the main points of consideration that should be kept in mind while formulating a research report is that it must be simple and attractive. It must be written in a very simple manner that is understandable to all. It must also be made attractive by using large prints, various sub-headings and by giving cartoons occasionally.

Following are the main points that must be kept in mind while preparing a popular report:

  • Findings and their implications : While preparing a popular report, main importance is given to the findings of the information and the conclusions that can be drawn out of these findings.
  • Recommendations for action : If there are any deviations in the report then recommendations are made for taking corrective action in order to rectify the errors.
  • Objective of the study : In a popular report, the specific objective for which the research has been undertaken is presented.
  • Methods employed : The report must contain the various methods that has been employed in order to conduct a research.
  • Results : The results of the research findings must be presented in a suitable and appropriate manner by taking the help of charts and diagrams.
  • Technical appendices : The report must contain an in-depth information used to collect the data in the form of appendices.

Following are the ways through which the results of the research report can be presented on the basis of representation:

  • Writtenreport
  • Oral report

Written Report

A written report plays a vital role in every business operation. The manner in which an organization writes business letters and business reports creates an impression of its standard. Therefore, the organization should emphasize on the improvement of the writing skills of the employees in order to maintain effective relations with their customers.

Writing effective written reports requires a lot of hard work. Therefore, before you begin writing, it is important to know the objective, i.e., the purpose of writing, collection and organization of required data.

Oral Report

At times, oral presentation of the results that are drawn out of research is considered effective, particularly in cases where policy recommendations are to be made. This approach proves beneficial because it provides a medium of interaction between a listener and a speaker. This leads to a better understanding of the findings and their implications.

However, the main drawback of oral presentation is the lack of any permanent records related to the research. Oral presentation of the report is also effective when it is supported with various visual devices, such as slides, wall charts and whiteboards that help in better understanding of the research reports.

Business Ethics

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Corporate social responsibility (CSR)

  • Theories of CSR
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Lean Six Sigma

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  • Value and Waste in Lean Six Sigma
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  • What is Binomial, Poisson, Normal Distribution?
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  • Six Sigma Project Charter
  • Project Decomposition in Six Sigma
  • Critical to Quality (CTQ) Six Sigma
  • Process Mapping Six Sigma
  • Flowchart and SIPOC
  • Gage Repeatability and Reproducibility
  • Statistical Diagram
  • Lean Techniques for Optimisation Flow
  • Failure Modes and Effects Analysis (FMEA)
  • What is Process Audits?
  • Six Sigma Implementation at Ford
  • IBM Uses Six Sigma to Drive Behaviour Change
  • Research Methodology
  • What is Research?
  • What is Hypothesis?
  • Sampling Method

Research Methods

Data collection in research.

  • Methods of Collecting Data
  • Application of Business Research
  • Levels of Measurement
  • What is Sampling?
  • Hypothesis Testing
  • What is Management?
  • Planning in Management
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  • What is Controlling?
  • What is Coordination?
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  • Centralization vs Decentralization
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  • Schools of Management Thought
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  • Who is a Manager?

Operations Research

  • What is Operations Research?
  • Operation Research Models
  • Linear Programming
  • Linear Programming Graphic Solution
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  • Transportation Problem Initial Basic Feasible Solution
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  • Project Network Analysis with Critical Path Method
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  • Simulation in Operation Research
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Operation Management

  • What is Strategy?
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  • Operations Competitive Dimensions
  • Operations Strategy Formulation Process
  • What is Strategic Fit?
  • Strategic Design Process
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  • Corporate Level Strategy
  • Expansion Strategies
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  • Strategic Choice and Strategic Alternatives
  • What is Production Process?
  • What is Process Technology?
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  • Strategic Capacity Management
  • Production and Logistics Strategy
  • Taxonomy of Supply Chain Strategies
  • Factors Considered in Supply Chain Planning
  • Operational and Strategic Issues in Global Logistics
  • Logistics Outsourcing Strategy
  • What is Supply Chain Mapping?
  • Supply Chain Process Restructuring
  • Points of Differentiation
  • Re-engineering Improvement in SCM
  • What is Supply Chain Drivers?
  • Supply Chain Operations Reference (SCOR) Model
  • Customer Service and Cost Trade Off
  • Internal and External Performance Measures
  • Linking Supply Chain and Business Performance
  • Netflix’s Niche Focused Strategy
  • Disney and Pixar Merger
  • Process Planning at Mcdonald’s

Service Operations Management

  • What is Service?
  • What is Service Operations Management?
  • What is Service Design?
  • Service Design Process
  • Service Delivery
  • What is Service Quality?
  • Gap Model of Service Quality
  • Juran Trilogy
  • Service Performance Measurement
  • Service Decoupling
  • IT Service Operation
  • Service Operations Management in Different Sector

Procurement Management

  • What is Procurement Management?
  • Procurement Negotiation
  • Types of Requisition
  • RFX in Procurement
  • What is Purchasing Cycle?
  • Vendor Managed Inventory
  • Internal Conflict During Purchasing Operation
  • Spend Analysis in Procurement
  • Sourcing in Procurement
  • Supplier Evaluation and Selection in Procurement
  • Blacklisting of Suppliers in Procurement
  • Total Cost of Ownership in Procurement
  • Incoterms in Procurement
  • Documents Used in International Procurement
  • Transportation and Logistics Strategy
  • What is Capital Equipment?
  • Procurement Process of Capital Equipment
  • Acquisition of Technology in Procurement
  • What is E-Procurement?
  • E-marketplace and Online Catalogues
  • Fixed Price and Cost Reimbursement Contracts
  • Contract Cancellation in Procurement
  • Ethics in Procurement
  • Legal Aspects of Procurement
  • Global Sourcing in Procurement
  • Intermediaries and Countertrade in Procurement

Strategic Management

  • What is Strategic Management?
  • What is Value Chain Analysis?
  • Mission Statement
  • Business Level Strategy
  • What is SWOT Analysis?
  • What is Competitive Advantage?
  • What is Vision?
  • What is Ansoff Matrix?
  • Prahalad and Gary Hammel
  • Strategic Management In Global Environment
  • Competitor Analysis Framework
  • Competitive Rivalry Analysis
  • Competitive Dynamics
  • What is Competitive Rivalry?
  • Five Competitive Forces That Shape Strategy
  • What is PESTLE Analysis?
  • Fragmentation and Consolidation Of Industries
  • What is Technology Life Cycle?
  • What is Diversification Strategy?
  • What is Corporate Restructuring Strategy?
  • Resources and Capabilities of Organization
  • Role of Leaders In Functional-Level Strategic Management
  • Functional Structure In Functional Level Strategy Formulation
  • Information And Control System
  • What is Strategy Gap Analysis?
  • Issues In Strategy Implementation
  • Matrix Organizational Structure
  • What is Strategic Management Process?

Supply Chain

  • What is Supply Chain Management?
  • Supply Chain Planning and Measuring Strategy Performance
  • What is Warehousing?
  • What is Packaging?
  • What is Inventory Management?
  • What is Material Handling?
  • What is Order Picking?
  • Receiving and Dispatch, Processes
  • What is Warehouse Design?
  • What is Warehousing Costs?

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What is Research? – Purpose of Research


  • By DiscoverPhDs
  • September 10, 2020

Purpose of Research - What is Research

The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. A research purpose is met through forming hypotheses, collecting data, analysing results, forming conclusions, implementing findings into real-life applications and forming new research questions.

What is Research

Simply put, research is the process of discovering new knowledge. This knowledge can be either the development of new concepts or the advancement of existing knowledge and theories, leading to a new understanding that was not previously known.

As a more formal definition of research, the following has been extracted from the Code of Federal Regulations :

purpose of report in research

While research can be carried out by anyone and in any field, most research is usually done to broaden knowledge in the physical, biological, and social worlds. This can range from learning why certain materials behave the way they do, to asking why certain people are more resilient than others when faced with the same challenges.

The use of ‘systematic investigation’ in the formal definition represents how research is normally conducted – a hypothesis is formed, appropriate research methods are designed, data is collected and analysed, and research results are summarised into one or more ‘research conclusions’. These research conclusions are then shared with the rest of the scientific community to add to the existing knowledge and serve as evidence to form additional questions that can be investigated. It is this cyclical process that enables scientific research to make continuous progress over the years; the true purpose of research.

What is the Purpose of Research

From weather forecasts to the discovery of antibiotics, researchers are constantly trying to find new ways to understand the world and how things work – with the ultimate goal of improving our lives.

The purpose of research is therefore to find out what is known, what is not and what we can develop further. In this way, scientists can develop new theories, ideas and products that shape our society and our everyday lives.

Although research can take many forms, there are three main purposes of research:

  • Exploratory: Exploratory research is the first research to be conducted around a problem that has not yet been clearly defined. Exploration research therefore aims to gain a better understanding of the exact nature of the problem and not to provide a conclusive answer to the problem itself. This enables us to conduct more in-depth research later on.
  • Descriptive: Descriptive research expands knowledge of a research problem or phenomenon by describing it according to its characteristics and population. Descriptive research focuses on the ‘how’ and ‘what’, but not on the ‘why’.
  • Explanatory: Explanatory research, also referred to as casual research, is conducted to determine how variables interact, i.e. to identify cause-and-effect relationships. Explanatory research deals with the ‘why’ of research questions and is therefore often based on experiments.

Characteristics of Research

There are 8 core characteristics that all research projects should have. These are:

  • Empirical  – based on proven scientific methods derived from real-life observations and experiments.
  • Logical  – follows sequential procedures based on valid principles.
  • Cyclic  – research begins with a question and ends with a question, i.e. research should lead to a new line of questioning.
  • Controlled  – vigorous measures put into place to keep all variables constant, except those under investigation.
  • Hypothesis-based  – the research design generates data that sufficiently meets the research objectives and can prove or disprove the hypothesis. It makes the research study repeatable and gives credibility to the results.
  • Analytical  – data is generated, recorded and analysed using proven techniques to ensure high accuracy and repeatability while minimising potential errors and anomalies.
  • Objective  – sound judgement is used by the researcher to ensure that the research findings are valid.
  • Statistical treatment  – statistical treatment is used to transform the available data into something more meaningful from which knowledge can be gained.

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Types of Research

Research can be divided into two main types: basic research (also known as pure research) and applied research.

Basic Research

Basic research, also known as pure research, is an original investigation into the reasons behind a process, phenomenon or particular event. It focuses on generating knowledge around existing basic principles.

Basic research is generally considered ‘non-commercial research’ because it does not focus on solving practical problems, and has no immediate benefit or ways it can be applied.

While basic research may not have direct applications, it usually provides new insights that can later be used in applied research.

Applied Research

Applied research investigates well-known theories and principles in order to enhance knowledge around a practical aim. Because of this, applied research focuses on solving real-life problems by deriving knowledge which has an immediate application.

Methods of Research

Research methods for data collection fall into one of two categories: inductive methods or deductive methods.

Inductive research methods focus on the analysis of an observation and are usually associated with qualitative research. Deductive research methods focus on the verification of an observation and are typically associated with quantitative research.

Research definition

Qualitative Research

Qualitative research is a method that enables non-numerical data collection through open-ended methods such as interviews, case studies and focus groups .

It enables researchers to collect data on personal experiences, feelings or behaviours, as well as the reasons behind them. Because of this, qualitative research is often used in fields such as social science, psychology and philosophy and other areas where it is useful to know the connection between what has occurred and why it has occurred.

Quantitative Research

Quantitative research is a method that collects and analyses numerical data through statistical analysis.

It allows us to quantify variables, uncover relationships, and make generalisations across a larger population. As a result, quantitative research is often used in the natural and physical sciences such as engineering, biology, chemistry, physics, computer science, finance, and medical research, etc.

What does Research Involve?

Research often follows a systematic approach known as a Scientific Method, which is carried out using an hourglass model.

A research project first starts with a problem statement, or rather, the research purpose for engaging in the study. This can take the form of the ‘ scope of the study ’ or ‘ aims and objectives ’ of your research topic.

Subsequently, a literature review is carried out and a hypothesis is formed. The researcher then creates a research methodology and collects the data.

The data is then analysed using various statistical methods and the null hypothesis is either accepted or rejected.

In both cases, the study and its conclusion are officially written up as a report or research paper, and the researcher may also recommend lines of further questioning. The report or research paper is then shared with the wider research community, and the cycle begins all over again.

Although these steps outline the overall research process, keep in mind that research projects are highly dynamic and are therefore considered an iterative process with continued refinements and not a series of fixed stages.

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Purpose of Research - What is Research

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purpose of report in research

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Research Report

Research Report Meaning, Characteristics and Types

Table of contents:-, research report meaning, characteristics of good research report, key characteristics of research report, types of research report, stages in preparation of research report, characteristics of a good report.

A research report is a document that conveys the outcomes of a study or investigation. Its purpose is to communicate the research’s findings, conclusions, and implications to a particular audience. This report aims to offer a comprehensive and unbiased overview of the research process, methodology, and results.

Once the researcher has completed data collection , data processing, developing and testing hypotheses, and interpretation of responses, the next important phase in research is the preparation of the research report. A research report is essential for the communication of research findings to its potential users.

The research report must be free from personal bias, external influences, and subjective factors. i.e., it must be free from one’s liking and disliking. The research report must be prepared to meet impersonal needs.

What is Research Report?

According to Lancaster, “A report is a statement of collected and considered facts, so drawn-ups to give clear and concise information to persons who are not already in possession of the full facts of the subject matter of the report”.

When researchers communicate their results in writing, they create a research report. It includes the research methodology, approaches, data collection precautions, research findings, and recommendations for solving related problems. Managers can put this result into action for more effective decision making .

Generally, top management places a higher emphasis on obtaining the research outcome rather than delving into the research procedure. Hence, the research report acts as a presentation that highlights the procedure and methodology adopted by the researcher.

The research report presents the complete procedure in a comprehensive way that in turn helps the management in making crucial decisions. Creating a research report adheres to a specific format, sequence, and writing style.

Enhance the effectiveness of a research report by incorporating various charts, graphs, diagrams, tables, etc. By using different representation techniques, researchers can convince the audience as well as the management in an effective way.

Characteristics of a good research report are listed below:

  • Clarity and Completeness
  • Reliability
  • Comprehensibility and Readability
  • Logical Content

characteristics of a good research report

The following paragraphs outline the characteristics of a good research report.

1) Accuracy

Report information must be accurate and based on facts, credible sources and data to establish reliability and trustworthiness. It should not be biased by the personal feelings of the writer. The information presented must be as precise as possible.

2) Simplicity

The language of a research report should be as simple as possible to ensure easy understanding. A good report communicates its message clearly and without ambiguity through its language.

It is a document of practical utility; therefore, it should be grammatically accurate, brief, and easily understood. 

Jargon and technical words should be avoided when writing the report. Even in a technical report, there should be restricted use of technical terms if it is to be presented to laymen.

3) Clarity and Completeness

The report must be straightforward, lucid, and comprehensive in every aspect. Ambiguity should be avoided at all costs. Clarity is achieved through the strategic and practical organization of information. Report writers should divide their report into short paragraphs with headings and insert other suitable signposts to enhance clarity. They should: 

  • Approach their task systematically, 
  • Clarify their purpose, 
  • Define their sources, 
  • State their findings and 
  • Make necessary recommendations. 

A report should concisely convey the key points without unnecessary length, ensuring that the reader’s patience is not lost and ideas are not confused. Many times, people lack the time to read lengthy reports.

However, a report must also be complete. Sometimes, it is important to have a detailed discussion about the facts. A report is not an essay; therefore, points should be added to it.

5) Appearance

A report requires a visually appealing presentation and, whenever feasible, should be attention-grabbing. An effective report depends on the arrangement, organization, format, layout, typography, printing quality, and paper choice. Big companies often produce very attractive and colourful Annual Reports to showcase their achievements and financial performance.

6) Comprehensibility and Readability

Reports should be clear and straightforward for easy understanding. The style of presentation and the choice of words should be attractive to readers. The writer must present the facts in elegant and grammatically correct English so that the reader is compelled to read the report from beginning to end.

Only then does a report serve its purpose. A report written by different individuals on the same subject matter can vary depending on the intended audience.

7) Reliability

Reports should be reliable and should not create an erroneous impression in the minds of readers due to oversight or neglect. The facts presented in a report should be pertinent.

Every fact in a report must align with the central purpose, but it is also vital to ensure that all pertinent information is included.

Irrelevant facts can make a report confusing, and the exclusion of relevant facts can render it incomplete and likely to mislead.

Report writing should not incur unnecessary expenses. Cost-effective methods should be used to maintain a consistent level of quality when communicating the content.

9) Timelines

Reports can be valuable and practical when they reach the readers promptly. Any delay in the submission of reports renders the preparation of reports futile and sometimes obsolete.

10) Logical Content

The points mentioned in a report should be arranged in a step-by-step logical sequence and not haphazardly. Distinctive points should have self-explanatory headings and sub-headings. The scientific accuracy of facts is very essential for a report.

Planning is necessary before a report is prepared, as reports invariably lead to decision-making, and inaccurate facts may result in unsuccessful decisions.

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A research report serves as a means of communicating research findings to the readers effectively.

Characteristics of Research Report

  • Clarity in Information
  • Optimal Length
  • Objective and Simple Language
  • Clear Thinking and Logical Organization
  • Engaging Style
  • Clarity in Presentation
  • Readability
  • Best Composition Practices
  • Inferences and Conclusions
  • Proper References
  • Attractive Appearance

i) Clarity in Information

A well-defined research report must define the what, why, who, whom, when, where, and how of the research study. It must help the readers to understand the focus of the information presented.

ii) Optimal Length

The report should strike a balance, being sufficiently brief and appropriately extended. It should cover the subject matter adequately while maintaining the reader’s interest.

iii) Objective and Simple Language

The report should be written in an objective style, employing simple language. Correctness, precision, and clarity should be prioritized, avoiding wordiness, indirection, and pompous language.

iv) Clear Thinking and Logical Organization

An excellent report integrates clear thinking, logical organization, and sound interpretation of the research findings.

v) Engaging Style

It should not be dull; instead, it should captivate and sustain the reader’s interest.

vi) Accuracy

Accuracy is paramount. The report must present facts objectively, eschewing exaggerations and superlatives.

vii) Clarity in Presentation

Presentation clarity is achieved through familiar words, unambiguous statements, and explicit definitions of new concepts or terms.

viii) Coherence

The logical flow of ideas and a coherent sequence of sentences contribute to a smooth continuity of thought.

ix) Readability

Even technical reports should be easily understandable. Translate technicalities into reader-friendly language.

x) Best Composition Practices

Follow best composition practices, ensuring readability through proper paragraphing, short sentences, and the use of illustrations, examples, section headings, charts, graphs, and diagrams.

xi) Inferences and Conclusions

Draw sound inferences and conclusions from statistical tables without repeating them in verbal form.

xii) Proper References

Footnote references should be correctly formatted, and the bibliography should be reasonably complete.

xiii) Attractive Appearance

The report should be visually appealing, maintaining a neat and clean appearance, whether typed or printed.

xiv) Error-Free

The report should be free from all types of mistakes, including language, factual, spelling, and calculation errors.

In striving for these qualities, the researcher enhances the overall quality of the report.

Research reports are of the following types:

  • Technical Report
  • Manuscripts for Journal Articles
  • Thesis and Dissertations
  • Other Types of Research Report

Types of Research Report

1) Technical Report

Technical reports are reports which contain detailed information about the research problem and its findings. These reports are typically subject to review by individuals interested in research methodology. Such reports include detailed descriptions of used methods for research design such as universe selection , sample preparation, designing questionnaire , identifying potential data sources, etc. These reports provide a complete description of every step, method, and tool used. When crafting technical reports, we assume that users possess knowledge of research methodology, which is why the language used in these reports is technical. Technical reports are valuable in situations where there is a need for statistical analysis of collected data. Researchers also employ it in conducting a series of research studies, where they can repetitively use the methodology.

2) Manuscripts for Journal Articles

When authors prepare a report with a particular layout or design for publishing in an academic or scientific journal, it becomes a “manuscript for journal articles”. Journal articles are a concise and complete presentation of a particular research study. While technical reports present a detailed description of all the activities in research, journal articles are known for presenting only a few critical areas or findings of a study. The readers or audience of journal articles include other researchers, management and executives, strategic analysts and the general public, interested in the topic.

In general, a manuscript for a journal article typically ranges from 10 to 30 pages in length. Sometimes there is a page or word limit for preparing the report. Authors primarily submit manuscripts for journal articles online, although they occasionally send paper copies through regular mail.

3) Thesis and Dissertations

Students working towards a Master’s, PhD, or another higher degree generally produce a thesis or dissertation, which is a form of research report. Like other normal research reports, the thesis or dissertation usually describes the design, tools or methods and results of the student’s research in detail.

These reports typically include a detailed section called the literature review, which encompasses relevant literature and previous studies on the topic. Firstly, the work or research of the student is analysed by a professional researcher or an expert in that particular research field, and then the thesis is written under the guidance of a professional supervisor. Dissertations and theses usually span approximately 120 to 300 pages in length.

Generally, the university or institution decides the length of the dissertation or thesis. A distinctive feature of a thesis or a dissertation is that it is quite economical, as it requires few printed and bound copies of the report. Sometimes electronic copies are required to be submitted along with the hard copy of the thesis or dissertations. Compact discs (CDs) are used to generate the electronic copy.

4) Other Types of Research Report

Along with the above-mentioned types, there are some other types of research reports, which are as follows:

  • Popular Report
  • Interim Report
  • Summary Report
  • Research Abstract

i) Popular Report

A popular report is prepared for the use of administrators, executives, or managers. It is simple and attractive in the form of a report. Clear and concise statements are used with less technical or statistical terms. Data representation is kept very simple through minimal use of graphs and charts. It has a different format than that of a technical one by liberally using margins and blank spaces. The style of writing a popular report is journalistic and precise. It is written to facilitate reading rapidly and comprehending quickly.

ii) Interim Report

An interim report is a kind of report which is prepared to show the sponsors, the progress of research work before the final presentation of the report. It is prepared when there is a certain time gap between the data collection and presentation. In this scenario, the completed portion of data analysis along with its findings is described in a particular interim report.

iii) Summary Report

This type of report is related to the interest of the general public. The findings of such a report are helpful for the decision making of general users. The language used for preparing a summary report is comprehensive and simple. The inclusion of numerous graphs and tables enhances the report’s overall clarity and comprehension. The main focus of this report is on the objectives, findings, and implications of the research issue.

iv) Research Abstract

The research abstract is a short presentation of the technical report. All the elements of a particular technical report, such as the research problem, objectives, sampling techniques, etc., are described in the research abstract but the description is concise and easy.

Research reports result from meticulous and deliberate work. Consequently, the preparation of the information can be delineated into the following key stages:

1) Logical Understanding and Subject Analysis: This stage involves a comprehensive grasp and analysis of the subject matter.

2) Planning/Designing the Final Outline: In this phase, the final outline of the report is meticulously planned and designed.

3) Write-Up/Preparation of Rough Draft: The report takes shape during this stage through the composition of a rough draft.

4) Polishing/Finalization of the Research Report: The final stage encompasses refining and polishing the report to achieve its ultimate form.

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Logical understanding and subject analysis.

This initial stage focuses on the subject’s development, which can be achieved through two approaches:

  • Logical development and
  • Chronological development

Logical development relies on mental connections and associations between different aspects facilitated by rational analysis. Typically, this involves progressing from simple to complex elements. In contrast, chronological development follows a sequence of time or events, with instructions or descriptions often adhering to chronological order.

Designing the Final Outline of the Research Report

This marks the second stage in report writing. Once the subject matter is comprehended, the subsequent step involves structuring the report, arranging its components, and outlining them. This stage is also referred to as the planning  and organization stage. While ideas may flow through the author’s mind, they must create a plan, sketch, or design. These are necessary for achieving a harmonious succession to become more accessible, and the author may be unsure where to commence or conclude. Effective communication of research results hinges not only on language but predominantly on the meticulous planning and organization of the report.

Preparation of the Rough Draft

The third stage involves the writing and drafting of the report. This phase is pivotal for the researcher as they translate their research study into written form, articulating what they have accomplished and how they intend to convey it.

The clarity in communication and reporting during this stage is influenced by several factors, including the audience, the technical complexity of the problem, the researcher’s grasp of facts and techniques, their proficiency in the language (communication skills), the completeness of notes and documentation, and the availability of analyzed results.

Depending on these factors, some authors may produce the report with just one or two drafts. In contrast, others, with less command over language and a lack of clarity about the problem and subject matter, may require more time and multiple drafts (first draft, second draft, third draft, fourth draft, etc.).

Finalization of the Research Report

This marks the last stage, potentially the most challenging phase in all formal writing. Constructing the structure is relatively easy, but refining and adding the finishing touches require considerable time. Consider, for instance, the construction of a house. The work progresses swiftly up to the roofing (structure) stage, but the final touches and completion demand a significant amount of time.

The rough draft, whether it is the second draft or the n th draft, must undergo rewriting and polishing to meet the requirements. The meticulous revision of the rough draft is what distinguishes a mediocre piece of writing from a good one. During the polishing and finalization phase, it is crucial to scrutinize the report for weaknesses in the logical development of the subject and the cohesion of its presentation. Additionally, attention should be given to the mechanics of writing, including language, usage, grammar, spelling, and punctuation.

Good research possesses certain characteristics, which are as follows:

  • Empirical Basis
  • Logical Approach
  • Systematic Nature
  • Replicability
  • Validity and Verifiability
  • Theory and Principle Development

1. Empirical Basis: It implies that any conclusion drawn is grounded in hardcore evidence collected from real-life experiences and observations. This foundation provides external validity to research results.

2. Logical Approach: Good research is logical, guided by the rules of reasoning and analytical processes of induction (general to specific) and deduction (particular to the public). Logical reasoning is integral to making research feasible and meaningful in decision-making.

3. Systematic Nature: Good research is systematic, which adheres to a structured set of rules, following specific steps in a defined sequence. Systematic research encourages creative thinking while avoiding reliance on guesswork and intuition to reach conclusions.

4. Replicability: Scientific research designs, procedures, and results should be replicable. This ensures that anyone apart from the original researcher can assess their validity. Researchers can use or replicate results obtained by others, making the procedures and outcomes of the research both replicable and transmittable.

5. Validity and Verifiability: Good research involves precise observation and accurate description. The researcher selects reliable and valid instruments for data collection, employing statistical measures to portray results accurately. The conclusions drawn are correct and verifiable by both the researcher and others.

6. Theory and Principle Development: It contributes to formulating theories and principles, aiding accurate predictions about the variables under study. By making sound generalizations based on observed samples, researchers extend their findings beyond immediate situations, objects, or groups, formulating generalizations or theories about these factors.

1. What are the key characteristics of research report?

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  • Research Objectives | Definition & Examples

Research Objectives | Definition & Examples

Published on July 12, 2022 by Eoghan Ryan . Revised on November 20, 2023.

Research objectives describe what your research is trying to achieve and explain why you are pursuing it. They summarize the approach and purpose of your project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement . They should:

  • Establish the scope and depth of your project
  • Contribute to your research design
  • Indicate how your project will contribute to existing knowledge

Table of contents

What is a research objective, why are research objectives important, how to write research aims and objectives, smart research objectives, other interesting articles, frequently asked questions about research objectives.

Research objectives describe what your research project intends to accomplish. They should guide every step of the research process , including how you collect data , build your argument , and develop your conclusions .

Your research objectives may evolve slightly as your research progresses, but they should always line up with the research carried out and the actual content of your paper.

Research aims

A distinction is often made between research objectives and research aims.

A research aim typically refers to a broad statement indicating the general purpose of your research project. It should appear at the end of your problem statement, before your research objectives.

Your research objectives are more specific than your research aim and indicate the particular focus and approach of your project. Though you will only have one research aim, you will likely have several research objectives.

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Research objectives are important because they:

  • Establish the scope and depth of your project: This helps you avoid unnecessary research. It also means that your research methods and conclusions can easily be evaluated .
  • Contribute to your research design: When you know what your objectives are, you have a clearer idea of what methods are most appropriate for your research.
  • Indicate how your project will contribute to extant research: They allow you to display your knowledge of up-to-date research, employ or build on current research methods, and attempt to contribute to recent debates.

Once you’ve established a research problem you want to address, you need to decide how you will address it. This is where your research aim and objectives come in.

Step 1: Decide on a general aim

Your research aim should reflect your research problem and should be relatively broad.

Step 2: Decide on specific objectives

Break down your aim into a limited number of steps that will help you resolve your research problem. What specific aspects of the problem do you want to examine or understand?

Step 3: Formulate your aims and objectives

Once you’ve established your research aim and objectives, you need to explain them clearly and concisely to the reader.

You’ll lay out your aims and objectives at the end of your problem statement, which appears in your introduction. Frame them as clear declarative statements, and use appropriate verbs to accurately characterize the work that you will carry out.

The acronym “SMART” is commonly used in relation to research objectives. It states that your objectives should be:

  • Specific: Make sure your objectives aren’t overly vague. Your research needs to be clearly defined in order to get useful results.
  • Measurable: Know how you’ll measure whether your objectives have been achieved.
  • Achievable: Your objectives may be challenging, but they should be feasible. Make sure that relevant groundwork has been done on your topic or that relevant primary or secondary sources exist. Also ensure that you have access to relevant research facilities (labs, library resources , research databases , etc.).
  • Relevant: Make sure that they directly address the research problem you want to work on and that they contribute to the current state of research in your field.
  • Time-based: Set clear deadlines for objectives to ensure that the project stays on track.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.


  • Sampling methods
  • Simple random sampling
  • Stratified sampling
  • Cluster sampling
  • Likert scales
  • Reproducibility


  • Null hypothesis
  • Statistical power
  • Probability distribution
  • Effect size
  • Poisson distribution

Research bias

  • Optimism bias
  • Cognitive bias
  • Implicit bias
  • Hawthorne effect
  • Anchoring bias
  • Explicit bias

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

Your research objectives indicate how you’ll try to address your research problem and should be specific:

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

  • Budget constraints or any specifics of grant funding
  • Your proposed timeline and duration
  • Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
  • Any inclusion and exclusion criteria
  • Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

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Section 1- Evidence-based practice (EBP)

Chapter 6: Components of a Research Report

Components of a research report.

Partido, B.B.

Elements of  research report

Introduction What is the issue?
Methods What methods have been used to investigate the issue?
Results What was found?
Discussion What are the implications of the findings?

The research report contains four main areas:

  • Introduction – What is the issue? What is known? What is not known? What are you trying to find out? This sections ends with the purpose and specific aims of the study.
  • Methods – The recipe for the study. If someone wanted to perform the same study, what information would they need? How will you answer your research question? This part usually contains subheadings: Participants, Instruments, Procedures, Data Analysis,
  • Results – What was found? This is organized by specific aims and provides the results of the statistical analysis.
  • Discussion – How do the results fit in with the existing  literature? What were the limitations and areas of future research?

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What Is a Research Report?

Understanding research reports, financial analyst research reports, research report impact, conflicts of interest.

  • Fundamental Analysis

What Is a Research Report? How They're Produced and Impact

James Chen, CMT is an expert trader, investment adviser, and global market strategist.

purpose of report in research

A research report is a document prepared by an analyst or strategist who is a part of the investment research team in a stock brokerage or investment bank . A research report may focus on a specific stock or industry sector, a currency, commodity or fixed-income instrument, or on a geographic region or country. Research reports generally, but not always, have actionable recommendations such as investment ideas that investors can act upon.

Research reports are produced by a variety of sources, ranging from market research firms to in-house departments at large organizations. When applied to the investment industry, the term usually refers to sell-side research, or investment research produced by brokerage houses.

Such research is disseminated to the institutional and retail clients of the brokerage that produces it. Research produced by the buy-side, which includes pension funds, mutual funds, and portfolio managers , is usually for internal use only and is not distributed to external parties.

Financial analysts may produce research reports for the purpose of supporting a particular recommendation, such as whether to buy or sell a particular security or whether a client should consider a particular financial product. For example, an analyst may create a report in regards to a new offering being proposed by a company. The report could include relevant metrics regarding the company itself, such as the number of years they have been in operation as well as the names of key stakeholders , along with statistics regarding the current state of the market in which the company participates. Information regarding overall profitability and the intended use of the funds can also be included.

Enthusiasts of the Efficient Market Hypothesis (EMH) might insist that the value of professional analysts' research reports is suspect and that investors likely place too much confidence in the conclusions such analysts make. While a definitive conclusion about this topic is difficult to make because comparisons are not exact, some research papers do exist which claim empirical evidence supporting the value of such reports.

One such paper studied the market for India-based investments and analysts who cover them. The paper was published in the March 2014 edition of the International Research Journal of Business and Management. Its authors concluded that analyst recommendations do have an impact and are beneficial to investors at least in short-term decisions.

While some analysts are functionally unaffiliated, others may be directly or indirectly affiliated with the companies for which they produce reports. Unaffiliated analysts traditionally perform independent research to determine an appropriate recommendation and may have a limited concern regarding the outcome.

Affiliated analysts may feel best served by ensuring any research reports portray clients in a favorable light. Additionally, if an analyst is also an investor in the company on which the report is based, he may have a personal incentive to avoid topics that may result in a lowered valuation of the securities in which he has invested.

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A research report is one big argument how and why you came up with your conclusions. To make it a convincing argument, a typical guiding structure has developed. In the different chapters, distinct issues need to be addressed to explain to the reader why your conclusions are valid. The governing principle for writing the report is full disclosure: to explain everything and ensure replicability by another researcher.

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Hunziker, S., Blankenagel, M. (2021). Writing up a Research Report. In: Research Design in Business and Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-34357-6_4

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Doing Research in Education: Theory and Practice

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Hannah, D.R. and Lautsch, B.A. (2010) ‘Counting in Qualitative Research: Why to Conduct it, When to Avoid it, and When to Closet it’, in Journal of Management Inquiry , 20(1): 14–22.

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Evaluating AI Literacy in Academic Libraries: A Survey Study with a Focus on U.S. Employees

Leo S. Lo *

This survey investigates artificial intelligence (AI) literacy among academic library employees, predominantly in the United States, with a total of 760 respondents. The findings reveal a modest self-rated understanding of AI concepts, limited hands-on experience with AI tools, and notable gaps in discussing ethical implications and collaborating on AI projects. Despite recognizing the benefits, readiness for implementation appears low among participants. Respondents emphasize the need for comprehensive training and the establishment of ethical guidelines. The study proposes a framework defining core components of AI literacy tailored for libraries. The results offer insights to guide professional development and policy formulation as libraries increasingly integrate AI into their services and operations.


In a world increasingly dictated by algorithms, artificial intelligence (AI) is not merely a technological phenomenon, it is a transformative force that redefines our intellectual, social, and professional landscapes (McKinsey and Company, 2023). The rapid integration of AI in our everyday lives has profound implications for higher education, a sector entrusted with preparing individuals to navigate, contribute to, and thrive in this AI-driven era. From personalized learning environments to automated administrative tasks, AI’s influence in higher education is omnipresent and its potential boundless. However, this potential can only be harnessed effectively if those at the frontline of academia—our educators, researchers, administrators, and, notably, academic library employees—are equipped with the necessary AI literacy (UNESCO, 2021). Without an understanding of AI’s principles, capabilities, and ethical considerations, higher education risks falling prey to AI’s pitfalls rather than leveraging its benefits.

The potential risks and benefits underscore a pressing need to scrutinize and elevate AI literacy within the higher education community—a task that begins with understanding its current state. As facilitators of information and knowledge, academic library employees stand at the crossroads of this AI revolution, making their AI literacy an imperative, not a choice, for the future of higher education.

AI Literacy: Context and Background

In an era marked by exponential growth in digital technology, the concept of literacy has evolved beyond traditional reading and writing skills to encompass a wide array of digital competencies. One such competency, which is gaining critical importance in higher education, is AI literacy. With AI systems beginning to permeate every facet of university operations—from learning management systems to research analytics—the ability to understand and navigate these AI tools has become an essential skill for academic library employees.

AI literacy, a subset of digital literacy, specifically pertains to understanding AI’s principles, applications, and ethical considerations. It involves not only the ability to use AI tools effectively, but also the capacity to evaluate their outputs critically, to understand their underlying mechanisms, and to contemplate their ethical and societal implications. AI literacy is not just for computer professionals; as Lo (2023b) and Cetindamar et al. (2022) emphasize, operationalizing AI literacy for non-specialists is essential.

The significance of AI literacy in higher education is underscored by several contemporary trends and challenges. Companies and governments globally are engaged in fierce competition to stay at the forefront of AI integration. Concurrently, the rapid proliferation of AI is giving rise to a host of ethical and privacy concerns that require informed stewardship (Cox, 2022). Furthermore, the COVID-19 pandemic has accelerated the digital transformation of higher education, leading to an increased reliance on AI technologies for remote learning and operations. This reliance further points to the necessity of AI literacy among academic library employees, who play a pivotal role in facilitating online learning and research.

As artificial intelligence proliferates across higher education, developing AI literacy is increasingly recognized as a priority to prepare students, faculty, staff, and administrators to harness AI’s potential, while mitigating risks (Ng et al., 2021). Hervieux and Wheatley’s (2021) 2019 study (n=163) found that academic librarians require more training regarding artificial intelligence and its potential applications in libraries. The U.S. Department of Education’s recent report (2023) on AI emphasizes the growing importance of AI literacy for educators and students, highlighting the necessity of understanding and integrating AI technologies in educational settings. This report aligns with the broader discourse on AI literacy and emphasizes the need to equip library professionals with skills needed to evaluate and utilize AI tools effectively (Lo, 2023a).

While efforts to promote AI literacy are growing, the required content for different target groups remains ambigu­ous. Some promising measurement tools have been proposed, such as Pinski and Benlian’s (2023) multidimensional scale assessing perceived knowledge of AI technology, processes, collaboration, and design. However, further validation of AI literacy assessments is required. Developing rigorous definitions and measurements is crucial for implementing effective AI literacy initiatives.

Ridley and Pawlick-Potts (2021) put forth the concept of algorithmic literacy, involving understanding algorithms and their influence, recognizing their uses, assessing their impacts, and positioning individuals as active agents rather than passive recipients of algorithmic decision-making. They propose libraries can contribute to algorithmic literacy by integrating it into information literacy education and supporting explainable AI.

Ocaña-Fernández et al. (2019) argued curriculum and skills training changes are critical to prepare students and faculty for an AI future, though also warn about digital inequality issues. Laupichler et al.’s (2022) scoping review reveals efforts to teach foundational AI literacy to non-specialists are still in formative stages. Proposed essential skills vary considerably across frameworks, and robust evaluations of AI literacy programs are lacking. Findings indicate that carefully designed AI literacy courses show promise for knowledge gains; however, research substantiating appropriate frameworks, core competencies and effective instructional approaches for diverse audiences remains an open need.

Within libraries, Heck et al. (2019) discussed the interplay of information literacy and AI. They propose that AI could aid information literacy teaching through timely feedback and tracking skill development, but note that common evaluation approaches would need establishing first. Information literacy empowers learners to actively engage with, not just passively consume from, AI systems. Lo (2023c) proposed a framework to utilize prompt engineering to enhance information literacy and critical thinking skills.

Oliphant (2015) examined intelligent agents for library reference services. The analysis found they rapidly retrieve information but lack human evaluation abilities. Findings suggest librarians will need to guide users in critically evaluating AI-generated results, indicating that information literacy instruction remains crucial. Furthermore, Lund et al. (2023) discuss the ethical implications of using large language models, such as ChatGPT, in scholarly publishing, emphasizing the need for ethical considerations and the potential impact of AI on research practices.

While research is still emerging, initial findings highlight the need for rigorous, tailored AI literacy initiatives encompassing technical skills, critical perspectives, and ethical considerations. As AI becomes further entwined with education and work, developing validated frameworks, assessments, and instructional approaches to enhance multidimensional AI literacy across contexts and roles is an urgent priority. This study seeks to contribute by investigating AI literacy specifically among academic library employees.

Purpose of the Study

The rapid pace of AI development and integration in higher education heightens the need to address this research gap. As AI continues to evolve and permeate further into academic libraries, the demand for AI-literate library employees will only increase. Failure to understand the current state of AI literacy, and to identify the gaps, could result in a significant skills deficit that would impedes the effective utilization of AI in academic libraries.

In light of this, the purpose of this study is to embark on an investigation of AI literacy among academic library employees. The study seeks to answer the following critical research questions:

  • What is the current level of AI literacy among academic library employees?
  • What gaps exist in their AI literacy, and how can these gaps be addressed through professional development and training programs?
  • What are their perceptions of generative AI, and what implications do they foresee for the library profession?

By addressing these questions, this study aims to fill a research gap and provide insights that can inform policy and practice in higher education. It strives to shed light on the competencies that academic library employees possess, identify the gaps that need to be addressed, and propose strategies for enhancing AI literacy among this essential group of higher education professionals.

Theoretic Framework

The Technological Pedagogical Content Knowledge (TPACK) framework developed by Mishra and Koehler (2006) serves as the theoretical foundation for this study. TPACK has also been advocated as a useful decision-making structure for librarians evaluating instructional technologies (Sobel & Grotti, 2013).

Mishra and Koehler (2006) explain that TPACK involves flexible, context-specific application of technology, pedagogy, and content knowledge. It goes beyond isolated knowledge of the concepts to an integrated understanding. TPACK development requires moving past viewing technology as an “add-on” and focusing on the connections between technology, content, and pedagogy in particular educational contexts.

In the context of this study, the researcher applied the TPACK framework to examine AI literacy specifically among academic library professionals. The three key components of the TPACK framework are interpreted as:

  • Technological Knowledge (TK)—Knowledge about AI itself, including its principles, capabilities, and limitations. This encompasses understanding AI as a technology and its potential applications in library settings.
  • Pedagogical Knowledge (PK)—Knowledge about how AI can be used to enhance library services and facilitate learning. This relates to understanding how AI can be integrated into library services to improve user experience, streamline operations, and support learning.
  • Content Knowledge (CK)—Knowledge about the library’s content and services. This involves perceiving the potential impact of AI on the library’s content and services, and how AI can enhance their management and delivery.

This tailored application of the TPACK framework will allow a multidimensional assessment of AI literacy among academic library employees. It facilitates examining employees’ understanding of AI as a technology (TK), perceptions of how AI can enhance library services (PK), and the potential impact of AI on the library’s content and services (CK).

Significance of the Study

The significance of this study lies in its potential to contribute to academic library policy, practice, and theory in several ways. Firstly, it utilizes the TPACK framework to evaluate AI literacy among academic library employees, identifying competencies, gaps, and necessary strategies. This insight is crucial for designing effective professional development programs, as well as for resource allocation. Secondly, it adds to the discourse on digital literacy in higher education by specifically focusing on AI literacy, aiding in understanding its role and implications. Thirdly, the study provides insights into the ethical, practical, and opportunity dimensions of AI technology integration in libraries, informing best practices and guidelines for its responsible use. Lastly, by applying the TPACK framework to AI literacy in libraries, the study expands its theoretical applications and offers a robust basis for future research in technology integration in academic settings.


Research design.

This study employs a survey-based approach to explore AI literacy among academic library employees, chosen for its ability to quickly gather extensive data across a geographically diverse group. The method aligns with the TPACK framework, highlighting the integration of technological, pedagogical, and content knowledge. Surveys facilitate the collection of standardized data, allowing for comparisons across different roles and demographics. This design is particularly effective for descriptive research in higher education, making it suitable for assessing the current state of AI literacy in academic libraries.


The researcher utilized a comprehensive approach to recruit a diverse group of academic library employees for the survey. This involved posting on professional listservs across various roles and regions in librarianship (Appendix A), as well directly contacting directors of prominent library associations: the Association of Research Libraries (ARL), the Greater Western Library Alliance (GWLA), and the New Mexico Consortium of Academic Libraries (NMCAL). These organizations represent a broad spectrum of academic libraries in terms of size, location, and type. The directors were requested to share the survey with their staff, thus ensuring a wide-reaching and representative sample for the study.

Data Collection

Data collection was facilitated through a custom-designed survey instrument, which was built and administered using the Qualtrics platform (Appendix B). The survey itself was developed to address the study’s research questions and was structured into four main sections, each focusing on a specific aspect of AI literacy among academic library employees.

The first section sought to capture respondents’ understanding and knowledge of AI, including their familiarity with AI concepts and terminology. The second section focused on respondents’ practical skills and experiences with AI tools and applications in professional settings. The third section aimed to identify areas of AI literacy where respondents felt less confident, signaling potential gaps in knowledge or skills that could be addressed through professional development initiatives. Finally, the last section explored respondents’ perspectives on the ethical implications and challenges presented by AI technologies in the library context.

The survey employed a mix of question types to engage respondents and capture nuanced data. These included Likert-scale questions, multiple choice, and open-ended questions. Prior to the full-scale administration, the survey was pilot-tested with a small group of academic library employees to ensure clarity, relevance, and appropriateness of the questions.

The survey questions were designed to tap into different dimensions of the TPACK framework. For instance, questions asking about practical experiences with AI tools and self-identified areas of improvement indirectly assess the intersection of technological and pedagogical knowledge (TPK), as they relate to AI.

Upon finalizing the survey, an invitation to participate, along with a link to the survey, was distributed via the listservs and direct outreach methods. The survey remained open for two weeks, with reminders sent out at regular intervals to maximize the response rate.


While the study offers insights into AI literacy among academic library employees, it is crucial to acknowledge its limitations. Firstly, given the survey’s self-report nature, the findings may be subject to social desirability bias, where respondents might have over- or under-estimated their knowledge or skills in AI.

Secondly, despite best efforts to reach a wide range of academic library employees, the sample may not be entirely representative of the population. The voluntary nature of participation, coupled with the distribution methods used, may have skewed the sample towards those with an existing interest or engagement in AI.

Moreover, while the use of professional listservs and direct outreach to library directors helped widen our reach, this strategy might have excluded those academic library employees who are less active, or not included, in these communication channels. The inclusion of Canadian libraries through the Association of Research Libraries suggests a small number of non-U.S. respondents.

Finally, the rapidly evolving nature of AI and its applications in libraries means that our findings provide a snapshot at a specific point in time. As AI continues to advance and integrate more deeply into academic libraries, the landscape of AI literacy among library employees is likely to shift, necessitating ongoing research in this area.

These limitations, while important to note, do not invalidate our findings. Instead, they offer points of consideration for interpreting the results and highlight areas for future research to build on our understanding of AI literacy among academic library employees.

Results and Analysis

Descriptive statistics.

The survey drew a diverse response: 760 participants started the survey, 605 completed it. The participants represented a cross-section of the academic library landscape, with the majority (45.20%) serving in Research Universities. A significant proportion also hailed from institutions offering both graduate and undergraduate programs (29.64%) and undergraduate-focused Colleges or Universities (10.76%). Community Colleges and specialized professional schools (e.g., Law, Medical) were represented as well, albeit to a lesser extent.

Over half of the respondents (61.25%) were from libraries affiliated with the Association of Research Libraries (ARL), signifying an extensive representation from research-intensive institutions. Respondents were predominantly from larger academic institutions. Those serving in institutions with enrollments of 30,000 or more made up the largest group (30.67%), closely followed by those in institutions with enrollments ranging from 10,000 to 29,999 (34.66%).

As for professional roles, the survey drew heavily from the library specialists or professionals (60.99%) who directly support the academic community’s research, learning, and teaching needs. Middle (20.00%) and senior (9.09%) management personnel were also well-represented, providing a leadership perspective to the survey insights.

Table 1

Role or Position in Organization

Role or Position in Organization

Percentage of Respondents

Number of Respondents

Senior management (e.g. Director, Dean, associate dean/director)



Middle management (e.g. department head, supervisor, coordinator)



Specialist or professional (e.g., librarian, analyst, consultant)



Support staff or administrative






Most of the respondents were primarily involved in Reference and Research Services (25.17%) or Library Instruction and Information Literacy (24.34%)—two areas integral to the academic support infrastructure.

In terms of professional experience, participants exhibited a broad range, from novices with less than a year’s experience (2.81%) to seasoned veterans with over 20 years in the field (22.68%).

Table 2

Primary Work Area in Academic Librarianship

Primary Work Area in Academic Librarianship

Percentage of Respondents

Number of Respondents

Administration or management



Reference and research services



Technical services (e.g., acquisitions, cataloging, metadata)



Collection development and management



Library instruction and information literacy



Electronic resources and digital services



Systems and IT services



Archives and special collections



Outreach, marketing, and communications






Table 3

Years of Experience as a Library Employee

Years of Experience as a Library Employee

Percentage of Respondents

Number of Respondents

Less than 1 year



1–5 years



6–10 years



11–15 years



16–20 years



More than 20 years



The survey group was highly educated, with most holding a master’s degree in library and information science (65.51%), and a significant number having completed a doctoral degree or a master’s in another field.

The survey also collected demographic information. A substantial majority identified as female (71.97%), and the largest age group was 35–44 years (27.97%). While the majority identified as White (76.11%), other ethnicities, including Asian, Black or African American, and Hispanic or Latino, were also represented.

This diverse participant profile offers a broad-based view of AI literacy in the academic library landscape, setting the stage for insightful findings and discussions.

Table 4

Level of Understanding of AI Concepts and Principles

Level of Understanding of AI Concepts and Principles

% of Respondents

Number of Respondents

1 (Very Low)






3 (Moderate)






5 (Very High)



RQ 1 AI Literacy Levels

At a broad level, participants expressed a modest understanding of AI concepts and principles, with a significant portion rating their knowledge at an average level. However, the number of respondents professing a high understanding of AI was quite small, revealing a potential area for further training and education.

A similar pattern was observed when participants were queried about their understanding of generative AI specifically. This suggests that while librarians have begun to grasp AI and its potential, there is a considerable scope for growth in terms of knowledge and implementation (Figure 1).

Figure 1

Understanding of Generative AI

Regarding the familiarity with AI tools, most participants had a moderate level of experience (30.94%). Only a handful of participants reported a high level of familiarity (3.87%), signaling an opportunity for more hands-on training with these tools.

In examining the prevalence of AI usage in the library sector, the researcher found a varied landscape. While some technologies have found significant adoption, others remain relatively unused. Notably, Chatbots and text or data mining tools were the most widely used AI technologies.

Participants’ understanding of specific AI concepts followed a similar trend. More straightforward concepts such as Machine Learning and Natural Language Processing had a higher average rating, whereas complex areas like Deep Learning and Generative Adversarial Networks were less understood. This trend underscores the need for targeted educational programs on AI in library settings.

Table 5

Understanding of Specific AI Concepts

AI Concept

Average Rating

Machine Learning


Natural Language Processing (NLP)


Neural Network


Deep Learning


Generative Adversarial Networks (GANs)


Notably, there was almost a nine percent drop in responses from the previous questions to the questions that asked about the more technical aspects of AI. This could signify a gap in knowledge or comfort level with these topics among the participants.

In the professional sphere, AI tools have yet to become a staple in library work. The majority of participants do not frequently use these tools, with 41.79% never using generative AI tools and 28.01% using them less than once a month. This might be attributed to a lack of familiarity, resources, or perceived need. However, for those who do use them, text generation and research assistance are the primary use cases.

Concerns about ethical issues, quality, and accuracy of generated content, as well as data privacy, were prevalent among the participants. This finding indicates that while there’s interest in AI technologies, the perceived challenges are significant barriers to full implementation and adoption.

In their personal lives, AI tools have yet to make a significant impact among the participants. The majority (63.98%) reported using these tools either ‘less than once a month’ or ‘never.’ This could potentially reflect the current state of AI integration in non-professional or leisurely activities, and may change as AI continues to permeate our everyday lives.

A chi-square test of independence was performed to examine the relation between the position of the respondent and the understanding of AI concepts and principles. The relation between these variables was significant, χ 2 (16, N = 760) = 26.31, p = .05. This means that the understanding of AI concepts and principles varies depending on the position of the respondent.

The distributions suggest that—while there is a significant association between the position of the respondent and their understanding of AI concepts and principles—the majority of respondents across all positions have a moderate understanding of AI. However, there are differences in the proportions of respondents who rate their understanding as high or very high, with Senior Management and Middle Management having higher proportions than the other groups.

There is also a significant relation between the area of academic librarianship and the understanding of AI concepts and principles, χ²(36, N = 760) = 68.64, p = .00084. This means that the understanding of AI concepts and principles varies depending on the area of academic librarianship. The distributions show that there are differences in the proportions of respondents who rate their understanding as high or very high, with Administration or management and Library Instruction and Information Literacy having higher proportions than the other groups.

Furthermore, a Chi-Square test shows that the relation between the payment for a premium version of at least one of the AI tools and the understanding of AI concepts and principles is significant, χ²(4, N = 539) = 85.42, p < .001. The distributions suggest that respondents who have paid for a premium version of at least one of the AI tools have a higher understanding of AI concepts and principles compared to those who have not. This could be because those who have paid for a premium version of an AI tool are more likely to use AI in their work or personal life, which could enhance their understanding of AI. Alternatively, those with a higher understanding of AI might be more likely to see the value in paying for a premium version of an AI tool.

It’s important to note that these findings are based on the respondents’ self-rated understanding of AI, which may not accurately reflect their actual understanding. Further research could involve assessing the respondents’ understanding of AI through objective measures. Additionally, other factors not considered in this analysis, such as the respondent’s educational background, years of experience, and exposure to AI in their work, could also influence their understanding of AI.

RQ2 Identifying Gaps

In this section, the researcher delved deeper into the gaps in knowledge and confidence among academic library professionals regarding AI applications. These gaps highlight the urgent need for targeted professional development and training in AI literacy.

Confidence Levels in Various Aspects of AI

The survey data pointed to moderate levels of confidence across a spectrum of AI-related tasks, indicating room for growth and learning. For evaluating ethical implications of using AI, a modest 30.12% of respondents felt somewhat confident (levels 4 and 5 combined), while 29.50% were not confident (levels 1 and 2 combined), and the largest group (39.38%) remained neutral.

Discussing AI integration revealed similar patterns. Here, 31.1% reported high confidence, 34.85% expressed low confidence, and the remaining 33.06% were neutral. These distributions suggest an overall hesitation or lack of assurance in discussing and ethically implementing AI, potentially indicative of inadequate training or exposure to these topics.

When it came to collaborating on AI-related projects, fewer respondents (31.39%) felt confident, while 40.16% reported low confidence, and 28.46% chose a neutral stance. This might point to the necessity of not only individual proficiency in AI but also the need for collaborative skills and shared understanding among teams working with AI.

Troubleshooting AI tools and applications emerged as the most significant gap, with 69.76% rating their confidence as low and only 10.9% expressing high confidence. This highlights an essential area for targeted training, as troubleshooting is a fundamental aspect of successful technology implementation.

Table 6

Confidence Levels in Various Aspects of AI


% at Confidence Level 1

% at Confidence Level 2

% at Confidence Level 3

% at Confidence Level 4

% at Confidence Level 5

Evaluating Ethical Implications of AI






Participating in AI Discussions






Collaborating on AI Projects






Troubleshooting AI Tools






Providing Guidance on AI Resources






Reflecting on Professional Development and Training in AI

Approximately one-third of survey participants have engaged in AI-focused professional development, showcasing several key themes:

  • Modes of Training: Librarians access training via various formats, including webinars, workshops, and self-guided learning. Online options are popular, providing accessibility for diverse professionals.
  • AI Tools and Applications: Training sessions mainly introduce tools like ChatGPT and others, with an emphasis on functionality and applications in academia.
  • Ethical Implications: Sessions often address ethical concerns such as bias and privacy, and the potential misuse of ‘black box’ AI models.
  • Integration into Librarian Workflows: Programs explore AI’s integration into library work, including instruction, cataloging, and citation analysis.
  • AI Literacy: There is a recurring focus on understanding and teaching AI concepts, tied to broader information literacy discussions.
  • AI in Instruction: Training includes using AI tools in library instruction and understanding its impacts on academic integrity.
  • Community of Practice: Responses highlight collaborative learning, suggesting a communal approach to understanding AI’s challenges and opportunities.
  • Self-guided Learning: Some librarians actively pursue independent learning opportunities, reflecting a proactive stance on AI professional development.

The findings emphasize the multifaceted nature of AI in libraries, underlining the need for ongoing, comprehensive professional development. This includes addressing both technical and ethical aspects, equipping librarians with practical AI skills, and fostering a supportive community of practice.

A Chi-square test examining the relationship between the respondents’ positions and their participation in any training focused on generative AI (χ²(4, N = 595) = 26.72, p < .001) indicates a significant association. Upon examining the data, the proportion of respondents who have participated in training or professional development programs focused on generative AI is highest among those in Senior Management (47.27%), followed by Specialist or Professional (37.40%), Middle Management (29.75%), and Other (16.67%). The proportion is lowest among Support Staff or Administrative (3.70%).

This suggests that individuals in higher positions, such as Senior Management and Specialist or Professional roles, are more likely to have participated in training or professional development programs focused on generative AI. This could be due to a variety of reasons, such as these roles potentially requiring a more in-depth understanding of AI and its applications, or these individuals having more access to resources and opportunities for such training. On the other hand, Support Staff or Administrative personnel are less likely to have participated in such programs, which could be due to less perceived need or fewer opportunities for training in these roles.

These findings highlight the importance of providing access to training and professional development opportunities focused on AI across all roles in an organization, not just those in higher positions or those directly involved in AI-related tasks. This could help ensure a more widespread understanding and utilization of AI across the organization.

Despite these efforts, many participants did not feel adequately prepared to utilize generative AI tools professionally. A notable 62.91% disagreed to some extent with the statement: “I feel adequately prepared to use generative AI tools in my professional work as a librarian,” underscoring the need for more effective training programs.

Interestingly, the areas identified for further training weren’t just about understanding the basics of AI. Participants showed a clear demand for advanced understanding of AI concepts and techniques (13.53%), familiarity with AI tools and applications in libraries (14.21%), and addressing privacy and data security concerns related to generative AI (14.36%). This suggests that librarians are looking to move beyond a basic understanding and are keen to engage more deeply with AI.

Preferred formats for professional development opportunities leaned towards remote and flexible learning opportunities, such as online courses or webinars (26.02%) and self-paced learning modules (22.44%). This preference reflects the current trend towards digital and remote learning, providing a clear direction for future training programs.

Notably, almost half of the participants (43.99%) rated the need for academic librarians to receive training on AI tools and applications within the next twelve months as ‘extremely important.’ This emphasis on urgency indicates a significant and immediate gap to be addressed.

In summary, a deeper analysis of the data reveals a landscape where academic librarians possess moderate to low confidence in understanding, discussing, and handling AI-related tasks, despite some exposure to professional development in AI. This finding indicates the need for more comprehensive, in-depth, and accessible AI training programs. By addressing these knowledge gaps, the library community can effectively embrace AI’s potential and navigate its challenges.

RQ 3 Perceptions

The comprehensive results of our survey, as illustrated in Table 7, offer a detailed portrait of librarians’ perceptions towards the integration of generative AI tools in library services and operations.

Table 7

Perceptions Towards the Integration of Generative AI Tools In Library Services







To what extent do you agree or disagree with the following statement: “I believe generative AI tools have the potential to benefit library services and operations.” (1 = strongly disagree, 5 = strongly agree)






How important do you think it is for your library to invest in the exploration and implementation of generative AI tools? (1 = not at all important, 5 = extremely important)






In your opinion, how prepared is your library to adopt generative AI tools and applications in the next 12 months? (1 = not at all prepared, 5 = extremely prepared)






To what extent do you think generative AI tools and applications will have a significant impact on academic libraries within the next 12 months? (1 = no impact, 5 = major impact)






How urgent do you feel it is for your library to address the potential ethical and privacy concerns related to the use of generative AI tools and applications? (1 = not at all urgent, 5 = extremely urgent)






When considering the potential benefits of AI, the responses indicate a degree of ambivalence, with 35.88% choosing a neutral stance. However, when we combine the categories of those who ‘agree’ and ‘strongly agree,’ we see that a significant portion, 49.84%, view AI as beneficial to a certain extent. Similarly, on the question of the importance of investment in AI, there is a notable inclination towards agreement, with 46.87% agreeing that investment is important to some degree.

However, this optimism is juxtaposed with concerns about readiness. When asked how prepared they feel to adopt generative AI tools within the forthcoming year, 70.03% of respondents (those who ‘strongly disagree’ or ‘disagree’) admit a lack of preparedness. This suggests that despite recognizing the potential value of AI, there are considerable obstacles to be overcome before implementation becomes feasible.

The uncertainty surrounding AI’s impact on libraries in the short-term further illuminates this complexity. A significant proportion of librarians (36.09%) chose a neutral response when asked to predict the impact of AI on academic libraries within the next twelve months. Nonetheless, there is a considerable group (41.06% who ‘agree’ or ‘strongly agree’) who foresee significant short-term impact.

A key finding from the survey was the collective recognition of the urgency to address ethical and privacy issues tied to AI usage. In fact, 74.34% of respondents, spanning ‘agree’ and ‘strongly agree,’ underscored the urgent need to address potential ethical and privacy concerns related to AI, highlighting the weight of responsibility librarians feel in maintaining the integrity of their services in the age of AI (Figure 2).

Figure 2

Perceived Urgency for Addressing Ethical and Privacy Concerns of Generative AI in Libraries

The qualitative responses provide a rich understanding of the perceptions of generative AI among library professionals and the implications they foresee for the library profession. The responses were categorized into several key themes, each of which is discussed below with relevant quotes from the respondents.

Ethical and Privacy Concerns

A significant theme that emerged from the responses was the ethical and privacy concerns associated with the use of generative AI tools in libraries. Respondents expressed apprehension about potential misuse of data and violations of privacy. As one respondent noted, “Library leaders should not rush to implement AI tools without listening to their in-house experts and operational managers.” Another respondent cautioned, “We need to be cautious about adopting technologies or practices within our own workflows that pose significant ethical questions, privacy concerns.”

Need for Education and Training

The need for education and training on AI for librarians was another prevalent theme. Respondents emphasized the importance of understanding AI tools and their implications before implementing them. One respondent suggested: “quickly education on AI is needed for librarians. As with anything else, there will be early adopters and then a range of adoption over time.” Another respondent highlighted the need for an AI specialist, stating, “I also think it would be valuable to have an AI librarian, someone who can be a resource for the rest of the staff.”

Potential for Misuse

Respondents expressed concern about the potential for misuse of AI tools, such as generating false citations or over-reliance on AI systems. They emphasized the importance of critical thinking skills, and cautioned against replacing human judgment and learning processes with AI. As one respondent put it, “Critical thinking skills and learning processes are vital and should not be replaced by AI.” Another respondent warned: “there are potential risks from misuse such as false citations being provided or too much dependence on systems.”

Concerns about Implementation

Several respondents expressed doubts about the ability of libraries to quickly and effectively implement AI tools. They cited issues such as frequent updates and refinements to AI tools, the need for significant investment, and the potential for AI to be used in ways that do not benefit the library or its users. One respondent noted, “the concern I have with AI tools is the frequent updates and refinements that occur. For libraries with small staff size, it seems daunting to keep up.”

Role of AI in Libraries

Some respondents suggested specific ways in which AI could be used in libraries, such as for collection development, instruction, and answering frequently asked questions. However, they also cautioned against viewing AI as a panacea for all library challenges. One respondent stated: “using them for FAQs will be more useful than answering a complicated reference question.”

Concerns about AI’s Impact on the Profession

Some respondents expressed concern that the use of AI could lead to job displacement or a devaluation of the human elements of librarianship. They suggested that AI should be used to complement, not replace, human librarians. One respondent expressed that, “I could see a future where only top research institutions have human reference librarians as a concierge service.”

Need for Critical Evaluation

Respondents emphasized the need for critical evaluation of AI tools, including understanding their limitations and potential biases. They suggested that libraries should not rush to implement AI without fully understanding its implications. One respondent advised: “the framing of AI usage as a forgone conclusion is concerning. It’s a tool, not a solution, and should not be implemented without due consideration.”

AI Literacy

Some respondents suggested that libraries have a role to play in teaching AI literacy to students and other library users. They emphasized the importance of understanding how AI tools work and how to use them responsibly. One respondent stated: “I think we need to teach AI literacy to students.” Another respondent echoed this sentiment, saying, “it is essential that we prepare our students to use generative AI tools responsibly.”

The perceptions of generative AI among library professionals are multifaceted, encompassing both the potential benefits and challenges of these technologies. While there is recognition of the potential of AI to enhance library services, there is also a strong emphasis on the need for ethical considerations, education and training, critical evaluation, and responsible use of these tools. The implications for the library profession are significant, with concerns about job displacement, the need for new skills and roles, and the potential for changes in library practices and services. These findings highlight the need for ongoing dialogue and research on the use of generative AI in libraries.

While library employees acknowledge the potential advantages of AI in library services, they also express concerns regarding readiness, and emphasize the urgency to address ethical and privacy considerations. These findings indicate the need for support systems, training, and resources to address readiness gaps, alongside rigorous discussion, and guidelines to navigate ethical and privacy issues as libraries explore the possibilities of AI integration.


The survey results cast light on the current state of artificial intelligence literacy, training needs, and perceptions within the academic library community. The findings reveal a landscape of recognition for the potential of AI technologies, yet, simultaneously, a lack of in-depth understanding and preparedness for their adoption.

A detailed examination of the data reveals that a considerable number of library professionals self-assess their understanding of AI as sitting around, or below, the middle. While this does suggest a basic level of familiarity with AI concepts and principles, it likely falls short of the proficiency required to navigate the rapidly evolving AI landscape confidently and competently. This gap in understanding holds implications for the library field as AI continues to infiltrate various sectors and increasingly permeates library services and operations.

Moreover, an analysis of the familiarity of library professionals with AI tools lends further credence to this call for more comprehensive AI education initiatives. An understanding of AI extends beyond mere theoretical comprehension—it necessitates hands-on familiarity with AI tools and the ability to use and apply them in practice. Direct interaction with AI technologies provides an avenue for library professionals to bolster their practical understanding and thus equip them to incorporate these tools into their work more effectively.

However, formulating training initiatives that address these gaps is a multifaceted task. The AI usage in libraries is as diverse as the scope of AI applications themselves. From customer service chatbots, and text or data mining tools, to advanced technologies like neural networks and deep learning systems—each offers unique applications and therefore requires distinct expertise and understanding. Accordingly, training programs must be flexible and comprehensive, encompassing the full range of potential AI applications while also delving deep enough to provide a solid grasp of each specific tool’s functionality and potential uses.

The study also sheds light on the varying degrees of understanding across different AI concepts. Participants generally exhibited a higher level of comprehension for simpler AI concepts. However, their understanding waned when it came to more complex concepts, often the bedrock of cutting-edge AI applications. This variation in comprehension underscores the need for a stratified approach to AI education. Such an approach could start with foundational concepts and gradually progress towards more advanced topics, providing a scaffold on which a deeper understanding of AI can be built.

Addressing the AI literacy gap in the library sector thus requires a concerted approach—one that offers comprehensive and layered educational strategies that bolster both theoretical understanding and practical familiarity with AI. The aim should not only be to impart knowledge, but to empower library professionals to confidently navigate the AI landscape, to adopt and adapt AI technologies in their work effectively and—crucially —responsibly. Through such training and professional development initiatives, libraries can harness the potential of AI, ensuring they continue to be at the forefront of technological advancements.

As the focus shifts to the professional use of AI tools in libraries, the data reveal that their adoption is not yet commonplace. The use of AI tools—such as text generation and research assistance—are most reported, reflecting the immediate utility these technologies offer to librarians. However, a significant proportion of participants do not frequently use AI tools, indicating barriers to adoption. These barriers could include a lack of understanding or familiarity with these tools, a perceived lack of necessity for their use, or limitations in resources necessary for implementation and maintenance. To overcome these barriers, the field may need more than just providing education and resources. Demonstrating the tangible benefits and efficiencies AI tools can bring to library work could play a pivotal role in their wider adoption.

The data show a strong enthusiasm among librarians for professional development related to AI. While introductory training modalities are popular, the findings reveal a demand for more advanced, hands-on training. This need aligns with the complexity and rapid evolution of AI technologies, which require a deeper understanding to be fully leveraged in library contexts.

Furthermore, the findings highlight the importance of ethical considerations and the potential benefits of fostering communities of practice in AI training. With the increasing integration of AI technology into library services, the issues related to AI ethics will likely become more complex. Proactively addressing these concerns through in-depth, focused training can help libraries continue to serve as ethical stewards of information. Communities of practice provide a platform for shared learning, mutual support, and the pooling of resources, equipping librarians to better navigate the intricacies of AI integration.

Importantly, the data show that the diversity in librarians’ roles and contexts necessitates a tailored approach to AI training. Libraries differ in their services, target audiences, resources, and strategic goals, and so do their AI training needs. A one-size-fits-all approach to AI training may fall short. Future AI training could therefore take these variations into account, offering specialized tracks or modules catering to specific roles or institutional contexts.

Likewise, the perceptions surrounding the use of generative AI tools in libraries are intricate and multifaceted. While the potential benefits of AI are acknowledged and the importance of investing in its implementation recognized, there is also a pronounced lack of readiness to adopt these tools. This readiness gap could stem from various factors, such as a lack of technical skills, insufficient funding, or institutional resistance. Future research should delve into these possibilities to better understand and address this gap.

Library professionals express uncertainty about the short-term implications of AI for libraries. This could reflect the novelty of these technologies and a lack of clear use cases, or it could echo the experiences of early adopters. The findings also emphasize a heightened sense of urgency in addressing the ethical and privacy concerns associated with AI technologies. These concerns underline the necessity for ongoing dialogue, education, and policy development around AI use in libraries.

Conclusions and Future Directions

The results reveal an intricate landscape of AI understanding, usage, and perception in the library field. While the benefits of AI tools are acknowledged, a comprehensive understanding and readiness to implement these technologies remain less than ideal. This reality underlines the pressing need for an investment in targeted educational strategies and ongoing professional development initiatives.

Crucially, the wide variance in AI literacy, understanding of AI concepts, and hands-on familiarity with AI tools among library professionals points towards the need for a stratified and tailored approach to AI education. Future training programs must aim beyond just knowledge acquisition—they must equip library professionals with the capabilities to apply AI technologies in their roles effectively, ethically, and responsibly. Ethical and privacy concerns emerged as significant considerations in the adoption of AI technologies in libraries. Our findings reinforce the crucial role that libraries have historically played, and must continue to play, in advocating for ethical information practices.

The readiness gap in AI adoption uncovered by the study suggests a disconnect between understanding the potential of AI and the ability to harness it effectively. This invites a deeper investigation into potential barriers, including technical proficiency, resource allocation, and institutional culture, among others.

Framework and Key Competencies

This study presents a framework for defining AI literacy in academic libraries, encapsulating seven key competencies:

  • Understanding AI System Capabilities and Limitations: Recognizing what AI can and cannot do, knowing its strengths and weaknesses.
  • Identifying and Evaluating AI Use Cases: Discovering and assessing potential AI applications in library settings.
  • Utilizing AI Tools Effectively and Appropriately: Applying AI technologies in library operations.
  • Critically Assessing AI Quality, Biases, and Ethics: Evaluating AI for accuracy, fairness, and ethical considerations.
  • Engaging in Informed AI Discussions and Collaborations: Participating knowledgeably in conversations and cooperative efforts involving AI.
  • Recognizing Data Privacy and Security Issues: Understanding and addressing concerns related to data protection and security in AI systems.
  • Anticipating AI’s Impacts on Library Stakeholders: Preparing for how AI will affect library users and staff.

This multidimensional definition of AI literacy for libraries provides a foundation for developing comprehensive training programs and curricula. For instance, the need to understand AI system capabilities and limitations highlighted in the definition indicates that introductory AI education should provide a solid grounding in how common AI technologies like machine learning work, where they excel, and their constraints. This conceptual comprehension equips librarians to set realistic expectations when evaluating or implementing AI.

The definition also accentuates that gaining practical skills to use AI tools appropriately should be a core training component. Hands-on learning focused on identifying appropriate applications, utilizing AI technologies effectively, and critically evaluating outputs can empower librarians to harness AI purposefully.

Moreover, emphasizing critical perspectives and ethical considerations reflects that AI training for librarians should move beyond technical proficiency. Incorporating modules examining biases, privacy implications, misinformation risks, and societal impacts is key for fostering responsible AI integration.

Likewise, the collaborative dimension of the definition demonstrates that cultivating soft skills for productive AI discussions and teamwork should be part of the curriculum. AI literacy has an important social element that training programs need to nurture.

Overall, this definition provides a skills framework that can inform multipronged, context-sensitive AI training tailored to librarians’ diverse needs. It constitutes an actionable guide for developing AI curricula and professional development that advance both technical and social aspects of AI literacy.

Future Research

Based on the findings and limitations of the current study, the following are specific recommendations for future research:

  • Longitudinal Studies: This study provides a snapshot of AI literacy among academic library employees at a specific point in time. Future research could conduct longitudinal studies to track changes in AI literacy over time, which would provide insights into the effectiveness of interventions and the evolution of AI literacy in the library profession.
  • Comparative Studies: This study focused on academic library employees. Future research could conduct comparative studies to examine AI literacy among different types of library employees (e.g., public library employees, school library employees), or among library employees in different countries. Such studies could provide insights into the factors that influence AI literacy and the strategies that are effective in different contexts.
  • Intervention Studies: This study identified the need for education and training on AI. Future research could design and evaluate interventions aimed at enhancing AI literacy among library employees. Such studies could provide evidence-based recommendations for the development of training programs and resources.
  • Ethical Considerations: This study highlighted ethical concerns about the use of AI in libraries. Future research could delve deeper into these ethical issues, examining the perspectives of different stakeholders (e.g., library users, library administrators) and exploring strategies for addressing these concerns.
  • Impact of AI on Library Services: This study explored library employees’ perceptions of the potential impact of AI on library services. Future research could examine the actual impact of AI on library services, assessing the effectiveness of AI in enhancing user experience, streamlining operations, and supporting learning.

By pursuing these avenues for future research, we can continue to deepen our understanding of AI literacy in the library profession, inform strategies for enhancing AI literacy, and promote the effective and ethical use of AI in libraries.

Cetindamar, D., Kitto, K., Wu, M., Zhang, Y., Abedin, B., & Knight, S. (2021). Explicating AI literacy of employees at digital workplaces. IEEE Transactions on Engineering Management , 68(5), 1259–1271.

Cox, A. (2022). The ethics of AI for information professionals: Eight scenarios.  Journal of the Australian Library and Information Association , 71(3), 201–214.

Heck, T., Weisel, L., & Kullmann, S. (2019). Information literacy and its interplay with AI . In A. Botte, P. Libbrecht, & M. Rittberger (Eds.), Learning Information Literacy Across the Globe (pp. 129–131). https://doi.org/10.25656/01:17891

Hervieux, S., & Wheatley, A. (2021). Perceptions of artificial intelligence: A survey of academic librarians in Canada and the United States.  The Journal of Academic Librarianship , 47(1), 102270.

Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence , 3, 100101. https://doi.org/10.1016/j.caeai.2022.100101

Lo, L. S. (2023a). An initial interpretation of the U.S. Department of Education’s AI report: Implications and recommendations for Academic Libraries. The Journal of Academic Librarianship , 49(5), 102761. https://doi.org/10.1016/j.acalib.2023.102761

Lo, L. S. (2023b). The art and science of prompt engineering: A new literacy in the information age. Internet Reference Services Quarterly , 27(4), 203–210. https://doi.org/10.1080/10875301.2023.2227621

Lo, L. S. (2023c). The clear path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship , 49(4), 102720. https://doi.org/10.1016/j.acalib.2023.102720

Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and a new academic reality: artificial intelligence‐written research papers and the ethics of the large language models in scholarly publishing. Journal of the Association for Information Science and Technology , 74(5), 570–581. https://doi.org/10.1002/asi.24750

McKinsey & Company. (2023). The state of AI in 2023 : Generative AI’s breakout year . McKinsey & Company. https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year

Mishra, P., & Koehler, M.J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record , 108(6), 1017–1054.

Mishra, P. (2019). Considering contextual knowledge: The TPACK diagram gets an upgrade. Journal of Digital Learning in Teacher Education , 35(2), 76–78. https://doi.org/10.1080/21532974.2019.1588611

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence , 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041

Ocaña-Fernández, Y., Valenzuela-Fernández, L., & Garro-Aburto, L. (2019). Artificial intelligence and its implications in higher education. Propósitos y Representaciones , 7(2), 536–568. https://doi.org/10.20511/pyr2019.v7n2.274

Oliphant, T. (2015). Social media and web 2.0 in information literacy education in libraries: New directions for self-directed learning in the digital age. Journal of Information Literacy , 9(2), 37–49.

Pinski, M., & Benlian, A. (2023). AI literacy—Towards measuring human competency in artificial intelligence. Proceedings of the 56th Hawaii International Conference on System Sciences, 165–174. https://doi.org/10.24251/HICSS.2023.012

Ridley, M., & Pawlick-Potts, D. (2021). Algorithmic literacy and the role for libraries. Information Technology and Libraries , 40(2), 1–15. https://doi.org/10.6017/ital.v40i2.12963

Sobel, K., & Grotti, M.G. (2013). Using the TPACK framework to facilitate decision making on instructional technologies. Journal of Electronic Resources Librarianship , 25(4), 255–262. https://doi.org/10.1080/1941126X.2013.847671

UNESCO. (2021). AI and education: Guidance for policy-makers . United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000376709

U.S. Department of Education. (2023). (rep.). Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations . Retrieved from https://www2.ed.gov/documents/ai-report/ai-report.pdf .

Appendix A. Recruitment—Listservs

  • American Indian Library Association (AILA)
  • American Libraries Association (ALA) Members
  • Asian Pacific American Librarians Association (APALA)
  • □ Members
  • □ University Libraries Section
  • □ Distance and Online Learning Section
  • □ Instruction Section
  • Association of Research Libraries (ARL) Directors Listserv
  • Black Caucus American Library Association (BCALA)
  • Chinese American Librarians Association (CALA)
  • Greater Western Library Alliance (GWLA) Directors’ listserv
  • Minnesota Institute Graduates (MIECL)
  • New Mexico Consortium of Academic Libraries (NMCAL) Directors’ Listserv

Appendix B. AI and Academic Librarianship

Survey flow.

Standard: Block 1 (1 Question)

Block: Knowledge and Familiarity (12 Questions)

Standard: Perceived Competence and Gaps in AI Literacy (5 Questions)

Standard: Training on Generative AI for Librarians (6 Questions)

Standard: Desired Use of Generative AI in Libraries (7 Questions)

Standard: Demographic (10 Questions)

Standard: End of Survey (1 Question)

Start of Block: Block 1

Q1.1 Introduction

Dr. Leo Lo from the University of New Mexico is conducting a research project. You are invited to participate in a research study aiming to assess AI literacy among academic library employees, identify gaps in AI literacy that require further professional development and training, and understand the differences in AI literacy levels across different roles and demographic factors. Before you begin the survey, please read this Informed Consent Form carefully. Your participation in this study is voluntary, and you may choose to withdraw at any time without any consequences.

Artificial Intelligence (AI) refers to the development of computer systems and software that can perform tasks that would typically require human intelligence. These tasks may include problem-solving, learning, understanding natural language, recognizing patterns, perception, and decision-making

You are being asked to participate based of the following inclusion and exclusion criteria:

Inclusion Criteria:

  • Currently employed as an employee in a college or university library setting.
  • Willing and able to provide informed consent for participation in the study.

The Exclusion Criteria are as Follows:

  • Librarian employees working in non-academic library settings (e.g., public libraries, school libraries, special libraries).
  • Individuals who are not currently library employees or who are employed in non-library roles within academic institutions.

The purpose of this study is to evaluate the current AI literacy levels of academic librarians and identify areas where further training and development may be needed. The findings will help inform the design of targeted professional development programs and contribute to the understanding of AI literacy in the library profession.

If you agree to participate in this study, you will be asked to complete an online survey that will take approximately 15–20 minutes to complete. The survey includes questions about your AI knowledge, familiarity with AI tools and applications, perceived competence in using AI, and your opinions on training needs.

Potential Risks and Discomforts

There are no known risks or discomforts associated with participating in this study. Some questions might cause minor discomfort due to self-reflection, but you are free to skip any questions you prefer not to answer. Benefits While there are no direct benefits to you for participating in this study, your responses will help contribute to a better understanding of AI literacy among academic librarians and inform the development of relevant professional training programs.


Your responses will be anonymous, and no personally identifiable information will be collected. Data will be stored securely on password-protected devices or encrypted cloud storage services, with access limited to the research team. The results of this study will be reported in aggregate form, and no individual responses will be identifiable. Your information collected for this project will NOT be used or shared for future research, even if we remove the identifiable information like your name.

Voluntary Participation and Withdrawal

Your participation in this study is voluntary, and you may choose to withdraw at any time without any consequences. Please note that if you decide to withdraw from the study, the data that has already been collected from you will be kept and used. This is necessary to maintain the integrity of the study and ensure that the data collected is reliable and valid.

Contact Information

If you have any questions or concerns about this study, please contact the principal investigator, Leo Lo, at [email protected] . If you have questions regarding your rights as a research participant, or about what you should do in case of any harm to you, or if you want to obtain information or offer input, please contact the UNM Office of the IRB (OIRB) at (505) 277-2644 or irb.unm.edu

By clicking “I agree” below, you acknowledge that you have read and understood the information provided above, had an opportunity to ask questions, and voluntarily agree to participate.

I agree (1)

I do not agree (2)

Skip To: End of Survey If Q1.1 = I do not agree

End of Block: Block 1

Start of Block: Knowledge and Familiarity

Q2.1 Artificial Intelligence

(AI) refers to the development of computer systems and software that can perform tasks that would typically require human intelligence. These tasks may include problem-solving, learning, understanding natural language, recognizing patterns, perception, and decision-making

Please rate your overall understanding of AI concepts and principles (using a Likert scale, e.g., 1 = very low, 5 = very high)

Q2.2 On a scale of 1 to 5, how would you rate your understanding of generative AI ? (1 = not at all knowledgeable, 5 = extremely knowledgeable)

Q2.3 Rate your familiarity with generative AI tools (e.g., ChatGPT, DALL-E, etc.) (using a Likert scale, e.g., 1 = not familiar, 5 = very familiar)

Q2.4 Which of the following AI technologies or applications have you encountered or used in your role as an academic librarian? (Select all that apply)

  • □ Chatbots (1)
  • □ Text or data mining tools (2)
  • □ Recommender systems (3)
  • □ Image or object recognition (4)
  • □ Automated content summarization (5)
  • □ Sentiment analysis (6)
  • □ Speech recognition or synthesis (7)
  • □ Other(please specify) (8) __________________________________________________

Q2.5 For each of the following AI concepts, indicate your understanding of the concept by selecting the appropriate response.

I don’t know what it is (1)

I know what it is but can’t explain it (2)

I can explain it at a basic level (3)

I can explain it in detail (4)

Machine Learning (1)

Natural Language Processing (NLP) (2)

Neural Network (3)

Deep Learning (4)

Generative Adversarial Networks (GANs) (5)

Q2.6 Which of the following generative AI tools have you used at least a few times? (Select all that apply)

  • □ Text generation (e.g., ChatGPT) (1)
  • □ Image generation (e.g., DALL-E, Mid Journey) (2)
  • □ Music generation (e.g., OpenAI’s MuseNet) (3)
  • □ Video generation (e.g. Synthesia) (4)
  • □ Presentation generation (e.g. Tome) (5)
  • □ Voice generation (e.g. Murf) (6)
  • □ Data synthesis for research purposes (7)
  • □ Other (please specify) (8) __________________________________________________

Display This Question:

If If Which of the following generative AI tools have you used at least a few times? (Select all that a… q://QID5/SelectedChoicesCount Is Greater Than 0

Q2.7 Have you ever paid for a premium version of at least one of the AI tools (for example, ChatGPT Plus; or Mid Journey subscription plan, etc.)

Q2.8 How frequently do you use generative AI tools in your professional work? (Select one)

Several times per week (2)

A few times per month (4)

Monthly (5)

Less than once a month (6)

Q2.9 For what purposes do you use generative AI tools in your professional work? (Select all that apply)

  • □ Content creation (e.g., blog posts, social media updates) (1)
  • □ Research assistance (e.g., literature reviews, data synthesis) (2)
  • □ Data analysis or visualization (3)
  • □ Cataloging or metadata generation (4)
  • □ User support or assistance (e.g., chatbots, virtual reference) (5)
  • □ Other (please specify) (6) __________________________________________________

Q2.10 On a scale of 1 to 5, how would you rate how reliable  generative AI tools have been in fulfilling your professional needs? (1 = not at all reliable, 5 = extremely reliable) 

Please explain your choice. 

1 (1) __________________________________________________

2 (2) __________________________________________________

3 (3) __________________________________________________

4 (4) __________________________________________________

5 (5) __________________________________________________

Q2.11 What level of concern do you have for the following potential challenges in implementing generative AI technologies in academic libraries? (Rate each challenge on a scale of 1 to 5, where 1 = not at all concerned and 5 = extremely concerned)

1 (1)

2 (2)

3 (3)

4 (4)

5 (5)

Obtaining adequate funding and resources for AI implementation (1)

Ethical concerns, such as bias and fairness (2)

Intellectual property and copyright issues (3)

Staff resistance or lack of buy-in (4)

Quality and accuracy of generated content (5)

Ensuring accessibility and inclusivity of AI tools for all users (6)

Potential job displacement due to automation (7)

Data privacy and security (8)

Technical expertise and resource requirements (9)

Other (please specify) (10)

Q2.12 How frequently do you use generative AI tools in your personal life ? (Select one)

End of Block: Knowledge and Familiarity

Start of Block: Perceived Competence and Gaps in AI Literacy

Q3.1 On a scale of 1 to 5, how confident are you in your ability to evaluate the ethical implications of using AI in your library? (1 = not at all confident, 5 = extremely confident)

Q3.2 On a scale of 1 to 5, how confident are you in your ability to participate in discussions about AI integration within your library? (1 = not at all confident, 5 = extremely confident)

Q3.3 On a scale of 1 to 5, how confident are you in your ability to collaborate with colleagues on AI-related projects in your library? (1 = not at all confident, 5 = extremely confident)

Q3.4 On a scale of 1 to 5, how confident are you in your ability to troubleshoot issues related to AI tools and applications used in your library? (1 = not at all confident, 5 = extremely confident)

Q3.5 On a scale of 1 to 5, how confident are you in your ability to provide guidance to library users about AI resources and tools ? (1 = not at all confident, 5 = extremely confident)

End of Block: Perceived Competence and Gaps in AI Literacy

Start of Block: Training on Generative AI for Librarians

Q4.1 Have you ever participated in any training or professional development programs focused on generative AI?

If Q4.1 = Yes

Q4.2 Please briefly describe the nature and content of the training or professional development program(s) you attended.


Q4.3 To what extent do you agree or disagree with the following statement: “ I feel adequately prepared to use generative AI tools in my professional work as a librarian .” (1 = strongly disagree, 5 = strongly agree)

Q4.4 In which of the following areas do you feel the need for additional training or professional development related to AI? (Select all that apply)

  • □ Basic understanding of AI concepts and terminology (1)
  • □ Advanced understanding of AI concepts and techniques (2)
  • □ Familiarity with AI tools and applications in libraries (3)
  • □ Ethical considerations of AI in libraries (4)
  • □ Collaborating on AI-related projects (5)
  • □ Addressing privacy and data security concerns related to generative AI (6)
  • □ Troubleshooting AI tools and applications (7)
  • □ Providing guidance to library users about AI resources (8)
  • □ Other (please specify) (9) __________________________________________________

Q4.5 What types of professional development opportunities related to AI would be most beneficial to you? (Select all that apply)

  • □ Online courses or webinars (1)
  • □ In-person workshops or seminars (2)
  • □ Conference presentations or panel discussions (3)
  • □ Self-paced learning modules (4)
  • □ Mentoring or coaching (5)
  • □ Peer learning groups or communities of practice (6)
  • □ Other (please specify) (7) __________________________________________________

Q4.6 How important do you think it is for academic librarians to receive training on generative AI tools and applications in the next 12 months ? (1 = not at all important, 5 = extremely important)

End of Block: Training on Generative AI for Librarians

Start of Block: Desired Use of Generative AI in Libraries

Q5.1 To what extent do you agree or disagree with the following statement: “ I believe generative AI tools have the potential to benefit library services and operations .” (1 = strongly disagree, 5 = strongly agree)

Q5.2 How important do you think it is for your library to invest in the exploration and implementation of generative AI tools ? (1 = not at all important, 5 = extremely important)

Q5.3 If you have any additional thoughts or suggestions on how your library could or should use (or not use) generative AI tools, please share them here.

Q5.4 How soon do you think your library should prioritize implementing generative AI tools and applications? (Select one)

Immediately (1)

Within the next 6 months (2)

Within the next year (3)

Within the next 2–3 years (4)

More than 3 years from now (5)

Not a priority at all (6)

Q5.5 In your opinion, how prepared is your library to adopt generative AI tools and applications in the next 12 months? (1 = not at all prepared, 5 = extremely prepared)

Q5.6 To what extent do you think generative AI tools and applications will have a significant impact on academic libraries within the next 12 months ? (1 = no impact, 5 = major impact)

Q5.7 How urgent do you feel it is for your library to address the potential ethical and privacy concerns related to the use of generative AI tools and applications? (1 = not at all urgent, 5 = extremely urgent)

End of Block: Desired Use of Generative AI in Libraries

Start of Block: Demographic

Q6.1 In which type of academic institution is your library located? (Select one)

Community college (1)

College or university (primarily undergraduate) (2)

College or university (graduate and undergraduate) (3)

Research university (4)

Specialized or professional school (e.g., law, medical) (5)

Other (please specify) (6) __________________________________________________

Q6.2 Is your library an ARL member library?

Q6.3 Approximately how many students are enrolled at your institution? (Select one)

Fewer than 1,000 (1)

1,000–4,999 (2)

5,000–9,999 (3)

10,000–19,999 (4)

20,000–29,999 (5)

30,000 or more (6)

Q6.4 What is your current role or position in your organization? (Select one)

Senior management (e.g. Director, Dean, associate dean/director) (1)

Middle management (e.g. department head, supervisor, coordinator) (2)

Specialist or professional (e.g., librarian, analyst, consultant) (3)

Support staff or administrative (4)

Other (please specify) (5) __________________________________________________

Q6.5 In which area of academic librarianship do you primarily work? (Select one)

Administration or management (1)

Reference and research services (2)

Technical services (e.g., acquisitions, cataloging, metadata) (3)

Collection development and management (4)

Library instruction and information literacy (5)

Electronic resources and digital services (6)

Systems and IT services (7)

Archives and special collections (8)

Outreach, marketing, and communications (9)

Other (please specify) (10) __________________________________________________

Q6.6 How many years of experience do you have as a library employee?

Less than 1 year (1)

1–5 years (2)

6–10 years (3)

11–15 years (4)

16–20 years (5)

More than 20 years (6)

Q6.7 What is the highest level of education you have completed? (Select one)

High school diploma or equivalent (1)

Some college or associate degree (2)

Bachelor’s degree (3)

Master’s degree in library and information science (e.g., MLIS, MSLS) (4)

Master’s degree in another field (5)

Doctoral degree (e.g., PhD, EdD) (6)

Other (please specify) (7) __________________________________________________

Q6.8 What is your gender? (Select one)

Non-binary / third gender (3)

Prefer not to say (4)

Q6.9 What is your age range?

Under 25 (1)

65 and above (5)

Q6.10 How do you describe your ethnicity? (Select one or more)

  • □ American Indian or Alaskan Native (1)
  • □ Asian (2)
  • □ Black or African American (3)
  • □ Hawaiian or Other Pacific Islander (4)
  • □ Hispanic or Latino (5)
  • □ White (6)
  • □ Prefer not to say (7)
  • □ Other (8) __________________________________________________

End of Block: Demographic

Start of Block: End of Survey

Q7.1 Thank you for participating in our survey!

Your input is incredibly valuable to us and will contribute to our understanding of AI literacy among academic librarians. We appreciate the time and effort you have taken to share your experiences and opinions. The information gathered will help inform future professional development opportunities and address potential gaps in AI knowledge and skills.

We will carefully analyze the responses and share the findings with the academic library community. If you have any further comments or questions about the survey, please do not hesitate to contact us at [email protected].

Once again, thank you for your contribution to this important research. Your insights will help shape the future of AI in academic libraries.

Best regards,

University of New Mexico

End of Block: End of Survey

* Leo S. Lo is Dean, College of University Libraries and Learning Sciences at the University of New Mexico, email: [email protected] . ©2024 Leo S. Lo, Attribution-NonCommercial (https://creativecommons.org/licenses/by-nc/4.0/) CC BY-NC.

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Meet the psychological needs of your people—all your people

As record numbers of workers quit their jobs, companies are busy trying to figure out how to make working conditions at their organization more attractive and more sustainable. Many companies boast flexible hours, good benefits, and, of course, higher pay. And some go further, looking closely at how roles in the organization can fulfill people’s psychological needs.

Business leaders recognize these emotional needs—whether it is the sense of reward workers have when they accomplish something, the frustration they feel when being micromanaged, the anger they experience after being treated unfairly, the longing they feel to be part of a group, or the desire they have for their work to be interesting and meaningful.

Yet many leaders mistakenly believe that only other professionals who have enjoyed similar success—and the financial rewards that come with it—truly value the nonfinancial aspects of their work. As we show in this article, that is simply not true.

People in lower-paying jobs also want their psychological needs at work to be satisfied. Yet data show that those needs are typically going unmet, far more often than is the case for higher earners.

Some of this may be unavoidable: for example, there is only so much autonomy one can feasibly grant a production line worker, while the job of a truck driver may be inherently lacking in social contact. However, most jobs could be enhanced to provide a much greater degree of psychological satisfaction.

In this article, we share novel data and analysis that illustrate the premium placed by all workers on psychologically satisfying work and how current work practices appear to be exacerbating existing inequalities. We also look at what business leaders can do to address the psychological needs of their lower-earning employees.

The good news is that, for the most part, companies have direct control over actions that can improve matters. Moreover, many of the practices that are needed—while requiring some time and effort—do not typically call for direct cash outlays. In fact, better satisfying workers’ psychological needs tends to correlate with higher revenues and profits.

Most people, across all income levels, believe that having an interesting job is as important as having a solid income

For thousands of years, philosophers have argued about what constitutes a “good life”—a life with more progress, pleasure, or purpose. Now, modern sciences—neuroscience, endocrinology (hormones), psychology, anthropology, and evolutionary biology, among others—have caught up. All agree: there is much more to being a human than surviving and procreating. 1 Admittedly, the underlying motivators of human behavior—needs, desires, and preferences—may be evolutionary. In other words, they may be serving the goal of survival and procreation. Nevertheless, in modern societies, these needs, desires, and preferences include a large social and psychological component—for example, the need for belonging, friendship, and love. If these needs are not met, people’s reactions can be just as visceral as if their physical safety is threatened.

In a way, Maslow’s famous hierarchy of needs 2 Abraham Maslow, “A theory of human motivation,” Psychological Review , July 1943, Volume 50, Number 4. was both right and wrong at the same time. On the one hand, it recognized that people have many desires in addition to basic bodily needs such as water, food, and shelter. On the other hand, it assumed a fixed hierarchy where psychological needs—such as belonging and self-esteem—became relevant only after basic physical and safety needs were met. However, modern research has shown that these needs exist in parallel and that a person’s well-being can be enhanced—for example, by good social relationships— even if their basic physical and safety needs are not completely fulfilled. 3 Ed Diener and Louis Tay, “Needs and subjective well-being around the world,” Journal of Personality and Social Psychology , August 2011, Volume 101, Number 2.

It is no longer a surprise that people seek more from their employers than just a paycheck and a safe place to work. A preponderance of evidence suggests that “good work” also means satisfying employees’ psychological needs.

At all levels of income, the most important drivers of people’s job satisfaction were interpersonal relationships and having an interesting job.
  • McKinsey’s recent analysis of the reasons why employees are leaving their jobs in record numbers ( the Great Attrition , or what many call the Great Resignation) showed that the most important factors were social and psychological, including not feeling valued by their organization or manager or not having a sense of belonging at work.
  • A quantitative analysis of more than 16,000 workers globally in 2015 showed that at all levels of income, the most important factors determining people’s job satisfaction were interpersonal relationships and having an interesting job—each accounting for around 20 percent of the explainable variation. In contrast, the level of pay accounted for only 4 percent of the variation in people’s job satisfaction. 4 Jan-Emmanuel de Neve et al., “Work and well-being: A global perspective,” in Global Happiness Policy Report , edited by Global Council for Happiness and Wellbeing, New York, NY: Sustainable Development Solutions Network, 2018.
  • In a representative global survey of nearly 50,000 people across 38 countries, more than 60 percent of respondents agreed or strongly agreed with the statement “I would enjoy having a paid job even if I did not need the money.” 5 ISSP Research Group (2017), “International Social Survey Programme: Work Orientations IV - ISSP 2015,” GESIS Data Archive, Cologne, ZA6770 data file version 2.1.0, doi.org/10.4232/1.12848. Percentages calculated using relevant weighting factors and excluding answers “can’t choose” and “no answer.” Only around 40 percent agreed or strongly agreed with the statement “A job is just a way of earning money—no more.”
  • In the same survey, across all occupations and income levels, only 16 percent of respondents rated “high income” as more important than having “an interesting job.” As shown in Exhibit 1, the average importance placed on “an interesting job” was on par with or higher than “high income” in all occupational groupings, including the lowest-paid ones .

Yet companies do a better job of addressing the psychological needs of higher-earning employees than lower-earning colleagues

One of the most prominent models of human motivation, extensively applied to organizational and employment research, is the self-determination theory by psychologists Richard Ryan and Edward Deci. 6 Delia O’Hara, “The intrinsic motivation of Richard Ryan and Edward Deci,” American Psychological Association, December 18, 2017. According to this theory, as well as a large body of empirical evidence, all employees have three basic psychological needs—competence, autonomy, and relatedness—and satisfying these needs promotes high-quality performance and broader well-being. 7 Edward L. Deci et al., “Self-determination theory in work organizations: The state of a science,” Annual Review of Organizational Psychology and Organizational Behavior , 2017, Volume 4. Additional studies, including McKinsey’s own research, have also found a link between positive outcomes  (for both employer and employee) and employee engagement, 8 Jan-Emmanuel de Neve et al., “Employee well-being, productivity, and firm performance: Evidence and case studies,” in Global Happiness Policy Report , edited by Global Council for Happiness and Wellbeing, New York, NY: Sustainable Development Solutions Network, 2019. often embodied in questions about the degree to which employees consider their work to be interesting, and purposeful .

Drawing on this literature, as well as a large global data set generated by the International Social Survey Programme, 9 ISSP Research Group (2017), “International Social Survey Programme: Work Orientations IV - ISSP 2015.” we looked at how well employees’ psychological needs are satisfied in different types of occupations, ranging from managerial and professional jobs to lower-paid roles, such as those in customer service, cleaning, and waste disposal. Given the data available, we focused on five psychological needs: competence (related to the concept of mastery), autonomy (related to control and agency), relatedness (including positive relationships), meaning (proxied by how interesting individuals find their jobs), and purpose (proxied by how proud individuals are of their organizations).

The results are fascinating (Exhibit 2). First, the good news: on a net basis (deducting those who “disagree” or “strongly disagree” from those who “agree” or “strongly agree”) across all occupations, a greater proportion of workers feel that their psychological needs are satisfied. Even for those with the worst net score—plant and machine operators and assemblers who were asked about feelings of competence—around 48 percent said that they could use “almost all” or “a lot” of their past experience and skills, versus 23 percent who said that they could use “almost none” of their skills on the job. Similarly, while 23 percent of workers in elementary occupations (such as cleaners, couriers, and waiters) didn’t find their jobs to be interesting, more than half did.

In absolute terms, more global workers—whatever their role—feel more positive than negative about the degree to which their psychological needs are met.

The bad news, however, is that this is far less true for individuals employed in lower-paying, and often lower-skilled, jobs. The differences between, say, managers and people in elementary occupations are particularly large in terms of competence (the ability to use experience and skills) and meaning (how interesting the job is). In this sense, current work practices globally seem to be exacerbating inequalities rather than ameliorating them.

The data indicate that not all of this is inherent to, or directly determined by, the characteristics of each role. After all, some people in even the most manual, routine, repetitive, or poorly paid jobs still indicate that their work is meaningful, that they are proud of the organization they work for, and that their role enables them to express and satisfy their needs for competence, autonomy, and relatedness.

Indeed, the potential for any job to inspire is illustrated powerfully by the classic story of the three bricklayers working at St Paul’s Cathedral in London. Christopher Wren, one of the most highly acclaimed English architects in history, had been commissioned in the late 17th century to rebuild the cathedral. One day, he noticed three bricklayers on a scaffold, each of whom appeared to have very different levels of motivation and speed. He asked each of them the same question: “What are you doing?”

The first bricklayer, seemingly the least satisfied with his position, said, “I’m a bricklayer. I’m working hard laying bricks to feed my family.” The second bricklayer, slightly more engaged, replied, “I’m a builder. I’m building a wall.” The third bricklayer, who seemed to be working with the greatest amount of purpose, said, “I’m a cathedral builder. I’m building a great cathedral to The Almighty.” 10 Jim Baker, “The story of three bricklayers—a parable about the power of purpose,” Sacred Structures, April 9, 2019. In the modern workplace, great managers and leaders can elicit a sense of meaning  by emphasizing, and reflecting with employees on, the ultimate contribution that their organization is making to society.

McKinsey research suggests that society is a key source of meaning for employees, along with company, customer, team, and individual. Together, they make up a collective, integrated whole that leaders can address. If average job satisfaction is weaker for lower-earning roles despite the many lower-paid individuals who do have their psychological needs met, organizations must be overlooking opportunities to do better. Luckily, they have many ways to refocus and improve their efforts.

Addressing the psychological needs of lower earners makes good business sense—here’s what leaders can do

Any organization claiming to be a good employer would want to address the imbalances highlighted above, as much as is operationally feasible. As we have written previously , positive and negative experiences at work—beyond pay and rations—have significant spillover consequences for people’s personal lives. 11 Diego Cortez et al., “Revisiting the link between job satisfaction and life satisfaction: The role of basic psychological needs,” Frontiers in Psychology , May 9, 2017, Volume 8, Article 680. For example, one study showed that a mother’s dissatisfaction with her job can contribute to her children’s behavioral problems. 12 Julian Barling and Karyl E. MacEwen, “Effects of maternal employment experiences on children’s behavior via mood, cognitive difficulties, and parenting behavior,” Journal of Marriage and Family , August 1991, Volume 53, Number 3.

However, in addition to the moral case for equalizing the scales on psychological well-being, there is also a strong business case. A comprehensive evidence base shows that higher employee satisfaction is associated with higher profitability 13 James K. Harter et al., “Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes: A meta-analysis,” Journal of Applied Psychology , April 2002, Volume 87, Number 2. and that this phenomenon is not confined to a company’s higher-earning roles. Consider the case of frontline customer service staff: one experiment showed that weekly sales for call center operators increased by 13 percent when the operators’ happiness increased by one point on a scale of one to five. 14 Clement Bellet et al., “Does employee happiness have an impact on productivity?,” Saïd Business School working paper 2019-13, October 17, 2019. Worker satisfaction and customer satisfaction tend to go hand in hand. 15 “Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes,” April 2002.

Another direct link from employee satisfaction to the business bottom line is through employee turnover. In the wake of the COVID-19 pandemic, more people than ever are leaving their jobs voluntarily , both in the United States and in other developed economies .

And while the competition for talent is heated among professionals such as software engineers and medics, vacancy rates in many low-paying jobs are also sky-high. Across the United States, the United Kingdom, and the European Union, unfilled roles abound in the hospitality, entertainment, and logistics sectors, among others. 16 McKinsey analysis based on data from the US Bureau of Labor Statistics, Eurostat, and the UK Office for National Statistics, accessed on May 11, 2022. For businesses, losing personnel means costly and time-consuming recruitment and retraining , not to mention lost output and productivity.

Psychological well-being at work  is one of the most important factors in employees’ decisions to stay or to go . Regardless of income level, workers who “strongly agreed” that they were proud of the organization they worked for were significantly more likely also to say that they would turn down a job at another organization, even if it offered higher pay. Granted, people in higher-earning roles tended to be more loyal, but the difference in loyalty between staff who felt proud and staff who did not was dramatic across all income categories.

Whether motivated by equity considerations or bottom-line benefits, employers would do well to consider ways they can improve the working experience for lower earners.

To get started, leaders can think of this as a journey with six steps:

  • Appreciate that the majority of people, at all levels of the organization, are looking for more than just money from their job—that they would like to have their psychological needs satisfied.
  • Recognize that workers’ circumstances vary significantly in different jobs and teams and are often very different from those of leaders themselves.
  • Analyze how effectively psychological needs are being met in each type of job and each part of the organization, benchmarking performance to peers and best practice.
  • Identify how psychological needs can be better satisfied—typically through changes in company culture, behaviors, and day-to-day working practices.
  • Act by creating initiatives, projects, and processes to help make workers feel more masterful, in jobs that are, as much as possible, more skills-based, autonomous, connected, interesting, or purposeful.
  • Monitor and evaluate the results, both in terms of how satisfied employees are with their psychological needs and in terms of commercial outcomes and employee well-being.

The best suggestions for how to redesign jobs or processes, or how to make the workplace more psychologically satisfying, will almost certainly come from workers themselves. Indeed, the process of discussing issues and opportunities and listening to employees’ daily experiences is itself a core part of creating positive change. Many businesses already routinely talk to their workers about employee engagement and satisfaction.

The best suggestions for how exactly to redesign jobs or processes, or make the workplace more psychologically satisfying, will almost certainly come from staff themselves.

However, it is vitally important to base these discussions on more than workers’ fundamental needs, such as physical safety and pay. The style of conversation should focus on both what people think about work and how they feel about work. Such discussions are likely to unleash a range of responses—both positive and negative—which leaders will need to harness both respectfully and skillfully.

In addition to intensive employee engagement processes, there are a number of practical behaviors that leaders can encourage through mindsets, communication, role modeling, training, and performance-management processes. For lower-earning employees, the actions and behaviors of immediate line managers can make an enormous difference. Some of the practices that have positive returns in almost every situation include the following:

Recognize competence: Frequently review a day’s work (with no judgment or blame) and ask what you as the manager or leader can do to make the next day easier. Thank and praise people for a job (well) done. Make the most of individuals’ skills through delegation. Provide regular, strength-based feedback oriented toward problem-solving.

For example, the plant and machine operators in Exhibit 2 who said that they were able to utilize their skills may still have had production line tasks that were fairly prescribed. But their factory organized short two-way briefings at every shift change, allowing workers to help make decisions about how operations are carried out.

Grant autonomy: Focus on the end goal of what is to be achieved and why and let employees decide—or at least give them a voice in—how to get there. Give frontline workers discretion over appropriate decisions. Ask employees how they feel about work and really listen to their answers.

For example, retail assistants who are given the discretion to accept customer returns or hand out vouchers in specific situations are more likely not only to make customers happier and more confident but also to feel better themselves.

Build connections: Set up regular (for example, daily) meetings at the beginning of each day (or shift) and allow time for socializing. Create regular breaks or events that help build social connections. Act decisively to eradicate any bullying or harassment. Praise and promote compassionate leaders .

For example, one skin care company whose sales agents work exclusively from home managed to maintain high levels of staff satisfaction by orchestrating regular one-on-one catch-ups, as well as virtual group get-togethers, throughout the COVID-19 pandemic, which allowed people to feel more connected to their colleagues. 17 Tera Allas et al., “Lessons on resilience for small and midsize businesses,” Harvard Business Review , June 3, 2021.

Instill meaning: Always explain the “why” behind tasks and link the reason to goals that go beyond making money (for example, being proud of the organization’s product or service). Help make work more interesting by upskilling people to be able to perform more complex or varied tasks. Simply ask people what would make their jobs more interesting.

For example, the workers in elementary occupations in Exhibit 2 who said that they still found their jobs meaningful may well have benefited from the same attitude that met President John F. Kennedy when he visited NASA in 1962. When the president came across a janitor in the hallway and asked him what his role was, the janitor replied, “I’m helping put a man on the moon.”

Discuss purpose: Set aside time for teams to reflect on the impact the company has on the world. Use one-on-one conversations to better understand workers’ individual sense of purpose  and discuss how they can act on it in their work setting.

For example, for a worker at a clothing manufacturer, a manager can make the role more fulfilling by regularly sharing positive messages, photos, or videos from smiling customers wearing the company’s garments.

This advice may sound basic. We all know how to meet the psychological needs of the people in our lives—our children, our partners, our friends. We might even compliment, thank, and empathize with strangers.

We need to take these positive behaviors and apply them in the workplace as well—not only with peers but with employees at all levels of the organization. However routine their tasks, we can stop treating workers as cogs in a machine and start treating them as the wonderful human beings they are.

Tera Allas

The authors wish to thank Jacqueline Brassey and Marino MB for their contributions to this article.

This article was edited by Rick Tetzeli, an executive editor in the New York office.

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Luxury yacht finds purpose and passion in scientific research.

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Humpback Whales, Megaptera novaeangliae, provided the reason for a recent expedition to the Silver ... [+] Bank area of the Dominican Republic Marine Sanctuary. Made possible by a Yachts For Science match with Bering Yachts, with assistance from the government of the Dominican Republic, Blue Marine Foundation, Mission Blue, BOAT International, and additional nonprofits, the five day trip collected information valuable to the protection of humpback whale populations on board a private Bering yacht.

Imagine: One boat. Five days. Thirteen people. Thousands of humpback whales.

Nothing compares. Just ask Alexei Mikhailov, Founder and CEO of luxury superyacht builder Bering Yachts , who recently teamed up with Mission Blue through Yachts For Science , two nonprofits, for five days of research on humpback whales in the Silver Bank calving zone.

The Bering 92 Papillon as it prepared to carry the team to the research area of the Dominican ... [+] Republic's Silver Bank Marine Sanctuary to photo ID individual whales and collect eDNA as it was shed by passing cetaceans.

Anchoring eighty miles off the northeast shore of the Dominican Republic, the team quickly got to work as they were surrounded by humpback whales coming to Silver Bank to mate and birth calves. Learning, discovering, sharing academic as well as cultural knowledge, there was great communication among the scientists and crew.

Mikhailov described the profuse conversation and exchange of information while on board for the expedition, noting that the thirteen people represented nine different nationalities with a wealth of knowledge from previous work.

A Newfound Passion For A Sturdy Yacht

"I got first hand experience of how to be on board a yacht in collaboration with the expedition," Mikhailov said, emphasizing that "The amount of information, the density of information, the value of this information, was incredible." He added that not a moment was wasted. People eagerly shared their expertise with one another about various expeditions and research findings, along with details relating to culture and family. All that while surrounded by thousands of whales in this protected calving area was "Marvelous," Mikhailov exclaimed.

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The team of international researchers and crew aboard the Papillon for the five-day expedition to ... [+] the humpback whale breeding ground 80 miles from the northeast coast of the Dominican Republic.

Not your everyday superyacht experience, there is increasing interest in the use of superyachts as vehicles for research. Organizations like Yachts For Science specialize in matching marine research projects to superyachts, creating expeditions that explore everything from coral reefs and marine flora to whales and microalgae.

It takes a village. The long list of those who worked to make the expedition possible includes the ... [+] Government of the Dominican Republic, Mission Blue, Blue Marine Foundation, Blue Nature Alliance, Wyss Foundation, and Caribbean Cetacean Society. Bering Yachts connected through the Yachts for Science initiative, made possible by the Ocean Family Foundation, BOAT International, Nekton, EYOS, and others.

Trip From Freeport to Silver Bank A Rough One

According to Mikhailov, the first four days were a little rough as the boat left from Freeport in the Bahamas en route to the Dominican Republic, experiencing rough weather with 25 knot winds. Many on board agreed that most research boats might not be very comfortable under those conditions. Papillon , the Bering 92 the group was on, was built for just such conditions. With its steel hull and two stabilizers, Papillon made walking, cooking, sleeping, even reading, comfortable with no issues.

The Silver Bank area of the Dominican Republic Marine Sanctuary is visited by as many as 3,000 ... [+] whales each year. By contrast, the privilege of visiting the whales in the sanctuary is extended to just 500 people annually. Alexei Mikhailov, Founder and CEO of Bering Yachts is bullish on getting Bering yacht owners engaged to experience what it's like to be a part of unique scientific expeditions, offering the use of their superyachts as a research base.© MAXBELLO

DR 30-30 Pledge For Ocean Protection

The government of the Dominican Republic has committed to protect 30 percent of its ocean areas within the Exclusive Economic Zone by 2030. The protected area would include coral reefs, deep-sea corals, seamounts, whale aggregations, and a section of the deepest zone of the Atlantic Ocean, the Puerto Rico Trench. This expedition set out to photo ID individual whales and collect eDNA samples to determine which species have visited the area.

Humpback fluke as the whale completes a visit to the surface.

Mikhailov is ready to continue to partner with such expeditions in the future, hoping that his participation will encourage others, triggering a robust Caribbean effort. Bering has compiled footage for a video recording highlights of the expedition in anticipation of completing many more in additional locations from the Mediterranean to the Antarctic.

About The Boat

The Bering 92 Papillon measures 29.08 meters with a 6.74 meter beam and a 1.85 meter draft. She carries a 3.6 meter tender, ten guests, and four crew across three decks. Equipped with two Cummins QSM engines and 1220 hp, she has a range of 3500 nautical miles at cruise speed with a maximum speed of 13 knots. Five solar panels, a saloon, a formal dining and entertainment area, an aft al fresco cockpit, swim platform, wet bar with grill, jetski, and spacious crew area, Papillon is engineered and outfitted for a combination of safety and comfort.

Designed to weather the storm, Bering yachts are built to be safe and capable for both owners and passengers. Sturdy, modern designs minimize noise and vibration, reduce fuel consumption, and engage alternative energy solutions. Active participants in conservation efforts, not just for videos and marketing, but with genuine commitment, Bering is positioning itself as a steward of the environment it operates in to improve the future for a thriving marine ecosystem.

Kathleen Turner

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Public finance and budgets

Countries across the OECD are facing long-term fiscal pressures in areas such as health, ageing, climate change, and defence. At the same time, governments must grapple with mounting debt levels, rising interest rates and high levels of uncertainty. In this increasingly constrained fiscal environment, reconciling new and emerging spending pressures with already stretched public finances requires high-quality budget institutions and processes.

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Key messages, oecd countries are facing long-term fiscal pressures..

The long-term fiscal pressures associated with climate change and reducing greenhouse gas emissions; ageing populations and shrinking labour supply; and rising health care and social care costs continued to mount. Interest expenditures are now increasing significantly. The current geopolitical tensions are adding further new spending pressures, including in the defence area, as well as greater economic uncertainty.

Reconciling these pressures with already stretched public finances requires high quality budget institutions and strengthened public understanding

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Governments must have credible public financial management frameworks to build trust in budgetary governance and maintain enough fiscal space to be able to finance crisis responses when needed.

Governments must have credible public financial management frameworks to build trust in budgetary governance and maintain enough fiscal space to finance crisis responses when needed.

Each of the crises of recent years has shown the importance of preserving the resilience of public finances; countries need to be able to finance large and unexpected expenditures, such as in the aftermath of major natural disasters, to support a distressed sector or to address the consequences of a major pandemic. However, debt levels in OECD countries have risen significantly in recent years.  

General government expenditures amounted to 46.3% of GDP on average across OECD countries in 2021

Between 2019 and 2021 general government expenditures as a percentage of GDP increased by 5.4 percentage points, from 40.9% in 2019. This  increase is largely explained by the COVID-19 pandemic, which led to significant economic disruption. This prompted  large-scale fiscal stimuluses, including increased spending on healthcare, social welfare programmes, and support for businesses and individuals affected by the pandemic, while at the same time GDP was falling.  

General Fiscal Balance

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    Step 4: Organizing Research and the Writer's Ideas. When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper.

  12. PDF Writing a Research Report

    Use the section headings (outlined above) to assist with your rough plan. Write a thesis statement that clarifies the overall purpose of your report. Jot down anything you already know about the topic in the relevant sections. 3 Do the Research. Steps 1 and 2 will guide your research for this report.

  13. What Is Research Report? Definition, Contents, Significance, Qualities

    Research Report Definition. According to C. A. Brown, "A report is a communication from someone who has information to someone who wants to use that information.". According to Goode and Hatt, "The preparation of report is the final stage of research, and it's purpose is to convey to the interested persons the whole result of the study, in sufficient detail and so arranged as to enable ...

  14. PDF How to Write an Effective Research REport

    Abstract. This guide for writers of research reports consists of practical suggestions for writing a report that is clear, concise, readable, and understandable. It includes suggestions for terminology and notation and for writing each section of the report—introduction, method, results, and discussion. Much of the guide consists of ...

  15. What is Research?

    The purpose of research is to further understand the world and to learn how this knowledge can be applied to better everyday life. It is an integral part of problem solving. Although research can take many forms, there are three main purposes of research: Exploratory: Exploratory research is the first research to be conducted around a problem ...

  16. Research Report Meaning, Characteristics and Types

    A research report is a document that conveys the outcomes of a study or investigation. Its purpose is to communicate the research's findings, conclusions, and implications to a particular audience. This report aims to offer a comprehensive and unbiased overview of the research process, methodology, and results.

  17. Research Objectives

    A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement, before your research objectives. Research objectives are more specific than your research aim. They indicate the specific ways you'll address the overarching aim.

  18. Research: Meaning and Purpose

    1. As an investigative process, it originates with a question. It attempts to satisfy an unanswered question that is in the mind of a researcher. 2. Research demands a clear articulation of a goal, and a clear statement of the problem is a pre-condition of any research. 3.

  19. Chapter 6: Components of a Research Report

    The research report contains four main areas: Introduction- What is the issue? What is known? What is not known? What are you trying to find out? This sections ends with the purpose and specific aims of the study. Methods- The recipe for the study. If someone wanted to perform the same study, what information would they need? How will you ...

  20. Research Paper Purpose Statement Examples

    A purpose statement clearly defines the objective of your qualitative or quantitative research. Learn how to create one through unique and real-world examples.

  21. What Is a Research Report? How They're Produced and Impact

    Research Report: A research report is a document prepared by an analyst or strategist who is a part of the investment research team in a stock brokerage or investment bank . A research report may ...

  22. Writing up a Research Report

    A research report is one big argument how and why you came up with your conclusions. To make it a convincing argument, a typical guiding structure has developed. ... In the following chapter, we present the purpose of each report section and provide some guidance how to write them. 4.4.1 Management Summary. The management summary is the ...

  23. 1. The Purpose of Research: Why do we do it?

    Report of a collaborative workshop in the UK to discuss social research priorities on visual impairment', British Journal of Visual Impairment, 25(2): 178-189. Hannah, D.R. and Lautsch, B.A. (2010) 'Counting in Qualitative Research: Why to Conduct it, When to Avoid it, and When to Closet it', in Journal of Management Inquiry, 20(1): 14 ...

  24. Evaluating AI Literacy in Academic Libraries: A Survey Study with a

    College & Research Libraries (C&RL) is the official, bi-monthly, ... The U.S. Department of Education's recent report (2023) on AI emphasizes the growing importance of AI literacy for educators and students, highlighting the necessity of understanding and integrating AI technologies in educational settings. ... The purpose of this study is to ...

  25. Meeting the psychological needs of all employees

    Yet companies do a better job of addressing the psychological needs of higher-earning employees than lower-earning colleagues. One of the most prominent models of human motivation, extensively applied to organizational and employment research, is the self-determination theory by psychologists Richard Ryan and Edward Deci. 6 Delia O'Hara, "The intrinsic motivation of Richard Ryan and Edward ...

  26. Luxury Yacht Finds Purpose And Passion In Scientific Research

    Many on board agreed that most research boats might not be very comfortable under those conditions. Papillon, the Bering 92 the group was on, was built for just such conditions. With its steel ...

  27. Business

    Local, state, and federal government websites often end in .gov. Commonwealth of Pennsylvania government websites and email systems use "pennsylvania.gov" or "pa.gov" at the end of the address.

  28. How AWS helps reduce carbon footprint of AI workloads

    A new report by 451 Research, part of S&P Global Market Intelligence, finds that computing in the cloud is five times more energy efficient than on-premises data centers in the Asia Pacific region. ... These purpose-built accelerators enable AWS to efficiently execute AI models at scale, reducing the carbon footprint for similar workloads ...

  29. Public finance and budgets

    Public finance is the economic field focusing on the financial activities of government entities at various levels. Our work examines government expenditures, including public services, infrastructure, social welfare, defence, education, healthcare, and more. These are outlined in the national budget, reflecting financial commitments to meet obligations and provide essential services. Our ...