how to make action research paper

Linking Research to Action: A Simple Guide to Writing an Action Research Report

What Is Action Research, and Why Do We Do It?

Action research is any research into practice undertaken by those involved in that practice, with the primary goal of encouraging continued reflection and making improvement. It can be done in any professional field, including medicine, nursing, social work, psychology, and education. Action research is particularly popular in the field of education. When it comes to teaching, practitioners may be interested in trying out different teaching methods in the classroom, but are unsure of their effectiveness. Action research provides an opportunity to explore the effectiveness of a particular teaching practice, the development of a curriculum, or your students’ learning, hence making continual improvement possible. In other words, the use of an interactive action-and-research process enables practitioners to get an idea of what they and their learners really do inside of the classroom, not merely what they think they can do. By doing this, it is hoped that both the teaching and the learning occurring in the classroom can be better tailored to fit the learners’ needs.

You may be wondering how action research differs from traditional research. The term itself already suggests that it is concerned with both “action” and “research,” as well as the association between the two. Kurt Lewin (1890-1947), a famous psychologist who coined this term, believed that there was “no action without research; no research without action” (Marrow, 1969, p.163). It is certainly possible, and perhaps commonplace, for people to try to have one without the other, but the unique combination of the two is what distinguishes action research from most other forms of enquiry. Traditional research emphasizes the review of prior research, rigorous control of the research design, and generalizable and preferably statistically significant results, all of which help examine the theoretical significance of the issue. Action research, with its emphasis on the insider’s perspective and the practical significance of a current issue, may instead allow less representative sampling, looser procedures, and the presentation of raw data and statistically insignificant results.

What Should We Include in an Action Research Report?

The components put into an action research report largely coincide with the steps used in the action research process. This process usually starts with a question or an observation about a current problem. After identifying the problem area and narrowing it down to make it more manageable for research, the development process continues as you devise an action plan to investigate your question. This will involve gathering data and evidence to support your solution. Common data collection methods include observation of individual or group behavior, taking audio or video recordings, distributing questionnaires or surveys, conducting interviews, asking for peer observations and comments, taking field notes, writing journals, and studying the work samples of your own and your target participants. You may choose to use more than one of these data collection methods. After you have selected your method and are analyzing the data you have collected, you will also reflect upon your entire process of action research. You may have a better solution to your question now, due to the increase of your available evidence. You may also think about the steps you will try next, or decide that the practice needs to be observed again with modifications. If so, the whole action research process starts all over again.

In brief, action research is more like a cyclical process, with the reflection upon your action and research findings affecting changes in your practice, which may lead to extended questions and further action. This brings us back to the essential steps of action research: identifying the problem, devising an action plan, implementing the plan, and finally, observing and reflecting upon the process. Your action research report should comprise all of these essential steps. Feldman and Weiss (n.d.) summarized them as five structural elements, which do not have to be written in a particular order. Your report should:

• Describe the context where the action research takes place. This could be, for example, the school in which you teach. Both features of the school and the population associated with it (e.g., students and parents) would be illustrated as well.
• Contain a statement of your research focus. This would explain where your research questions come from, the problem you intend to investigate, and the goals you want to achieve. You may also mention prior research studies you have read that are related to your action research study.
• Detail the method(s) used. This part includes the procedures you used to collect data, types of data in your report, and justification of your used strategies.
• Highlight the research findings. This is the part in which you observe and reflect upon your practice. By analyzing the evidence you have gathered, you will come to understand whether the initial problem has been solved or not, and what research you have yet to accomplish.
• Suggest implications. You may discuss how the findings of your research will affect your future practice, or explain any new research plans you have that have been inspired by this report’s action research.

The overall structure of your paper will actually look more or less the same as what we commonly see in traditional research papers.

What Else Do We Need to Pay Attention to?

We discussed the major differences between action research and traditional research in the beginning of this article. Due to the difference in the focus of an action research report, the language style used may not be the same as what we normally see or use in a standard research report. Although both kinds of research, both action and traditional, can be published in academic journals, action research may also be published and delivered in brief reports or on websites for a broader, non-academic audience. Instead of using the formal style of scientific research, you may find it more suitable to write in the first person and use a narrative style while documenting your details of the research process.

However, this does not forbid using an academic writing style, which undeniably enhances the credibility of a report. According to Johnson (2002), even though personal thoughts and observations are valued and recorded along the way, an action research report should not be written in a highly subjective manner. A personal, reflective writing style does not necessarily mean that descriptions are unfair or dishonest, but statements with value judgments, highly charged language, and emotional buzzwords are best avoided.

Furthermore, documenting every detail used in the process of research does not necessitate writing a lengthy report. The purpose of giving sufficient details is to let other practitioners trace your train of thought, learn from your examples, and possibly be able to duplicate your steps of research. This is why writing a clear report that does not bore or confuse your readers is essential.

Lastly, You May Ask, Why Do We Bother to Even Write an Action Research Report?

It sounds paradoxical that while practitioners tend to have a great deal of knowledge at their disposal, often they do not communicate their insights to others. Take education as an example: It is both regrettable and regressive if every teacher, no matter how professional he or she might be, only teaches in the way they were taught and fails to understand what their peer teachers know about their practice. Writing an action research report provides you with the chance to reflect upon your own practice, make substantiated claims linking research to action, and document action and ideas as they take place. The results can then be kept, both for the sake of your own future reference, and to also make the most of your insights through the act of sharing with your professional peers.

Feldman, A., & Weiss, T. (n.d.). Suggestions for writing the action research report . Retrieved from http://people.umass.edu/~afeldman/ARreadingmaterials/WritingARReport.html

Johnson, A. P. (2002). A short guide to action research . Boston, MA: Allyn & Bacon.

Marrow, A. J. (1969). The practical theorist: The life and work of Kurt Lewin . New York, NY: Basic Books.

Tiffany Ip is a lecturer at Hong Kong Baptist University. She gained a PhD in neurolinguistics after completing her Bachelor’s degree in psychology and linguistics. She strives to utilize her knowledge to translate brain research findings into practical classroom instruction.

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Action research

A type of applied research designed to find the most effective way to bring about a desired social change or to solve a practical problem, usually in collaboration with those being researched.

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How do you define action research.

Professor David Coghlan explains action research as an approach that crosses many academic disciplines yet has a shared focus on taking action to address a problem. He describes the difference between this approach and empirical scientific approaches, particularly highlighting the challenge of getting action research to be taken seriously by academic journals

Dr. Nataliya Ivankova defines action research as using systematic research principles to address an issue in everyday life. She delineates the six steps of action research, and illustrates the concept using an anti-diabetes project in an urban area.

This is just one segment in a whole series about action research. You can find the rest of the series in our SAGE database, Research Methods:

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Action Research Design

• First Online: 10 November 2021

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• Michael Blankenagel 3  

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This chapter addresses the peculiarities, characteristics, and major fallacies of action research design. This research design is a change-oriented approach. Its central assumption is that complex social processes can best be studied by introducing change into these processes and observing their effects. The fundamental basis for action research is taking actions to address organizational problems and their associated unsatisfactory conditions. Also, researchers find relevant information on how to write an action research paper and learn about typical methodologies used for this research design. The chapter closes with referring to overlapping and adjacent research designs.

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Action Research for my Dissertation – The Do’s and the Don’ts

Published by Alvin Nicolas at August 14th, 2021 , Revised On August 29, 2023

Introduction

Action research is performed to identify solutions for a  problem , or it can be a progressive problem-solving process with a focus on reflection.

Action research can also be a part of a community of practice designed to identify issues and develop proactive solutions. Action research aims to develop appropriate guidelines that can be considered to be best practices in any discipline.

The researcher pursues an active strategy of participating in the change situation while conducting research. Action is important for the research enterprise, which differentiates action research from traditional research that takes a distant research setting approach.

Action researchers strive to study the current actions that play a critical role in any setting. This article will help introduce action research for a dissertation – the do’s and don’ts to research students so they can kickstart their action research promptly.

Struggling to get going with your dissertation? Here is an article on “ How to write a dissertation – Step by step guide .”

Definition of Action Research

Action research is a disciplined process of inquiry conducted by and for those taking action. The primary reason for engaging in action research is to assist the “actor” in improving and/or refining their actions.

Students who are required to perform action research find the process of action research extremely powerful. One of the foremost benefits of action research is that it is always relevant to the participants.

The principal consumers of any action research project’s findings are the researchers themselves, so relevance is guaranteed every time.

The Process of Action Research

Action research in education can be performed by the entire school faculty, a group of participants who share common interests, or an individual. Regardless of who participates in educational action research, the process of action research includes the following seven stages;

• Selecting a focus
• Clarifying theories
• Recognising research questions
• Data collection
• Data analysis
• Presenting Results
• Taking informed action

Advantages and Disadvantages

It is important to understand how to perform action research in education settings to establish its advantages and disadvantages. One of the key advantages of action research is that it helps researchers increase their knowledge through experience.

The action research cycle can be a learning cycle focusing on systematic reflection to have an effective ability to learn.  Action research is participative in nature and helps to understand researchers and the participants of any study.

Students can find it worthwhile to mention a  dissertation in their resume that directly relates to this practice.  There are some disadvantages to this type of research, such as the fact that a conventional format cannot  write the dissertation .

Students will have to learn to employ the action research methodology to complete their dissertation papers. Another disadvantage is that the library work for action research is demanding as the data and its interpretation define the literature.

Why not take advantage of the ResearchProspect.com dissertation writing service? Your dissertation is the most important part of your degree, and for that reason, you cannot risk failing it.

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The Do’s and Don’ts

Make yourself familiar with the complexities and requirements of action research before conducting the study. This will help you in  preparing the introduction to the dissertation .

The first step is to  write a winning proposal  to establish your  research problem  and decide on the research’s  approach and direction .

Action research problems play a critical role in driving the research to a level equal to or greater than existing literature. A good action research dissertation is data-driven rather than being theory-driven.

Selecting the action  research questions is critical from the perspective of the researcher. These questions are important in research as they identify the implications of such questions in the real world.

Action research questions could emerge by researching a setting where students have relationships when they ask what research questions should be explored to address and identify the social, political, and ethical dilemmas.

Similarly, students can conduct action research in external settings by identifying problems and developing relationships to undertake a comprehensive study. It is important to have an idea of  primary research and secondary research  when writing an action-based dissertation.

The research methodology for action research is not specific as the methods are context-bound. Moreover, the methods can be changed according to the nature of the present problems in the context. There are no unique methodological characteristics of action research.

The  types of research strategies  selected will depend on the  dissertation topic and the students’ action research. The best approach is to identify these approaches at an earlier stage so they can be used to address the questions.

Moreover, students need to identify the data that needs to be explored to develop the questions. Typically, an action research dissertation involves analysing data in which patterns, insights, and new understandings are identified.

The meaning of these patterns and insights is clearly explained to ensure that high levels of reliability and validity can be maintained.

A key approach in action research dissertations should be to identify limitations and use them as an advantage. This provides the ability to produce knowledge based on ground realities while also being useful for local participants.

This article aims to help students learn about action Research for the dissertation – the dos and the don’ts. It will help them to use a systematic approach towards writing action research dissertations.

Action research is an important approach towards resolving research problems and initiating a continuous reflection and learning process for students.

One of the strengths of action research is that it enables the researcher to directly participate in the research process. Moreover, researchers can obtain knowledge that is based on ground realities.

The process of writing an action research dissertation is different as compared to conventional research. Students are recommended to read as much as possible about action research before undertaking it since it can be a difficult process.

Also Read: What Are the Different Research Methods for Dissertation?

“Improve language, structure, style, and overall quality of your work. Get help from our experienced dissertation editors to improve the quality of your paper to First Class Standard. Click here to learn more about our Dissertation, Editing and Improvement Service .”

Action Research checklist

Frequently asked questions, what is meant by action research.

Action research is a problem-solving approach where researchers, often practitioners, study real-world issues in their context. They collaboratively identify problems, implement solutions, and reflect on outcomes to enhance practices and generate insights for continuous improvement.

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Textual analysis is the method of analysing and understanding the text. We need to look carefully at the text to identify the writer’s context and message.

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Best Practices and Lessons Learned for Action Research in eHealth Design and Implementation: Literature Review

Kira oberschmidt.

1 eHealth Cluster, Roessingh Research and Development, Enschede, Netherlands

2 Biomedical Signals and Systems Group, University of Twente, Enschede, Netherlands

Christiane Grünloh

Femke nijboer, lex van velsen, associated data.

Full overview of all categories and description of settings for each category.

Full list of categories per setting variable.

Action research (AR) is an established research framework to introduce change in a community following a cyclical approach and involving stakeholders as coresearchers in the process. In recent years, it has also been used for eHealth development. However, little is known about the best practices and lessons learned from using AR for eHealth development.

This literature review aims to provide more knowledge on the best practices and lessons learned from eHealth AR studies. Additionally, an overview of the context in which AR eHealth studies take place is given.

A semisystematic review of 44 papers reporting on 40 different AR projects was conducted to identify the best practices and lessons learned in the research studies while accounting for the particular contextual setting and used AR approach.

Recommendations include paying attention to the training of stakeholders’ academic skills, as well as the various roles and tasks of action researchers. The studies also highlight the need for constant reflection and accessible dissemination suiting the target group.

Conclusions

This literature review identified room for improvements regarding communicating and specifying the particular AR definition and applied approach.

Introduction

The way health care is organized and executed is of great societal concern, as it affects our quality of life. Hence, health care systems and eHealth technologies used to support health care should be designed in a way that meets the needs and expectations of their stakeholders. One way of doing this is through action research (AR). According to Bradbury and Lifvergren [ 1 ], AR in health care “seeks to (1) improve patient experiences and the health of populations, (2) reduce the per capita cost, (3) improve the work life of those who deliver care, and (4) bring health care providers into circumstances that allow for continuous learning together with patients.” AR has been used as a research framework in nursing and health care, for example, to improve the quality of patient care and investigate changes in action [ 2 ]. AR is a collaborative approach, where people affected by the change envisioned in AR become active members of the research team. AR is often used in the design of eHealth systems. However, existing literature reviews of AR in eHealth predominantly focus on the development of new frameworks [ 3 - 5 ] but not on how eHealth AR is currently carried out. Therefore, this literature review outlines the state of the art of AR in eHealth design.

eHealth projects cover a wide variety of topics and technologies and can therefore greatly benefit patients, professionals, and many other health care stakeholders. However, to gain the most from eHealth systems and technologies, it is crucial that they match with what is needed in practice [ 6 ]. To ensure such a match, Van Gemert-Pijnen and colleagues [ 6 ] suggest, among other things, working together with relevant stakeholders in all stages of the project, implementing the study results in practice, and continuously evaluating the process. Similarly, co-design has been mentioned as a useful technique for creating eHealth systems that suit the needs of the end users [ 3 ]. These ideas fit well with the principles of AR, which will be outlined below.

Definitions of AR have changed over the years. AR originated with Kurt Lewin [ 7 ], who described it as several consecutive circles of planning, action, and reflection. These cycles are shown in Figure 1 , developed by Williamson and colleagues [ 2 ]. In later definitions, the cyclical nature of AR remains one of its key features. Reason and Bradbury [ 8 ], who build on Lewin’s work, define AR as research that (1) involves stakeholders not only as participants but also as members of the research team, (2) consists of (at least) 1 cycle of planning, action, and reflection, (3) establishes direct changes, and (4) then evaluates those changes in and with the community. Their work [ 8 ] includes many interesting examples of AR from various fields. Furthermore, Bradbury and colleagues defined 7 “choice points for quality in action research” [ 9 ], criteria that can be used to plan, conduct, report, and assess AR projects .

Action research cycles (adapted from Kurt Lewin [ 7 ] by Williamson and colleagues [ 2 ]).

Within AR, different variations exist, such as action design research (ADR) or participatory action research (PAR). Usually, there is agreement on the main principles of AR explained earlier, but some authors or groups emphasize some aspects over others. For example, as the name suggests, ADR incorporates elements of design research into AR [ 10 ], whereas PAR highlights the involvement of the community [ 11 ]. For a more detailed overview of the similarities and differences between some of these approaches, see Williamson et al [ 2 ] or Coghlan and Brannick [ 11 ].

In general, AR and AR approaches such as ADR are similar to participatory design (PD) approaches that are used in human computer interaction (HCI) research. However, AR emphasizes reflection on and learning from the process that was carried out, whereas the main aim of PD is to create a solution [ 12 ]. AR, as opposed to PD, does not start with a clear goal of what needs to be developed but defines this throughout the process together with stakeholders. Additionally, AR is more immersive and calls for stakeholder involvement for a longer period of time due to its iterative cycles [ 13 ]. Nevertheless, in some cases, studies that are described as PD-related ones also meet Reason and Bradbury’s criteria [ 8 ] for AR [ 14 ]. Hayes [ 12 ] argues that AR and HCI research can supplement each other, as both often provide solutions on a local scale. As Hughes [ 15 ] describes, there is no standard way of implementing AR in health care due to the broadness of the field. Instead, there is a variety regarding the why, how, and with whom AR in health care is carried out [ 15 , 16 ]. For example, levels of stakeholder engagement and the context in which AR takes place can vary [ 16 ]. Other differences among AR studies include the topic, country, project duration, main target group, and methods used. Therefore, these aspects are considered in this review. The purpose of this review is to give an overview of the current literature on eHealth AR and summarize the best practices and points of improvement for future eHealth AR projects. Special attention is paid to the contextual variables of the research (eg, setting, duration, number of stakeholders), as this is expected to influence the outcomes, best practices, and points of improvement of a study. To provide an overview of AR in eHealth, this literature review addresses the following subquestions:

• What is the context of AR eHealth projects?
• How do eHealth AR studies define and operationalize AR?
• What are the best practices for conducting AR in concrete eHealth studies?
• What are the lessons learned from conducting AR in concrete eHealth studies?

Study Selection and Screening

The search was carried out in June 2020. PubMed, Scopus, and Google Scholar were searched using combinations of the search terms “action research” or “participatory design” and “eHealth,” “health technology,” “digital health,” or “telemedicine.” PubMed was chosen for its extensive medical database, and Scopus and Google Scholar were chosen as large scientific databases. Searching for “action research” turns up articles that include similar and related keywords like “participatory action research,” “action design research,” or “action-based research.” “Participatory design” was included as a search term because PD has significant overlap with AR, and both are sometimes used to supplement each other. The list of synonyms for “eHealth,” although not exhaustive, is expected to cover the various facets of the field. The initial search yielded 739 results. Articles were included if they (1) used and explicitly mentioned AR and (2) were about eHealth or health technology. Papers were excluded if they (1) were not written in English, (2) only included a study protocol but did not report results, or (3) only included a review of other articles. Full-text screening of the same 15 articles was performed by 2 authors (KO and CG); the authors discussed whether to include the studies until an agreement was reached. Next, the first author screened the full texts of the remaining articles, with some exceptions where a second opinion was necessary. These were again discussed between the first and second authors until an agreement was reached. Ultimately, 44 articles were included, reporting on 40 different projects. Figure 2 shows the flowchart of the inclusion process.

Inclusion flowchart of the literature search and screening process.

Data Extraction

For each study, the definition of AR that was provided by the authors, and the related AR approaches that they cited (if any) were extracted. Additionally, information about contextual variables of the study was derived. Specifically, we identified the topic, country, organizational context, project duration, types of stakeholders involved, the main target group of the research, and methods used. The types of involved stakeholders were grouped according to the framework described by Schiller et al [ 17 ], in which they define the main stakeholder categories as the public, policy makers, and governments, the research community, practitioners and professionals, health and social service providers, civil society organizations, and private businesses. Finally, the best practices and lessons learned were derived. The best practices and lessons learned were activities that could move forward and benefit the AR project, without necessarily being recognized as standard components of AR. The difference between what was seen as a best practice and as a lesson learned was based on the timing and reporting of these actions. An activity was labeled as a best practice if researchers already planned their project with this in mind (eg, mentioning it in the description of the methods). On the other hand, lessons learned were those points that researchers came to know during their project, which were reported mainly in the discussion section. From the first 5 articles, the best practices and lessons learned were extracted by 2 authors (KO and CG), and they compared their results. The remaining data were extracted by 1 author (KO) in consultation with the second author where a second opinion was necessary. Furthermore, 5 authors published not 1 but 2 papers about their project. For these papers, the same study context was described whereas the definition of and approach to AR and the best practices and lessons learned were reported separately, as these sometimes differed between the articles. A reflection on 2 projects was included in 1 article. In this case, each project context was reported separately whereas only 1 AR definition and approach as well as one set of best practices and lessons learned were outlined.

A general overview of all the included studies describing the AR approach, AR definition, and contextual variables was obtained. The contextual variables (topic, location, target group, stakeholders, duration, and methods used) were categorized. Furthermore, the studies were mapped in a matrix based on the study duration and the types and number of different stakeholders that participated in the study. The contextual data were coded and categorized inductively. To identify which AR approach was the most used, the citation frequency of each approach in the included studies was recorded. Furthermore, the cited AR approaches that were available were accessed and checked for cross-referencing. All cited AR definitions were mapped to show the relationship between them. The AR definitions used, best practices, and lessons learned were coded by 1 author (KO). The best practices and lessons learned were coded individually first and then combined for both categories.

The setting of the included studies was described based on 6 categories (topic, location, duration, involved stakeholders, target group, and methods). Multimedia Appendix 1 presents all the categories and the description of the setting for each study. The most common aspects of each category will be discussed below.

We identified 9 broader categories of the research topics in the 44 included studies (see Table 2.1 in Multimedia Appendix 2 for the full list). The most common were home care and telemonitoring, and health promotion and education (both n=8), followed by electronic medical records and health information systems (n=7), and mental health services (n=5).

The studies were set in 21 different countries, Australia being the most common (n=5) followed by the United States (n=4) and Canada, Sweden, and the United Kingdom (all n=3). Some studies from nonwestern countries, like Tanzania or Colombia were included, but no country was represented more than once or twice. Within the different countries, studies took place in various contexts, the most prevalent of which were rural areas (n=6) and hospitals (n=5). All contexts and countries can be found in Tables 2.2 and 2.3 of Multimedia Appendix 2 .

Target Groups

Among the 44 studies, 2 studies explicitly focused on 2 different target groups at the same time, whereas all other studies had 1 main target group. In most cases, the target groups were patients (n=11). Of these, the most common group was patients with cancer (n=3). There were 6 studies each focusing on clinicians as well as children and young adults, and 5 studies targeted older adults (see Table 2.4 in Multimedia Appendix 2 for the full list of target groups).

Stakeholders

In many cases, several stakeholders were included in the study, up to 6 different types of stakeholders included in some cases. In summary, 20 different types of stakeholders were involved (see Table 2.5 in Multimedia Appendix 2 for the full list). Health care workers (n=18) and patients and their representatives (n=12) were involved the most, followed by governmental bodies (n=9) and general nonmedical staff members (n=8). When clustering these stakeholder types according to the framework defined by Schiller and colleagues [ 17 ], the largest group consisted of practitioners and professionals (n=48), followed by members of the public (n=38). Policy makers and government bodies (n=13), the research community (n=10), private businesses (n=6), and civil society organizations (n=3) were represented less often. The only group that was not represented at all included health and social service providers.

Not all of the 44 studies reported the duration of the project (n=7). Studies that did report the duration (n=33) lasted from a few months (n=5) to more than 10 years (n=2). The majority (n=13) of these studies reported a project duration between 2 and 3 years, and the average project duration was 2.7 years. Figure 3 shows the distribution of the 10 most frequently involved types of stakeholders for the different project durations in the 33 projects that reported the project duration. Stakeholder types are shown in the order of how many times they were involved in total; however, because some studies did not report project durations, the numbers in this graph differ from those described above. The 2 biggest stakeholder groups, health care workers and patients, were rarely, or in the case of patients even not at all, involved in long-term studies.

Heat map showing the most commonly involved types of stakeholders against the project duration.

In Figure 4 , the study duration is mapped against the number of different stakeholders that were involved in each of the 33 projects that reported a project duration. Studies that did not report the overall project duration are not included in the figure. Most of the included studies lasted for up to 2 years, including 2 or 3 stakeholder groups. There are some longer studies including more stakeholder groups.

Heat map showing the number of stakeholders involved against the project duration.

Research Methods Used

As mentioned earlier, AR is a framework that does not advise the use of a single methodology, and studies can therefore include a variety of different research methods. Most of the 44 included studies indeed used several methods, with some studies employing up to 6 different methods . Interviews were used most frequently (n=24), followed by focus groups (n=22), workshops (n=14), and surveys (n=13). On average, studies used nearly 3 different methods (average 2.8). All methods can be found in Table 2.6 of Multimedia Appendix 2 .

AR Definitions

The articles contained 44 definitions of AR. They could be grouped according to 4 different aspects that they emphasized. First, 21 studies emphasized that in AR projects, practitioners and other stakeholders become (co)researchers (n=21). Second, AR is a cyclical process that includes different stages (n=19). Third, 14 studies described how AR focuses on solving a practical issue and aims to extend research knowledge. The fourth aspect was that AR takes place in a community setting (n=10). Further, 2 studies included 3 of these aspects in their definitions, and only 2 other studies mentioned all 4 aspects. Most studies included either 1 (n=16) or 2 (n=17) of the aspects, whereas 7 studies included none of these points in their definition or did not at define AR in detail. Table 1 provides an overview of the number of mentions per aspect and the studies mentioning these aspects.

Number of mentions and studies mentioning the aspects of the AR definition.

AR Approaches

Table 2 gives an overview of the AR approaches that were cited at least twice in the included articles. The AR approach was not cited in 4 studies. In some cases, different papers from the same authors were cited; however, as these eventually described the same approach, the citation count was added up. The most commonly cited approach was that proposed by Reason and Bradbury [ 8 ]. As described earlier, the key elements of this approach are that AR (1) involves stakeholders as coresearchers, (2) consists of plan, act, and reflect cycles, (3) makes a change in practice, and (4) evaluates the said changes in and with the community. Overall, most definitions share these main aspects but differ in terms of the aspects that are particularly emphasized. For example, Baskerville and colleagues [ 55 ] highlight the duality of practical work and scientific knowledge, whereas Baum and colleagues [ 56 ] underline the need for reflective practice that includes all stakeholders. Figures 5 and ​ and6 6 depict the cited approaches in more detail. There are 3 independent researchers or groups that are mentioned as being the origin of AR, namely Lewin [ 7 ], Trist and colleagues [ 57 ], and Freire [ 58 ]. Wherever the origin of AR was mentioned, some cases have named 2 of these, as observed in Figure 5 . The cited AR approaches also frequently refer to each other and sometimes authors collaborate with each other, for example on books about AR (see Figure 6 ). There are no very distinct groups conducting their own AR, but the different AR groups are often connected and build upon each other’s work.

Overview of the most cited action research approaches in the included articles per author or research group, including the number of citations.

Overview of the action research approaches referred to in the included articles, indicating those papers that are mentioned as “the origin” of action research. Studies that either name an approach as being the origin of action research, or are being named as such, are highlighted in blue for better readability.

Overview of action research approaches referred to in the included articles. Arrows indicate citations between the action research approach papers. The number of times that the articles included in this review cited each approach is indicated in the box. We have used different arrow thicknesses for better readability. Blue boxes indicate those papers that were available and checked for citations.

Best Practices and Lessons Learned

As previously described, an activity was identified as a “best practice” if researchers already planned their project with this in mind (eg, mentioning it in the description of methods). Lessons learned were those points that researchers came to know during their project. These were mostly reported in the discussion section. In total, 85 best practices and 66 lessons learned were identified, which were clustered into 22 categories of best practices and 16 categories of lessons learned. Among the 44 papers, 3 papers did not indicate any best practices that they followed, whereas 12 papers did not include any identifiable lessons learned. There were 8 overlapping categories, identified as best practices in some articles and as lessons learned in others. These will be discussed in more detail below.

Best Practices

The identified best practices in the 44 studies were most often related to the use of a specific method (n=9), namely personas (n=2), world café, journey mapping, role play, scenarios, case studies, design cards, and mixing different types of data collection methods (all n=1). Other best practices were a continuous evaluation of the project and a reflection on the process by the research team (n=8). The importance of establishing active contact between researchers and stakeholders and raising the confidence and skills of stakeholders was emphasized by 7 studies. The improvement of stakeholder skills mainly referred to research and analytical skills, allowing stakeholders to set up their own studies or continue the work after the project was finished. There were several specific suggestions to improve the regular project team meetings, for example, to always use the same agenda or to share a common area (office space) to make contact easier. Some other best practices concern the reporting and presentation of outcomes (n=6). The complete list of best practice categories can be found in Table 3 .

Overview of all best practice categories and number of mentions per category (N=44).

Lessons Learned

Apart from the best practices, the lessons learned from each study were identified. The most common lessons learned were increasing stakeholder knowledge and skills (n=8) and continuous evaluation of the project and reflection on the process (n=6). Both of these had been identified as best practices in other articles (more on this overlap below). Recommendations for the use of specific methods were also common (n=5). Lessons learned regarding reporting, adapting the project to fit the needs of stakeholders, fostering a welcoming environment, and the questionable replicability of the research were each mentioned 4 times. All lessons learned are shown in Table 4 .

Overview of all lessons learned categories and number of mentions per category (N=44).

Overlapping Best Practices and Lessons Learned

As stated earlier, some aspects were identified as best practices in some articles and as lessons learned in others. In total, we identified 7 such overlapping aspects. Overall, the most mentioned aspect was the importance of raising stakeholder skills and confidence (n=15, where best practices= 7 and lessons learned=8). Many articles reported the need for stakeholders to learn new skills, for example related to academic research, or the need to be convinced about their ability to perform these tasks. Almost all the studies that reported this as a best practice or lesson learned involved health care professionals as stakeholders. Other commonly mentioned points were recommendations for specific methods, even though the suggested methods differed (n=14, where best practices=9 and lessons learned=5) and there was continuous reframing and evaluation of the project (n=14, where best practices=8 and lessons learned=6). Continuous reframing often referred to the iterations of planning, action, and evaluation in AR projects. Studies that described this mostly did not include this cyclical nature of AR in their definition of it. In total, there were 10 recommendations regarding the reporting and presentation of results (best practices=6 and lessons learned=4), for example calling for open and accessible publishing of outcomes. The best practices and lessons learned included recommendations about meeting regularly (n=9, where best practices=7 and lessons learned=2), adapting to the needs of stakeholders (n=8, where best practices=3 and lessons learned=5), and investing in the relationship between partners (n=6, where best practices=3 and lessons learned=3).

Chronology of Overlapping Best Practices and Lessons Learned

When observing the publication timeline, most of the overlapping aspects appeared as a lesson learned in earlier publications, and then as a best practice in papers published at a later point in time. This was the case regarding stakeholder skills, appearing as a lesson learned in 1999 [ 33 ] and as a best practice in 2016 [ 25 ]; continuous reframing of the project was a lesson learned in 2003 [ 19 ] and best practice in 2009 [ 42 ]; further, having regular meetings was a lesson learned in 2006 [ 72 ] and a best practice in 2018 [ 27 ], and adapting the research to stakeholder needs was a lesson learned in 2007 [ 32 ] and a best practice in 2016 [ 77 ]. Such a clear timeline could not be seen for accessible reporting, appearing as a lesson learned in 2017 [ 78 ] and a best practice in 2007 [ 45 ], and the relationship between partners appearing as a lesson learned in 2017 [ 36 ] and as a best practice in 2008 [ 38 ].

Principal Results

To identify recommendations on how to conduct AR in eHealth studies, this literature review analyzed the setting, AR description, and best practices and lessons learned in 44 studies. The most important recommendations from this review, which will be discussed in more detail below, are as follows: actively raising stakeholder skills and confidence; fulfilling multiple roles and tasks as a researcher; fostering constant reflection and evaluation; ensuring open and accessible dissemination; reporting in a more structured and comprehensive way.

These recommendations are not exclusively related to eHealth, despite them being derived from a review of eHealth AR studies. Hence, it is possible that the recommendations are also relevant for AR in various other fields. Therefore, where possible, examples from different disciplines are discussed below to explain or supplement a recommendation.

Stakeholder Skills and Confidence

Being involved in a project as coresearcher can potentially increase stakeholders’ confidence, besides teaching them new skills [ 79 ]. However, this does not happen automatically. Similar to our findings, the narrative review conducted by Harrison and colleagues [ 80 ] also identified educating the research team as the most important task when stakeholders are involved in health care research. Nevertheless, there is limited research on how skill training for stakeholders could look like, and this can vary greatly between studies. Stakeholders in some eHealth studies might need to learn content-related information [ 81 ], whereas other studies require methodological or statistical skills [ 54 ]. Researchers should provide adequate training and material for their project and encourage stakeholders to make use of it. The studies included in this review that recommended stakeholder skill training almost exclusively worked with health care professionals. The relationship between recommending skill training and working mainly with health care professionals remains unclear. A possible explanation could be that other stakeholder groups in other studies already had the necessary skills and thus did not require any additional training. Another possibility is that other stakeholders were not given the same roles that health care professionals held, and therefore, they did not need skill training. Finally, as we will discuss later, reporting of AR activities was not always very extensive. Thus, stakeholders outside the health care sector were possibly trained, and these studies did not report on this aspect. Generally, not all participants prefer the same level of engagement in a project, and researchers should respect these preferences [ 82 ].

Tasks and Roles of the Researcher

Different aspects of the role and tasks of the researcher in an AR project are discussed. Brydon-Miller and Aragón describe the many different tasks that action researchers need to fulfil as their “500 hats” [ 83 ]. These are not specific to eHealth studies, but they can occur in any AR study. As researchers and stakeholders have many varied duties, their roles are not fixed and might change over the course of the project [ 19 ]. One main task of the researchers that continues throughout the project is the need to foster a welcoming environment for all stakeholders [ 42 ]. Researchers should also be present and actively involve themselves at a higher level than that needed in non-AR projects [ 38 ]. Additional AR-specific tasks for the researchers include investing in partner relationships [ 35 ] or breaking down power structures [ 28 ]. Generally, AR studies demand more self-reflection and awareness from the researchers than other projects and researchers should keep this in mind when entering an AR project.

Constant Reflection

The importance of continuous reframing and evaluation of the project was emphasized in several studies. Although evaluation is 1 of the AR cycles, studies providing recommendations on this topic rarely included this in their definition of AR. Owing to the lack of reports on AR cycles, which will be discussed below, it is unclear if these studies still followed the AR cycles without reporting on them. However, sometimes, it seems that periodic planned evaluation is not enough. Instead, the participants need to regularly reflect on the current status of the project and their role in it. Therefore, new AR projects should create suitable spaces for evaluation and reflection in ways that fit the projects and stakeholders. This is especially important because reflection can become difficult once a person is in the middle of the project [ 49 ]. Holeman and Kane [ 53 ] emphasize that reflection should not only take place within the project, but it should also be explicitly reported to help other researchers. If action researchers take reflection seriously and include honest evaluations in their publishing, the AR community members can learn from each other. Additionally, researchers and other stakeholders within the project learn and benefit from constant reflection [ 9 ].

Accessible Dissemination

Another important aspect concerns paying attention to open and understandable dissemination of results within the community and among researchers. Action researchers need to communicate findings to the academic world while also finding ways to inform the target group about the project in ways that suit the target users’ needs. An example of open and accessible dissemination can be found in Canto-Farachala and Larrea [ 83 ]. They present the results of their AR project regarding territorial development on an interactive website, allowing others to learn from their work. However, it seems that accessible reporting is still not the norm in AR, as Avison and colleagues [ 62 ] describe that many AR studies are generally “published in books rather than as articles. Action researchers have large and complicated stories to tell.” Future AR projects should attempt to narrate their stories in such a way that others can learn from them.

Comprehensive Reporting

The different way of describing AR studies also leads to another issue, incomplete and elusive reporting. Although most studies did provide at least a short description of what they saw as AR, 7 studies provided no definition at all. Additionally, there were only 4 studies that included 3 or all of the 4 aspects of the AR definition in their description. Even the most mentioned aspects appeared in less than half of the included papers. Even though most papers did cite an AR approach of definition, some did not. In combination with the often-limited descriptions of AR, this makes it difficult to obtain a clear picture of how AR is perceived and performed in a particular study. This resonates with what Bradbury and colleagues [ 9 ] describe as 1 of the quality points of AR, namely “action research process and related methods (should be) clearly articulated and illustrated.” The best practices and lessons learned that were extracted from the included studies were seldom mentioned explicitly. Best practices were often hidden in the description of the project, without much reasoning. Similarly, lessons learned were often described as adaptations made during the project or as plans for the future. Although we observed that some lessons learned turned into best practices over time, we think that researchers could benefit more from each other’s work by providing concrete recommendations. This review is a step in that direction. Both aspects show that the reporting of AR studies in eHealth can be improved to show more clearly what eHealth AR projects can look like and help others in setting up such projects with specific recommendations.

Limitations

Approximately a third of the included papers (14 out of 44) were published more than 10 years ago. This also means that some of the technologies that are described in the older papers are now relatively old. However, this literature review focuses mainly on the AR methodology and lessons learned about doing action research. Therefore, there was no exclusion criterium regarding the publication date of the papers.

The search yielded several PD-related papers. These papers could have been included, given that some definitions of PD are very similar to AR. However, as our aim was to provide an overview of how AR is done, these were excluded as the researchers of these studies themselves did not identify their studies as being related to AR (ie, not referring to, mentioning, or describing AR). Although this offers a clearer picture of how researchers conduct AR, it also creates a potential limitation in that best practices and lessons learned could be enriched from PD literature.

This overview of AR approaches focuses mostly on the interconnectedness among the approaches, without a comprehensive comparison of the content. Comparing the approaches with regard to the specific aspects of AR that they describe would be a review in and of itself, going beyond the scope of this current review. Therefore, we decided to focus on the definitions that the authors themselves provided even when they also cited AR approaches, as these are most likely to reflect their own vision of AR.

This review illustrates how AR is conducted in eHealth studies. Studies that fulfilled the inclusion criteria mainly took place in western countries and lasted for 2 to 3 years. Different stakeholders were involved, but the most commonly involved groups were health care professionals and patients. As for the methods used, most studies opted for focus groups and interviews. Even though many studies cited the AR approach proposed by Reason and Bradbury [ 8 ], their own definitions of AR were often not explicit in terms of how they implemented AR. Future projects should report their AR definition as well as the best practices and lessons learned more clearly. Other recommendations include paying attention toward developing the skill and confidence of the stakeholders, being aware of the changing role of the researcher, frequently evaluating the project, and disseminating results in an understandable manner.

Abbreviations

Multimedia Appendix 1

Multimedia appendix 2.

Authors' Contributions: KO performed the literature search and analysis and was a major contributor in designing the study and writing the manuscript. CG contributed to the design of the study, assisted with the search and analysis, and made major contributions to the manuscript. FN and LvV contributed to the design of the study and substantially revised the manuscript. All authors read and approved the final manuscript. This project has received funding from the European Union’s Horizon 2020 research and innovation program (grant 857188).

Conflicts of Interest: None declared.

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• Writing Strong Research Questions | Criteria & Examples

Writing Strong Research Questions | Criteria & Examples

Published on October 26, 2022 by Shona McCombes . Revised on November 21, 2023.

A research question pinpoints exactly what you want to find out in your work. A good research question is essential to guide your research paper , dissertation , or thesis .

All research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly

Table of contents

How to write a research question, what makes a strong research question, using sub-questions to strengthen your main research question, research questions quiz, other interesting articles, frequently asked questions about research questions.

You can follow these steps to develop a strong research question:

• Choose your topic
• Do some preliminary reading about the current state of the field
• Narrow your focus to a specific niche
• Identify the research problem that you will address

The way you frame your question depends on what your research aims to achieve. The table below shows some examples of how you might formulate questions for different purposes.

Using your research problem to develop your research question

Note that while most research questions can be answered with various types of research , the way you frame your question should help determine your choices.

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Research questions anchor your whole project, so it’s important to spend some time refining them. The criteria below can help you evaluate the strength of your research question.

Focused and researchable

Feasible and specific

Complex and arguable

Relevant and original

Chances are that your main research question likely can’t be answered all at once. That’s why sub-questions are important: they allow you to answer your main question in a step-by-step manner.

Good sub-questions should be:

• Less complex than the main question
• Focused only on 1 type of research
• Presented in a logical order

Here are a few examples of descriptive and framing questions:

• Descriptive: According to current government arguments, how should a European bank tax be implemented?
• Descriptive: Which countries have a bank tax/levy on financial transactions?
• Framing: How should a bank tax/levy on financial transactions look at a European level?

Keep in mind that sub-questions are by no means mandatory. They should only be asked if you need the findings to answer your main question. If your main question is simple enough to stand on its own, it’s okay to skip the sub-question part. As a rule of thumb, the more complex your subject, the more sub-questions you’ll need.

Try to limit yourself to 4 or 5 sub-questions, maximum. If you feel you need more than this, it may be indication that your main research question is not sufficiently specific. In this case, it’s is better to revisit your problem statement and try to tighten your main question up.

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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.

Methodology

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

 Statistics

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

Research bias

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

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

As you cannot possibly read every source related to your topic, it’s important to evaluate sources to assess their relevance. Use preliminary evaluation to determine whether a source is worth examining in more depth.

This involves:

• Reading abstracts , prefaces, introductions , and conclusions
• Looking at the table of contents to determine the scope of the work
• Consulting the index for key terms or the names of important scholars

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“ x affects y because …”).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses . In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

• Researchability
• Feasibility and specificity
• Relevance and originality

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Just Practicing

Sharing my journey through landscapes of practice.

Forming a research question for action research

The minute I wrote that title, I realised that in a strict sense it is a little back to front.  We all know that our choice of research methodology should follow the definition of our aims, objectives and research question – form should follow function!  At least that is what the text books say.

But I’ll readily confess that I became a research student because I wanted the opportunity to learn more about and experience action research – others do that too for example some embark on a PhD because they want to home their quantitative data analysis skills.  So the ‘search’ for a research question and defining aims and objectives is also informed by the sort of knowledge, skills and experience I want to develop through my PhD and ultimately the sort of researcher I want to be.

Although I produced a draft research proposal last July, I felt uncomfortable about the research question I’d included, it didn’t seem to home in on what was interesting to me.  So I’ve been trying to focus on what an action research question looks like – unlike other forms of research there aren’t lots of published research proposals/protocols that you can easily locate so it is hard to get a feel for what you are trying to emulate.  And, action research books just simply say ‘form your research question’ as if it isn’t a problematic thing to do.

The main problem comes with the ‘dual’ function of action research – it is simultaneously a process to generate knowledge AND a process to improve a situation.  This distinction is described in different ways in the literature.  I have two favourites…

In literature discussing doing action research for academic accreditation (e.g. Zuber-Skerritt and Perry (2002); Zuber-Skerritt and Fletcher (2007); Coghlan and Brannick (2014)), a distinction is made between the Thesis Action Research which is carried out independently by the research candidate and the Core Action Research which is carried out collaboratively.  The ‘core action research’ is understood as being the fieldwork phase of the ‘thesis action research’.  The Thesis action research kind of operates at a meta-level – i.e. research on the core action research.  This means that the ‘thesis action research’ can have a different research question to the ‘core action research’.

The second way of making the distinction is even more powerful and quite exciting because it builds on the work of Checkland who developed soft systems methodology so it feels quite systemsy.  It appears in information system research discussions of action research (e.g. McKay and Marshall 2001, 2007).  The authors argue that action research has dual imperatives – what they refer to as a research imperative AND a problem solving imperative*.  Drawing on the idea of action research as a cyclical process, they argue that the dual imperatives mean that two interlinked cycles are operating – a research cycle and a problem solving cycle each driven by their own interests, aims and objectives and therefore different understandings of progress and success.  Importantly, they argue that it is important not to conflate the Methodology for the research (i.e. action research) with the Problem solving methodology (which could be any one of a range of organisational development or change management methodologies including systemsy ones like SSM or systemic inquiry).  The balance of the two imperatives is really important – focus on the problem solving imperative, then it becomes more like consultancy than research with potential risks to the ‘rigour’ of your findings.  Whereas focussing on the research imperative can lead to stakeholders in the research setting and participants feeling ‘done to’.

Taking the two distinctions together offers another helpful insight.  In my case, the research imperative is fulfilled independently as the ‘thesis action research’ – I am its owner and its customer is the academic community.  The ‘knowledge’ it generates is judged through the academic lens of validity, reliability and so on with all the caveats that those words have when drawing on qualitative data.  The problem solving imperative is fulfilled by the participants together as a collaborative problem solving process.  The participants are the co-owners and they and their stakeholders are the main customers.  It can be referred to generally as the core action research – but in itself it needs to be understood through the lens of creating improvement/change with learning and knowing-in-action being more important than formal propositional knowledge.  The change could be understood as ‘new’ learning generated through a process of social learning and/or it could be understood as new procedures, new practices, new ‘systems’ etc.

Back to the Checkland connection.  According to Checkland, research consists of a framework of ideas (F), which are employed via a methodology (M) to investigate an area of interest (A).  As a result of the research, learning will take place about F, and/or M and/or A.  McKay and Marshall (2001, 2007) argue that the dual imperatives of action research result in an adaptation to this general model.  The setting in which the research takes place has a ‘real world’ problem situation (P) which enables the researcher to find out about the area of interest (A).  As already mention there are two methodologies in use – the research methodology (MR) and the problem solving methodology (MPS).  This means the research can tell us about any combination of:

P – the real world problem situation A – the area of research interest F – the framework of ideas MR – i.e. action research (a methodological contribution) MPS – i.e. the chosen methodology to improve the situation

And so, opens up different options for framing your research aim(s) and question(s)…

It could focus on the area of research interest (A).  The setting for the research is one example – a case study if you like – of the research phenomenon of interest.  The research is about understanding and exploring this situation.  You could do this by other research methods but the value of using action research is you take a dynamic perspective of the forces and factors that shape the phenonenon of interest and you go back to test your ideas as the research proceeds.  As Lewin is cited as saying – you can’t understand a system unless you try to change it.  In my case then a research question is something like “What shapes policy work practice and its development in English local government?”

It could focus on the real world problem situation (P).  In my case the question would be something like “What is policy work practice like in local authority X?”  In my view this could by a risky route to take – whilst providing a thick description of the real world problem situation could be valuable to help with the generalisable lessons, there is a risk that the findings in themselves aren’t useful to third parties i.e. those not directly involved.  From the point of view of the research imperative, the Thesis has to make some attempt to go beyond the specific case and generalise.  However, this question could well be a natural part of the process in the research setting whereby the participants inquire – it belongs to the problem solving imperative, not the research one.

It could focus on the research methodology (MR).  This is more focused on making a methodological contribution and would be something like “What are the value and limitations of action research in understanding policy work practice and its development?”.  Most research will include an element of this – potentially in an implicit way – as the strengths and limitations of the research are generally included as part of the Thesis or the research articles.  The ‘answer’ comes as much from rigorous reflection on the experience of the process as it does from empirical data.  This feels like a ‘sideline’ – something to be aware of but not the main purpose of the research.

It could focus on the ‘problem solving’ methodology (MPS).  This is more like an evaluation – an assessment of whether the ‘problem solving’ methodology is useful and creates a ‘better’ situation.  It has parallels with an experiment – you hypothesise that using problem solving methodology X will create an improvement in the situation – and your research therefore focusses on evaluating what changes if any arise and if so why.  From the reading I have done so far I think this is a key way that action research is framed – “a what happens if I” orientation.  In my case then a research question would be something like “Is [methodology] an effective way of making improvements to policy work practice in English local government?”  This of course throws up other issues in terms of what constitutes an improvement, what constitutes effective and who gets to define that.

It could be on the framework of ideas (F).  I’m struggling to articulate this a little more and maybe that is because I have yet to really identify,  home in on, and justify my framework of ideas.  In general I know that they all seem to fall into the area of things that feel systemsy – particularly the soft and critical traditions and social learning.  McKay and Marshall (2001, 2007) don’t seem to suggest that there are different Fs for the research imperative and the problem solving imperative, but in theory they may not be congruent (probably leading to some cognitive discomfort!).  So I know I have some work to do here articulating my F for myself and others.   But a tentative research question about my tentative F would be something like “To what extent and in what ways are systems thinking and social learning helpful ideas in researching and developing policy work practice?”

Of course, there is no reason why these questions can’t be combined in a research project – making knowledge contributions and methodological ones.  But you’d need to design your data generation and analysis differently to answer each question so in my view I need to major on one – make it my primary question – and then treat anything else as a useful ‘by product’ of  the process.

The distinction of research imperative and problem solving imperative has also helped me develop clarity on how to write my research proposal.  Again books can be a little light on action research proposals and what may be different in them from research proposals from other disciplines.  But a general observation I have made is that some seem to imply there is no real difference whereas others imply a great deal of difference…but what I have realised is that this is all about whether you frame your proposal through the lens of the research imperative or the problem solving imperative.

Framing a proposal through the lens of the research imperative is more consistent with ‘traditional’ research proposals.  You set the scene by talking about what is already known about your phenomenon of interest, what the debates are and where the gaps are.  You then talk about what your research aims to do, what its question is.  The problem solving imperative surfaces more when you talk about the setting in which the research will take place – what is the problematic situation that participants will be addressing there and how that offers an opportunity to generate data that will help you with your research aim and question.

Framing a proposal through the lens of the problem solving imperative is more like a business case for change.  You start by describing the real world instance of the situation perceived as problematic in its wider context – why it needs to be improved and how you are going to set about doing that and later explain how the activities of research will complement and enhance that improvement/change journey.  The more I think about this the more I realise it isn’t a RESEARCH proposal at all – it is a change or improvement proposal.  In my case, this isn’t what my university wants but it could be what the stakeholders in the setting where I am going to do the research want.  I think it gets confused a little in books because in some cases universities are asking for this type of proposal.  One of the issues I have worried about with my research proposal is that I define too much up front, by myself, rather than involve the participants themselves in the ‘proposal’ – what I may find as I embark on the core action research is that this type of proposal is generated as part of the ‘action’ that the participants choose to take together.  As I said above this is their process, they are the owners not me – I am their facilitator or helper.

*I’m a little uncomfortable with the framing of ‘problem solving’ here – I’d prefer to say something like ‘improving a situation perceived as problematic’ – but that is quite clumsy and wordy.  So I am using ‘problem solving’ as the authors do but with some caveats about taking the words too literally.

Coghlan, D. and Brannick, T. (2014), Doing action research in your own organisation Fourth Edition., London: Sage Publications.

McKay, J. and Marshall, P. (2001), The dual imperatives of action research. Information Technology & People , 14(1), pp.46–59.

McKay, J. and Marshall, P. (2007), Driven by two masters, serving both: the interplay of problem solving and research in information systems action research projects. In Kock, N. (Editor), Information Systems Action Research: An applied view of emerging concepts and methods. New York: Springer US, pp. 131–158.

Zuber‐Skerritt, O. and Fletcher, M. (2007), The quality of an action research thesis in the social sciences. Quality Assurance in Education , 15(4), pp.413–436.

Zuber-Skerritt, O. and Perry, C. (2002), Action research within organisations and university thesis writing. The Learning Organization , 9(3/4), p.171.

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5 Science-Backed Ways to Write Clearly

If you want to become a better writer, ignore the lore and follow the science..

Posted June 24, 2024 | Reviewed by Devon Frye

• We read sentences written with active voice faster and comprehend content better than passive sentences.
• Studies document that we read and recall sentences with less effort when they turn content into micro-stories.
• Pronouns as subjects send readers backward, but readers comprehend sentences through prediction.
• Action verbs activate the brain's motor systems, creating semantic richness and enabling rapid comprehension.

Most writers assume they write well. Yet most writers grapple with the reality of writing as a black box.

That is, we know that writing works, but we’re a bit fuzzy on what makes readers grasp the meaning of some sentences instantly and without noticeable effort, while we find others difficult to understand after repeat re-readings. And contrary to popular belief, clear writing has virtually nothing to do with content, sentence length, or writing style.

Instead, we perceive sentences as clear when they map onto the methods our reading brains use to make sense of writing. Knowing the most important ones, including the below, could help make you a better writer.

1. Active voice makes sentences easier to read.

In dozens of studies, researchers have found that readers comprehend sentences more rapidly when sentences reflect the causal order of events. Two factors determine these outcomes.

First, human brains naturally perceive cause and effect, a likely survival mechanism. In fact, infants as young as six months can identify cause and effect, registered as spikes in heart rate and blood pressure.

Second, English sentence structure reflects causes and effects in its ordering of words: subject-verb-object order. In key studies, participants read sentences with active voice at speeds one-third faster than they read sentences in passive voice. More significantly, these same participants misunderstood even simple sentences in passive voice about 25 percent of the time.

As readers, we also perceive active sentences as both shorter and easier to read because active voice typically makes sentences more efficient. Consider the difference between the first sentence below, which relies on passive voice, and the second, which uses active voice.

• Passive: Among board members, there was an instant agreement to call for a pause in negotiations.
• Active: Board members instantly agreed to call for a pause in negotiations.

2. Actors or concrete objects turn sentences into micro-stories.

We read sentences with less effort—or cognitive load—when we can clearly see cause and effect, or, “who did what to whom,” as Ina Bornkessel-Schlesewsky puts it.

Bornkessel-Schlesewsky, a professor of cognitive neuroscience at the University of South Australia, used functional Magnetic Resonance Imaging (fMRI), to spot brains reacting to meaning and word order in sentences. Unsurprisingly, when the subjects of sentences are nouns clearly capable of performing actions, readers process sentences with greater speed and less effort. For actors, writers can choose people, organizations, publications—any individual, group, or item, intentionally created, that generates impact.

In addition to our unconsciously perceiving these sentences as easy to read and recall, we can also more readily identify actors in sentences. Furthermore, these nouns enhance the efficiency of any sentence by paring down its words. Take the examples below:

• Abstract noun as subject: Virginia Woolf’s examination of the social and economic obstacles female writers faced due to the presumption that women had no place in literary professions and so were instead relegated to the household, particularly resonated with her audience of young women who had struggled to fight for their right to study at their colleges, even after the political successes of the suffragettes.
• Actor as subject: In A Room of One’s Own , Virginia Woolf examined social and economic obstacles female writers faced. Despite the political success of the suffragettes, writers like Woolf battled the perception that women had no place in the literary professions. Thus Woolf’s book resonated with her audience, young women who had to fight for the right to study at their colleges.

3. Pronouns send readers backward, but readers make sense of sentences by anticipating what comes next.

Writers typically love to use pronouns as the subjects of sentences, especially the demonstrative pronouns this, that, these, those, and it , believing that these pronouns help link their sentences. Instead, pronouns save writers time and effort—but significantly cost readers for two likely reasons.

First, readers assume that pronouns refer to a singular noun, rather than a cluster of nouns, a phrase, or even an entire sentence. Second and more importantly, when writers use these pronouns without anchoring nouns, readers slow down and frequently misidentify the pronoun referents. In fact, readers rated writing samples with high numbers of sentences using demonstrative pronouns as being less well-written than sentences that used actors as subjects or pronouns anchored by nouns.

Pronoun as subjects: [Katie Ledecky] estimated that she swims more than 65,000 yards—or about 37 miles—a week. That adds up to 1,900 miles a year, and it means eons of staring at the black line that runs along the bottom of a pool. Actor as subject: [Katie] Ledecky swims up to 1,900 miles a year, mileage that entails seeming aeons of staring at the black line that runs along the bottom of a pool.

4. Action verbs make sentences more concrete, memorable, and efficient.

For years, old-school newspaper and magazine editors urged writers to use action verbs to enliven sentences.

However, action verbs also offer readers and writers significant benefits in terms of their memorability, as revealed in one study of readers’ recall of verbs. Of the 200 verbs in the study, readers recalled concrete verbs and nouns more accurately than non-action verbs.

In fact, when we read concrete verbs, our brains recruit the sensory-motor system, generating faster reaction times than abstract or non-action verbs, processed outside that system . Even in patients with dementia , action verbs remain among the words patients can identify with advanced disease, due to the richness of semantic associations that action verbs recruit in the brain.

• Non-action verbs: That the electric trolleys being abandoned in Philadelphia were greener and more efficient was not an insight available at that time.
• Action Verbs: Philadelphia scrapped its electric trolleys, decades before urban planners turned to greener, more efficient forms of transport.

5. Place subjects and verbs close together.

Over the past 20 years, researchers have focused on models of reading that rely on our understanding of sentence structure, a focus validated by recent studies.

As we read, we predict how sentence structure or syntax unfolds, based on our encounters with thousands of sentences. We also use the specific words we encounter in sentences to verify our predictions, beginning with grammatical subjects, followed by verbs.

As a result, readers struggle to identify subjects and verbs when writers separate them—the more distance between subjects and verbs, the slower the process of identifying them correctly. Moreover, readers make more errors in identifying correct subjects and verbs—crucial to understanding sentences—with increases in the number of words between subjects and verbs, even with relatively simple sentence structure.

Ironically, as writers tackle increasingly complex topics, they typically modify their subjects with phrases and adjective clauses that can place subjects at one end of the sentence and verbs at the opposite end. This separation strains working memory , as readers rely on subject-verb-object order in English to understand the sentence’s meaning. Consider, for example, this sentence from an online news organization:

In Florida, for instance, a bill to eliminate a requirement that students pass an Algebra I end-of-course and 10th-grade English/language arts exams in order to graduate recently cleared the Senate’s education committee.

On the other hand, when we place the subject and verb close together and use modifiers after the verb, we ease readers’ predictions and demands on working memory:

In Florida, the Senate’s education committee recently cleared a bill to eliminate two graduation requirements: an Algebra I end-of-course and 10th-grade English language arts.

Jane Yellowlees Douglas, Ph.D. , is a consultant on writing and organizations. She is also the author, with Maria B. Grant, MD, of The Biomedical Writer: What You Need to Succeed in Academic Medicine .

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