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The role of research at universities: why it matters.

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Teaching and learning, research and discovery, synthesis and creativity, understanding and engagement, service and outreach. There are many “core elements” to the mission of a great university. Teaching would seem the most obvious, but for those outside of the university, “research” (taken to include scientific research, scholarship more broadly, as well as creative activity) may be the least well understood. This creates misunderstanding of how universities invest resources, especially those deriving from undergraduate tuition and state (or other public) support, and the misperception that those resources are being diverted away from what is believed should be the core (and sole) focus, teaching. This has led to a loss of trust, confidence, and willingness to continue to invest or otherwise support (especially our public) universities.

Why are universities engaged in the conduct of research? Who pays? Who benefits? And why does it all matter? Good questions. Let’s get to some straightforward answers. Because the academic research enterprise really is not that difficult to explain, and its impacts are profound.

So let’s demystify university-based research. And in doing so, hopefully we can begin building both better understanding and a better relationship between the public and higher education, both of which are essential to the future of US higher education.   

Why are universities engaged in the conduct of research?

Universities engage in research as part of their missions around learning and discovery. This, in turn, contributes directly and indirectly to their primary mission of teaching. Universities and many colleges (the exception being those dedicated exclusively to undergraduate teaching) have as part of their mission the pursuit of scholarship. This can come in the form of fundamental or applied research (both are most common in the STEM fields, broadly defined), research-based scholarship or what often is called “scholarly activity” (most common in the social sciences and humanities), or creative activity (most common in the arts). Increasingly, these simple categorizations are being blurred, for all good reasons and to the good of the discovery of new knowledge and greater understanding of complex (transdisciplinary) challenges and the creation of increasingly interrelated fields needed to address them.

It goes without saying that the advancement of knowledge (discovery, innovation, creation) is essential to any civilization. Our nation’s research universities represent some of the most concentrated communities of scholars, facilities, and collective expertise engaged in these activities. But more importantly, this is where higher education is delivered, where students develop breadth and depth of knowledge in foundational and advanced subjects, where the skills for knowledge acquisition and understanding (including contextualization, interpretation, and inference) are honed, and where students are educated, trained, and otherwise prepared for successful careers. Part of that training and preparation derives from exposure to faculty who are engaged at the leading-edge of their fields, through their research and scholarly work. The best faculty, the teacher-scholars, seamlessly weave their teaching and research efforts together, to their mutual benefit, and in a way that excites and engages their students. In this way, the next generation of scholars (academic or otherwise) is trained, research and discovery continue to advance inter-generationally, and the cycle is perpetuated.

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University research can be expensive, particularly in laboratory-intensive fields. But the responsibility for much (indeed most) of the cost of conducting research falls to the faculty member. Faculty who are engaged in research write grants for funding (e.g., from federal and state agencies, foundations, and private companies) to support their work and the work of their students and staff. In some cases, the universities do need to invest heavily in equipment, facilities, and personnel to support select research activities. But they do so judiciously, with an eye toward both their mission, their strategic priorities, and their available resources.

Medical research, and medical education more broadly, is expensive and often requires substantial institutional investment beyond what can be covered by clinical operations or externally funded research. But universities with medical schools/medical centers have determined that the value to their educational and training missions as well as to their communities justifies the investment. And most would agree that university-based medical centers are of significant value to their communities, often providing best-in-class treatment and care in midsize and smaller communities at a level more often seen in larger metropolitan areas.

Research in the STEM fields (broadly defined) can also be expensive. Scientific (including medical) and engineering research often involves specialized facilities or pieces of equipment, advanced computing capabilities, materials requiring controlled handling and storage, and so forth. But much of this work is funded, in large part, by federal agencies such as the National Science Foundation, National Institutes of Health, US Department of Energy, US Department of Agriculture, and many others.

Research in the social sciences is often (not always) less expensive, requiring smaller amount of grant funding. As mentioned previously, however, it is now becoming common to have physical, natural, and social scientist teams pursuing large grant funding. This is an exciting and very promising trend for many reasons, not the least of which is the nature of the complex problems being studied.

Research in the arts and humanities typically requires the least amount of funding as it rarely requires the expensive items listed previously. Funding from such organizations as the National Endowment for the Arts, National Endowment for the Humanities, and private foundations may be able to support significant scholarship and creation of new knowledge or works through much more modest grants than would be required in the natural or physical sciences, for example.

Philanthropy may also be directed toward the support of research and scholarly activity at universities. Support from individual donors, family foundations, private or corporate foundations may be directed to support students, faculty, labs or other facilities, research programs, galleries, centers, and institutes.

Who benefits?

Students, both undergraduate and graduate, benefit from studying in an environment rich with research and discovery. Besides what the faculty can bring back to the classroom, there are opportunities to engage with faculty as part of their research teams and even conduct independent research under their supervision, often for credit. There are opportunities to learn about and learn on state-of-the-art equipment, in state-of-the-art laboratories, and from those working on the leading edge in a discipline. There are opportunities to co-author, present at conferences, make important connections, and explore post-graduate pathways.

The broader university benefits from active research programs. Research on timely and important topics attracts attention, which in turn leads to greater institutional visibility and reputation. As a university becomes known for its research in certain fields, they become magnets for students, faculty, grants, media coverage, and even philanthropy. Strength in research helps to define a university’s “brand” in the national and international marketplace, impacting everything from student recruitment, to faculty retention, to attracting new investments.

The community, region, and state benefits from the research activity of the university. This is especially true for public research universities. Research also contributes directly to economic development, clinical, commercial, and business opportunities. Resources brought into the university through grants and contracts support faculty, staff, and student salaries, often adding additional jobs, contributing directly to the tax base. Research universities, through their expertise, reputation, and facilities, can attract new businesses into their communities or states. They can also launch and incubate startup companies, or license and sell their technologies to other companies. Research universities often host meeting and conferences which creates revenue for local hotels, restaurants, event centers, and more. And as mentioned previously, university medical centers provide high-quality medical care, often in midsize communities that wouldn’t otherwise have such outstanding services and state-of-the-art facilities.

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And finally, why does this all matter?

Research is essential to advancing society, strengthening the economy, driving innovation, and addressing the vexing and challenging problems we face as a people, place, and planet. It’s through research, scholarship, and discovery that we learn about our history and ourselves, understand the present context in which we live, and plan for and secure our future.

Research universities are vibrant, exciting, and inspiring places to learn and to work. They offer opportunities for students that few other institutions can match – whether small liberal arts colleges, mid-size teaching universities, or community colleges – and while not right for every learner or every educator, they are right for many, if not most. The advantages simply cannot be ignored. Neither can the importance or the need for these institutions. They need not be for everyone, and everyone need not find their way to study or work at our research universities, and we stipulate that there are many outstanding options to meet and support different learning styles and provide different environments for teaching and learning. But it’s critically important that we continue to support, protect, and respect research universities for all they do for their students, their communities and states, our standing in the global scientific community, our economy, and our nation.

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Chapter 1: Introduction to Educational Research

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Chapter 22 Evaluating a Research Report Gay, Mills, and Airasian

Research Methods in Crime and Justice

Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.

The Cycle of Science Research question about the real world Research question about the real world Theory Interpretation Statistical analyses Statistical.

Educational Research: Introduction to the Concept

Introduction to Research

Chapter 1 Conducting & Reading Research Baumgartner et al Chapter 1 Nature and Purpose of Research.

Historical Research.

Chapter 3 Preparing and Evaluating a Research Plan Gay and Airasian

Sabine Mendes Lima Moura Issues in Research Methodology PUC – November 2014.

Quantitative and Qualitative Approaches

Research problem, Purpose, question

Introduction to Educational Research

Quantitative and Qualitative Approaches Dr. William M. Bauer

Chapter 14 Overview of Qualitative Research Gay, Mills, and Airasian

Chapter 19: Mixed Methods Research

McGraw-Hill © 2006 The McGraw-Hill Companies, Inc. All rights reserved. The Nature of Research Chapter One.

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The importance of undergraduate research

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Learning Domain: Social Work

Standard: Basic Research Methodology

Lesson 10: Sampling in Qualitative Research

Lesson 11: qualitative measurement & rigor, lesson 12: qualitative design & data gathering, lesson 1: introduction to research, lesson 2: getting started with your research project, lesson 3: critical information literacy, lesson 4: paradigm, theory, and causality, lesson 5: research questions, lesson 6: ethics, lesson 7: measurement in quantitative research, lesson 8: sampling in quantitative research, lesson 9: quantitative research designs, powerpoint slides: sowk 621.01: research i: basic research methodology.

The twelve lessons for SOWK 621.01: Research I: Basic Research Methodology as previously taught by Dr. Matthew DeCarlo at Radford University. Dr. DeCarlo and his team developed a complete package of materials that includes a textbook, ancillary materials, and a student workbook as part of a VIVA Open Course Grant.

The PowerPoint slides associated with the twelve lessons of the course, SOWK 621.01: Research I: Basic Research Methodology, as previously taught by Dr. Matthew DeCarlo at Radford University. 

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IMPORTANCE OF RESERCH ACTIVITIES IN HIGHER EDUCATION

Research is addition of new knowledge to existing knowledge in a field. It is also a discipline that teaches the researcher the method of seeking and identifying new knowledge and of formally codifying such knowledge. Updating one's knowledge is indispensable in fields that have practical and technological implications. Failure to update can result in invalidation of one's knowledge and practice. Explosion of knowledge emphasizes research. Specialization becomes indispensible. But over emphasis on research makes it focus-less. Knowledge gathered is unassimilated and therefore unusable. The anxiety to publish or to win a degree leads to unethical practices like plagiarism. Also specialization is often at the cost of comprehensive basic knowledge. Research under such circumstances is a ritual that has no meaning.

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Higher education and research can't be separated for many reasons especially quality of education. All the developed and developing countries are allocating huge amount of funds for educational research with a hope that it would strengthen the process of education. On the other hand, good education also leads to quality research. The present paper is a modest attempt towards highlighting some of the theoretical aspects related to educational research, its nature, relevance and issues related to some dimensions of education. Education assures national and social development, and researches leads to educational developments.

Sreeramana Aithal

Research is a continuous process in higher educational institutions due to many reasons which include, identification of new problems to be solved in a given area, creation of new knowledge in a given subject, interconnecting and interrelating different subjects, identifying new skills, ideas, concepts, theories, developing new technologies and systems which makes life more comfortable, finding the relationship between various variables of a system in an effort to simplify it, deepening insight into a system or method with an intention of discovering new things, etc. Like other organizations which have the objective of enhancing their productivity or quality of service for long-term benefits, higher education institutions also have to struggle to enhance their output or performance which is mainly creating and disseminating new knowledge through research and publications. This can be achieved by including both faculty members and students actively in research. " Theory A " on organizational performance has been found to be applicable for enhancing research productivity. The theory focuses on creativity as an inherent urge, responsibility as fulfilling target and accountability as commitment and role model as motivation for improved performance. This paper discusses the methodical sequence and outlines the challenges and opportunities for research and publications in higher educational institutions.

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The situation today is that research efforts are very unevenly distributed between different countries and regions. Some industrialized countries conduct the greater part of the world’s research. This picture has several problematic consequences for the developing countries that do not have a large share in the global research effort. On the one hand, most research is directed at problems and questions that are related to the needs of the industrialized countries where the research is conducted. On the other hand, a certain level of education, research and technology competence is necessary to benefit from knowledge developed elsewhere. Platform of Research and innovation for higher education institutions is an entrance ticket to take part in the international knowledge development. With this research article, we have tried to explore & discuss the role, contribution & implications of research for the sustainable development of higher education institutions (HEIs). Key Words: Sustainable development, Quality Education, Education and research, Research innovations.

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Academic training in research is fundamental in the quality of higher education

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Academic training in research is fundamental in the quality of higher education and within this context, technological mediation becomes pivotal to reach student-centered learning objectives in any moment and at any time. The findings of a study, the purpose of which has been to evaluate the results of the formative research of two groups of students that have interacted in learning environments (E-learning and U-learning), are presented. The research follows a quasi-experimental study with a design of chronological series and multiple treatment, framed in three stages that were defined as referencing, systematization, and analysis. The sample consisted of 189 fourth-year students of the Early Childhood Education degree, at El Bosque University in Bogotá, Colombia. The results reveal that U-learning environments strengthen and consolidate formative research as an ongoing process for undertaking educational research through personalization, adaptation, and situational learning, marking meaningful differences with respect to E-learning environments during the systematization stage. The intervention with U-learning environments has revealed challenges and needs in the academic curriculum such as strengthening the link between evaluation and educational research in the field of professional practice, as well as the incorporation of technology with the purpose of making it something natural, adaptable, and interoperable, that students are able to use it without even thinking about it.

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Teaching and research are the two most important traditional functions of universities. It is widely recognised that teaching contributes to enrichment of research and research contributes to enhanced levels of teaching. Both are closely related, inter-dependent and mutually supportive. ...

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Importance of Research

Mar 16, 2019

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The Carroll Park Municipal Golf Course: A Case Study of the National Civil Rights Campaign: 1923-1954. Part of a Larger Study: The History of Racial and Ethnic Access Within Baltimore’s Carroll Park: 1870-1954. Defended June, 2006.

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The Carroll Park Municipal Golf Course: A Case Study of the National Civil Rights Campaign: 1923-1954

Part of a Larger Study: The History of Racial and Ethnic Access Within Baltimore’s Carroll Park: 1870-1954. Defended June, 2006. • In what ways has park access on the land that became Carroll Park been influenced by issues of race and ethnicity? • The Schuetzen Period: 1870-1886. • The Segregation Era: 1923-1954

Importance of Research • Recent findings (Wolch et. al, 2005) indicate that America’s urban parks are still coming to terms with a past marked by segregation and racial violence. Reluctance to enter a park due to issues of race and ethnicity can have deep historical roots. Nevertheless, most modern research on urban parks focus solely on the present.

Introduction • Where is Carroll Park?

The Origins of the Carroll Park Municipal Golf Course • 1888: Death of Mary Ludlow Carroll, the last member of the family to own the Mount Clare property in its entirety. • 1890-1907: City Park Board Purchases land east of Monroe Avenue from Carroll heirs and other landowners in order to serve residents of southwestern Baltimore. • East of Monroe Street: Largely preserved green space near the Mount Clare Mansion. Designed as a mixed-use park by the Olmsted Firm and Carroll Park Superintendent, Charles Seybold. • West of Monroe Street: Scarred industrial landscape from a history of brickyards, clay pits, and munitions factories. • Fears that lack of park development would result in loss of park land to business. 10 Acres to Montgomery Ward, 1924. • Charles Hook, 1923: Director of Parks and Recreation in Baltimore announces plans for a 65-acre golf course on the property. • Reasons for growing interest in the sport of golf.

Carroll Park, 1914.

Timeline: 1923-1936 • 1923: Carroll Park Golf Course opened on 35 acres west of Monroe Street. Predated only by Clifton Park. • 1920s: All of Baltimore’s golf courses remained “White Only”, forcing Black players to travel to Philadelphia or Washington, D.C. • Early 1930s: Monumental Golf Club of Baltimore challenged the policy of segregation in a campaign of protests and newspaper articles. • Leading Figures: Willie Adams, Dallas Nicholas, Bernard Harris. • Lack of direct ACLU Support. • 1934: Amidst vehement White objections, African Americans given rights to play at Carroll Park every other day. • 1936: Full course rights at Carroll Park given to African Americans. Whites barred from playing. • Carroll Park was known as the city’s worst golf course. It lacked a club house, contained only nine holes, no bunkers, and sand greens.

Baltimore’s Golf Courses, 1940

Timeline: 1936-1943 • National Civil Rights Strategy: Do not directly attack segregation, but make whites pay to make separate facilities equal under the Plessy v. Ferguson decision of 1898. • 1940: National Boxing Hero, Joe Louis, recommends that local activists fight to make Carroll Park’s facilities equal. • May, 1942: Using African American service in World War II as a pretext, Black golfers secure the right to play at all courses within Baltimore. • June, 1942: Heavy protests from White neighborhoods (Not White golfers) force the Park Board to revoke its decision. • July, 1942: An all white Jury determines that the facilities at Carroll Park are not equal. Judge Eugene O’Dunne restores the right of African Americans to play any course. • December, 1942: Appeals Court overturns this decision on technical grounds (Judge O’Dunne had not been present for the jury’s verdict). • April, 1943: Compromise Reached: Carroll Park would be improved. Blacks could use all other courses in the meantime.

Timeline: 1943-1954 • 1945: Renovations to Carroll Park completed: Yardage increased, clubhouse improved, grass greens, and sand bunkers. African American golfers forced to return to Carroll Park. • 1948: In a new lawsuit, Judge Chestnut ruled that nine holes could not be equal to eighteen. African Americans given rights to play all courses, though on alternating days. • Disagreement between Commissioners Harris and Boone. • 1949: Gang battle between Whites and Blacks in Carroll Park, south of Mount Clare. One African American, 19-year old Linwood Matthews, killed. Park Board blamed for creating racial tension. • 1951: Monumental Golf Club sues Park Board again. Total victory – all golf courses fully desegregated. • 1953-1954: Lawsuit to desegregate Carroll Park swimming facilities. Brown v. Board (1954) settles the case prematurely. End of “Separate but Equal” • 1957: Swimming Facilities at Carroll Park closed due to lack of use. Whites boycotted the pool, rather than allow their families to swim with Blacks.

IV. Conclusions • Today, Carroll Park exists without any limitations in ethnic or racial access. Example of an urban green space in which the errors of the past have been corrected. • Numbers on general park usage are unavailable, though golf course patrons are approximately 40% white and 60% black. • In conjunction with other research projects (Korth, 2005), this thesis can help to understand how modern-day patterns of park access came to be, as well as how well the Olmsted Brothers’ plan of equal park access to all held up over the course of history.

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Role and Need of Research in Higher Education

On hear of the term higher education one thing that makes a lot of significance is the outcome from the learning that has been done in those crucial years.

Students investing in higher education must be given exposure and opportunities to be able to use all that knowledge to evolve themselves as well as be able to contribute in the discipline with better research, studies and other discoveries made.

The pointers mentioned below implies the role and need of research in higher education and why research must be a part of every higher education institution.

1. Teaching will improve if the staff engages in research (research-based teaching):

The first argument emphasizes on the necessity of research oriented teaching. Educators engaged in research are updated with latest information and updated facts instead of all that is mentioned in a book years old. It is essential that teachers engage in research to come out with latest and original information but also when they expect students to be research oriented they must have familiarity with various aspects to the concept. Also, educators familiar with research based teaching can help students with the following things:

– Teaching research results

– Making research known

– Showing what it means to be a researcher

– Helping to conduct research

– Providing research experience   

2. Students will learn more if they come into contact with research (research-based learning):

Students when involved in research based learning are bound to learn more and better than they would without the integration of research.  Students start as consumers of knowledge and move toward knowledge producers in the following eight steps.

– Students are provided with an overview of the basic facts, terms, and ideas related to the discipline.

– Students learn about research findings in the (sub) field through lectures and readings dedicated to current research.

– Students discuss and critique research findings and approaches in the discipline or (sub) field; assignments include literature reviews or summaries.

– Students learn some research methodologies; engage in limited applications of those approaches in course assignments, such as statistical analyses.

– Students learn in a course dedicated to the research methodologies, engage in extensive applications of a variety of approaches.

– Students engage in faculty designed and led original (to the student) research such as replications of existing studies.

– Students engage in faculty designed and led original research such as research related to faculty projects and/or conducted in faculty labs.

– Students engage in student designed and led original (to the discipline) research such as a senior thesis or capstone project

3. Professional practice will improve if professional workers in their training learn how to base their work on research-based knowledge (research-based practice):

This highlights the importance of hiring professionals who are familiar with research based practice. Having trainers who can help the current staff to make research based modules is also essential. To integrate the practice of research it is important to learn how to base curriculum aligned to the practice of research.

4. Professional programs have an obligation to improve the knowledge basis of professional work through research (research-based knowledge production):

The main concern of this point is the importance of doing research to enhance ‘evidence-based’ knowledge. The need of this practice is to help students learn with hands-on experience and not just what’s said and done but speak and do!

What to do for more research based teaching –learning

– Deciding that education and research are equally important.

– Appointing at least one university professor of research education.

– Establishing a university Centre for Teaching and Learning.

– Building a university Teaching and Learning House.

– Linking research and teaching committees.

– Bridging any divides between research staff and teaching staff.

– Appointing only academics who excel in both research and teaching.

– Strengthening positive attitudes towards research by students among staff and students.

– Making resources available for students to do research.

– Making it possible that libraries give information literacy instruction to students.

– Offering opportunities and incentives for teachers for further development of their ‘research based’ teaching competence and excellence.

– Creating and stimulating opportunities for dissemination of successful practices.

– Recognizing teaching excellence.

– Introducing an undergraduate student research award.

– Monitoring the growth of ‘research-based’ teaching.

– Ordering and financing more research of the teaching-research nexus and of research-based teaching and learning in particular.

Universities can improve the relevance of the education and can better prepare the students for follow-up studies and to the new and emerging demands of the labor market in the twenty-first century. Moreover, a close intertwining of teaching and research strengthens their identity. Academics can help students by engaging them in research to better develop highly valued competencies. More research-based teaching can also make teaching more attractive for academics and can make teaching instrumental to the academics’ own research.

“Re-inventing Research-Based Teaching and Learning by Henk Dekker and Sylvia Walsarie Wolff”  is a paper prepared for presentation at the meeting of the European Forum for Enhanced Collaboration in Teaching of the European University Association from December 2016. This is a must read to get to the depths of understanding about the need and importance of research in higher education.

Don’t forget to share your views on the importance of research in higher education. Make a mention in the comment section below!

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What Are Professional Development Goals? 10 Examples + How to Set Them

Professional development goals can help you achieve your short- and long-term objectives in your career.

Professional development goals are objectives you can set for yourself to help further your career. These might include taking steps to learn relevant skills, expand your professional network, or find more satisfaction at work.

Why set professional development goals?

Setting professional development goals can have many benefits. They can help you stay up-to-date on industry trends, increase engagement and job satisfaction, and align you with what you want out of your career and life.

Setting goals that are SMART—specific, measurable, achievable, relevant, and time-bound —can clarify what you need to achieve in the short-term to arrive at your long-term goals. Read more about setting SMART goals below.

10 examples of professional development goals

Here are ten examples of professional development goals to inspire your own:

1. Develop a new skill set.

Growing professionally often means expanding the arsenal of things you’re able to do. What skill you choose to develop can depend on your industry, job, and personal preferences. In-demand skills across the job sector in 2022 included cloud computing, data analysis skills like artificial intelligence and SQL, management, and UX design [ 1 ].

Don’t know where to start? Approach your manager and see if they have suggestions. You can also browse job descriptions of positions you’d be interested in pursuing; the common skills listed will help you get a sense of what’s in-demand in your field. Do some research to get a sense of what you want to learn and what will be useful to your work.

Develop skills by taking online or in-person courses, shadowing a coworker, or going back to school, among other ways. Think about what fits your schedule and the level of expertise you’re aiming for to see what works best for you.

2. Develop your workplace skills.

Workplace skills are the tools and practices that help people in a workplace connect and interact smoothly with one another. Sometimes referred to as human or soft skills, workplace skills can be crucial for advancing to higher-level positions. Workplace skills include verbal and nonverbal communication, empathy, self-awareness, and leadership.

Specific goals might include:

Complete an online course on communication, negotiation, or psychology

Join a social public speaking club, such as a local Toastmasters chapter

Read more: Hard Skills vs. Soft Skills: What’s the Difference?

3. Take up leadership responsibilities.

Actively seeking out leadership opportunities will allow you to develop leadership skills , and show others that you are striving to grow. Approach your manager to see how you might be able to put your leadership skills into practice. Have a few suggestions at the ready. Here are some examples to get your started:

Lead two team meetings this quarter

Plan and lead a team initiative to collectively learn a new tool or skill

Plan the next team offsite or activity

4. Expand your professional network.

Expanding your professional network can expose you to new ideas, build your profile, keep you informed of new job opportunities, and help you learn continuously. 

Sign up for events to attend in your field, join professional groups in person or through social media platforms like Facebook or LinkedIn, or find opportunities to volunteer your skills through volunteer databases like VolunteerMatch . 

Some concrete goals you can set include:

Attend five in-person or virtual professional events

Find and join three professional groups on LinkedIn

Read more: 9 Networking Tips to Expand and Strengthen Your Network

5. Level-up your credentials.

Beefing up your credentials can open up new career opportunities or clear a path to a promotion. Credentials can include certifications, professional certificates , and degrees. See what makes the most sense for both your short- and long-term career goals . Once you get your credential, don’t forget to inform your manager and list it in relevant places like your resume and LinkedIn profile .

Relevant goals might look like the following:

Earn a certification in your field in the next quarter or year

Complete a professional certificate

Find five degree programs to begin applying to

Read more: Upskilling: What It Means and How It Can Help Your Career

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6. Consume media in your field.

Learning more about your field through various media—like books, podcasts, and news publications, to name a few—can enrich your understanding of the context around your work and inform you of ways to improve. Plus, as passive ways of absorbing information, you’ll be able to learn as you, say, go on a walk or wait for the bus.

Ask coworkers or professionals in your network about recommendations. Otherwise, a quick online search should yield plenty of ideas, whether you’re looking for marketing podcasts , books on project management , or something else.

Here are some concrete goals you might aspire to:

Read two books in your field in a quarter

Listen to one podcast on a relevant topic a week

Find 10 experts in your field on Twitter to follow

7. Find other ways to deepen job satisfaction.

Being satisfied as a professional doesn’t necessarily mean striving for constant achievement and earning promotions. Job satisfaction is tied to many factors besides enjoying the work itself—including forming fulfilling relationships with coworkers, achieving work-life balance , and keeping your mental and physical health in check. Plus, there’s evidence that links job satisfaction to higher productivity and less turnover in workplaces—being a happy worker is likely going to benefit your company too [ 2 ].

Here are some goals you might set to improve your workday:

Schedule lunch or coffee chats with coworkers 

Join or start a workplace interest group

Create a plan to prepare healthy meals for lunch

Set reminders to take intermittent breaks throughout the day

Clarify boundaries on work expectations outside of working hours

8. Take a relevant course.

Courses can help you develop skills, learn about issues relevant to your work, and flex new parts of your brain. Courses can be directly related to your work responsibilities, but this might be an opportunity to challenge yourself to develop in new ways. Data analysis , project management , or UX design courses may give you the skills you need—but consider other fields like creative writing, public speaking, or foreign languages that can deepen your work in more unexpected ways.

Specific goals for coursework might look like the following:

Complete a course on XYZ topic in a quarter 

Map out a plan for coursework you’ll take throughout the year

Did you know?

You can start enrolling in hundreds of free courses after you sign up for Coursera. Join our global community and start learning today .

9. Shadow another department.

Shadowing another department can have myriad positives: it can encourage communication and cooperation across siloed teams, inspire ways to improve your own team, and leave you with a better understanding of how your organization works. 

You can set goals such as:

Ask three people from different departments to lunch

Create a program in your workplace to encourage cross-team shadowing

10. Find a mentor.

A mentor can help you navigate challenges in the workplace and help you progress in your career. 

Finding a mentor might sound like a daunting task, but be assured that many have done it before. Some workplaces have mentoring programs in place that make it easy for people to connect with a more experienced professional. You might also find that your professional network will come in handy here. You can start by finding people who have had careers you find close to your aspirations in professional groups or alumni communities. Or if it makes sense, reach out to somebody in your workplace that you think you’ll be able to learn from.

Goals that will help you land a mentor include:

Create a pitch that you can use to contact potential mentors

Arrange a meeting with potential mentors to see if they’re a fit

Map out your short- or long-term goals (or both) of having a mentor

How to set professional development goals

1. know what you’re working towards..

Start by taking some time to consider what you want out of your career, now or in the future. Goal-setting is a useful exercise because it can clarify what you really want out of your career, and identify tangible steps to achieve it.

Don’t know what you want to do in five or 10 years yet? Start smaller, and identify your interests. If you’ve always admired your manager who can speak eloquently in front of others, consider a public speaking course. If you find yourself fascinated by your coworker’s ability to analyze data sets, try learning Python or another programming language.

2. Set SMART goals.

SMART goals are goals that are specific, measurable, achievable, relevant, and time-bound. Here’s what each of those components mean:

Specific: Goals should be well-defined and unambiguous so that you know exactly what you’re aspiring to.

Measurable: Goals should have a clear way of identifying whether you’ve achieved them, or if not, how close you came to them. For example, saying Finish three modules of my online course is more measurable than a goal like Work on my online course.

Achievable: Setting a goal that you can realistically achieve is key to actually achieving them. Plus, thinking in the back of your mind that a goal is impossible may be demotivating. Keep yourself motivated by setting reasonable goals.

Relevant: Your goals should be relevant to you—that is, they should align with your long-term aspirations and values. Think of this as the “why” of your goal.

Time-bound: Set a deadline for your goals so you can stay on track and motivated. 

Getting started on professional development goals

Professional development goals can help identify what you want your career to look like in the short and long term, and what steps you need to take to get where you want to be. Ready to get started? Learn from world-class institutions with over 7,000 courses, certificates, and degrees on Coursera .

Article sources

1. Coursera. " Global Skills Report , https://pages.coursera-for-business.org/rs/748-MIV-116/images/Coursera-Global-Skills-Report-2022.pdf." Accessed May 18, 2023.

2. Harvard Business Review. " Proof That Positive Work Cultures Are More Productive , https://hbr.org/2015/12/proof-that-positive-work-cultures-are-more-productive." Accessed May 18, 2023.

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Americans Are Losing Faith in the Value of College. Whose Fault Is That?

For most people, the new economics of higher ed make going to college a risky bet.

Credit... Illustration by Sean Dong

Supported by

By Paul Tough

Paul Tough is a contributing writer for the magazine who has written several books on inequality in education.

• Sept. 5, 2023

A decade or so ago, Americans were feeling pretty positive about higher education. Public-opinion polls in the early 2010s all told the same story. In one survey, 86 percent of college graduates said that college had been a good investment ; in another, 74 percent of young adults said a college education was “very important” ; in a third, 60 percent of Americans said that colleges and universities were having a positive impact on the country. Ninety-six percent of parents who identified as Democrats said they expected their kids to attend college — only to be outdone by Republican parents, 99 percent of whom said they expected their kids to go to college.

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In the fall of 2009, 70 percent of that year’s crop of high school graduates did in fact go straight to college. That was the highest percentage ever, and the collegegoing rate stayed near that elevated level for the next few years. The motivation of these students was largely financial. The 2008 recession devastated many of the industries that for decades provided good jobs for less-educated workers, and a college degree had become a particularly valuable commodity in the American labor market. The typical American with a bachelor’s degree (and no further credential) was earning about two-thirds more than the typical high school grad, a financial advantage about twice as large as the one a college degree produced a generation earlier. College seemed like a reliable runway to a life of comfort and affluence.

A decade later, Americans’ feelings about higher education have turned sharply negative. The percentage of young adults who said that a college degree is very important fell to 41 percent from 74 percent. Only about a third of Americans now say they have a lot of confidence in higher education. Among young Americans in Generation Z, 45 percent say that a high school diploma is all you need today to “ensure financial security.” And in contrast to the college-focused parents of a decade ago, now almost half of American parents say they’d prefer that their children not enroll in a four-year college.

The numbers on campus have shifted as well. In the fall of 2010, there were more than 18 million undergraduates enrolled in colleges and universities across the United States. That figure has been falling ever since, dipping below 15.5 million undergrads in 2021. As recently as 2016, 70 percent of high school graduates were still going straight to college; now the figure is 62 percent.

Outside the United States, meanwhile, higher education is more popular than ever. Our global allies and competitors have spent the last couple of decades racing to raise their national levels of educational attainment. In Britain, the number of current undergraduates has risen since 2016 by 12 percent. (Over the same period, the American figure fell by 8 percent.) In Canada, 67 percent of adults between 25 and 34 are graduates of a two- or four-year college, about 15 percentage points higher than the current American attainment rate.

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The state of AI in 2023: Generative AI’s breakout year

You have reached a page with older survey data. please see our 2024 survey results here ..

The latest annual McKinsey Global Survey  on the current state of AI confirms the explosive growth of generative AI (gen AI) tools . Less than a year after many of these tools debuted, one-third of our survey respondents say their organizations are using gen AI regularly in at least one business function. Amid recent advances, AI has risen from a topic relegated to tech employees to a focus of company leaders: nearly one-quarter of surveyed C-suite executives say they are personally using gen AI tools for work, and more than one-quarter of respondents from companies using AI say gen AI is already on their boards’ agendas. What’s more, 40 percent of respondents say their organizations will increase their investment in AI overall because of advances in gen AI. The findings show that these are still early days for managing gen AI–related risks, with less than half of respondents saying their organizations are mitigating even the risk they consider most relevant: inaccuracy.

The organizations that have already embedded AI capabilities have been the first to explore gen AI’s potential, and those seeing the most value from more traditional AI capabilities—a group we call AI high performers—are already outpacing others in their adoption of gen AI tools. 1 We define AI high performers as organizations that, according to respondents, attribute at least 20 percent of their EBIT to AI adoption.

The expected business disruption from gen AI is significant, and respondents predict meaningful changes to their workforces. They anticipate workforce cuts in certain areas and large reskilling efforts to address shifting talent needs. Yet while the use of gen AI might spur the adoption of other AI tools, we see few meaningful increases in organizations’ adoption of these technologies. The percent of organizations adopting any AI tools has held steady since 2022, and adoption remains concentrated within a small number of business functions.

Table of Contents

• It’s early days still, but use of gen AI is already widespread
• Leading companies are already ahead with gen AI
• AI-related talent needs shift, and AI’s workforce effects are expected to be substantial
• With all eyes on gen AI, AI adoption and impact remain steady

About the research

1. it’s early days still, but use of gen ai is already widespread.

The findings from the survey—which was in the field in mid-April 2023—show that, despite gen AI’s nascent public availability, experimentation with the tools  is already relatively common, and respondents expect the new capabilities to transform their industries. Gen AI has captured interest across the business population: individuals across regions, industries, and seniority levels are using gen AI for work and outside of work. Seventy-nine percent of all respondents say they’ve had at least some exposure to gen AI, either for work or outside of work, and 22 percent say they are regularly using it in their own work. While reported use is quite similar across seniority levels, it is highest among respondents working in the technology sector and those in North America.

Organizations, too, are now commonly using gen AI. One-third of all respondents say their organizations are already regularly using generative AI in at least one function—meaning that 60 percent of organizations with reported AI adoption are using gen AI. What’s more, 40 percent of those reporting AI adoption at their organizations say their companies expect to invest more in AI overall thanks to generative AI, and 28 percent say generative AI use is already on their board’s agenda. The most commonly reported business functions using these newer tools are the same as those in which AI use is most common overall: marketing and sales, product and service development, and service operations, such as customer care and back-office support. This suggests that organizations are pursuing these new tools where the most value is. In our previous research , these three areas, along with software engineering, showed the potential to deliver about 75 percent of the total annual value from generative AI use cases.

In these early days, expectations for gen AI’s impact are high : three-quarters of all respondents expect gen AI to cause significant or disruptive change in the nature of their industry’s competition in the next three years. Survey respondents working in the technology and financial-services industries are the most likely to expect disruptive change from gen AI. Our previous research shows  that, while all industries are indeed likely to see some degree of disruption, the level of impact is likely to vary. 2 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. Industries relying most heavily on knowledge work are likely to see more disruption—and potentially reap more value. While our estimates suggest that tech companies, unsurprisingly, are poised to see the highest impact from gen AI—adding value equivalent to as much as 9 percent of global industry revenue—knowledge-based industries such as banking (up to 5 percent), pharmaceuticals and medical products (also up to 5 percent), and education (up to 4 percent) could experience significant effects as well. By contrast, manufacturing-based industries, such as aerospace, automotives, and advanced electronics, could experience less disruptive effects. This stands in contrast to the impact of previous technology waves that affected manufacturing the most and is due to gen AI’s strengths in language-based activities, as opposed to those requiring physical labor.

Responses show many organizations not yet addressing potential risks from gen AI

According to the survey, few companies seem fully prepared for the widespread use of gen AI—or the business risks these tools may bring. Just 21 percent of respondents reporting AI adoption say their organizations have established policies governing employees’ use of gen AI technologies in their work. And when we asked specifically about the risks of adopting gen AI, few respondents say their companies are mitigating the most commonly cited risk with gen AI: inaccuracy. Respondents cite inaccuracy more frequently than both cybersecurity and regulatory compliance, which were the most common risks from AI overall in previous surveys. Just 32 percent say they’re mitigating inaccuracy, a smaller percentage than the 38 percent who say they mitigate cybersecurity risks. Interestingly, this figure is significantly lower than the percentage of respondents who reported mitigating AI-related cybersecurity last year (51 percent). Overall, much as we’ve seen in previous years, most respondents say their organizations are not addressing AI-related risks.

2. Leading companies are already ahead with gen AI

The survey results show that AI high performers—that is, organizations where respondents say at least 20 percent of EBIT in 2022 was attributable to AI use—are going all in on artificial intelligence, both with gen AI and more traditional AI capabilities. These organizations that achieve significant value from AI are already using gen AI in more business functions than other organizations do, especially in product and service development and risk and supply chain management. When looking at all AI capabilities—including more traditional machine learning capabilities, robotic process automation, and chatbots—AI high performers also are much more likely than others to use AI in product and service development, for uses such as product-development-cycle optimization, adding new features to existing products, and creating new AI-based products. These organizations also are using AI more often than other organizations in risk modeling and for uses within HR such as performance management and organization design and workforce deployment optimization.

AI high performers are much more likely than others to use AI in product and service development.

Another difference from their peers: high performers’ gen AI efforts are less oriented toward cost reduction, which is a top priority at other organizations. Respondents from AI high performers are twice as likely as others to say their organizations’ top objective for gen AI is to create entirely new businesses or sources of revenue—and they’re most likely to cite the increase in the value of existing offerings through new AI-based features.

As we’ve seen in previous years , these high-performing organizations invest much more than others in AI: respondents from AI high performers are more than five times more likely than others to say they spend more than 20 percent of their digital budgets on AI. They also use AI capabilities more broadly throughout the organization. Respondents from high performers are much more likely than others to say that their organizations have adopted AI in four or more business functions and that they have embedded a higher number of AI capabilities. For example, respondents from high performers more often report embedding knowledge graphs in at least one product or business function process, in addition to gen AI and related natural-language capabilities.

While AI high performers are not immune to the challenges of capturing value from AI, the results suggest that the difficulties they face reflect their relative AI maturity, while others struggle with the more foundational, strategic elements of AI adoption. Respondents at AI high performers most often point to models and tools, such as monitoring model performance in production and retraining models as needed over time, as their top challenge. By comparison, other respondents cite strategy issues, such as setting a clearly defined AI vision that is linked with business value or finding sufficient resources.

The findings offer further evidence that even high performers haven’t mastered best practices regarding AI adoption, such as machine-learning-operations (MLOps) approaches, though they are much more likely than others to do so. For example, just 35 percent of respondents at AI high performers report that where possible, their organizations assemble existing components, rather than reinvent them, but that’s a much larger share than the 19 percent of respondents from other organizations who report that practice.

Many specialized MLOps technologies and practices  may be needed to adopt some of the more transformative uses cases that gen AI applications can deliver—and do so as safely as possible. Live-model operations is one such area, where monitoring systems and setting up instant alerts to enable rapid issue resolution can keep gen AI systems in check. High performers stand out in this respect but have room to grow: one-quarter of respondents from these organizations say their entire system is monitored and equipped with instant alerts, compared with just 12 percent of other respondents.

3. AI-related talent needs shift, and AI’s workforce effects are expected to be substantial

Our latest survey results show changes in the roles that organizations are filling to support their AI ambitions. In the past year, organizations using AI most often hired data engineers, machine learning engineers, and Al data scientists—all roles that respondents commonly reported hiring in the previous survey. But a much smaller share of respondents report hiring AI-related-software engineers—the most-hired role last year—than in the previous survey (28 percent in the latest survey, down from 39 percent). Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption, with 7 percent of respondents whose organizations have adopted AI reporting those hires in the past year.

The findings suggest that hiring for AI-related roles remains a challenge but has become somewhat easier over the past year, which could reflect the spate of layoffs at technology companies from late 2022 through the first half of 2023. Smaller shares of respondents than in the previous survey report difficulty hiring for roles such as AI data scientists, data engineers, and data-visualization specialists, though responses suggest that hiring machine learning engineers and AI product owners remains as much of a challenge as in the previous year.

Looking ahead to the next three years, respondents predict that the adoption of AI will reshape many roles in the workforce. Generally, they expect more employees to be reskilled than to be separated. Nearly four in ten respondents reporting AI adoption expect more than 20 percent of their companies’ workforces will be reskilled, whereas 8 percent of respondents say the size of their workforces will decrease by more than 20 percent.

Looking specifically at gen AI’s predicted impact, service operations is the only function in which most respondents expect to see a decrease in workforce size at their organizations. This finding generally aligns with what our recent research  suggests: while the emergence of gen AI increased our estimate of the percentage of worker activities that could be automated (60 to 70 percent, up from 50 percent), this doesn’t necessarily translate into the automation of an entire role.

AI high performers are expected to conduct much higher levels of reskilling than other companies are. Respondents at these organizations are over three times more likely than others to say their organizations will reskill more than 30 percent of their workforces over the next three years as a result of AI adoption.

4. With all eyes on gen AI, AI adoption and impact remain steady

While the use of gen AI tools is spreading rapidly, the survey data doesn’t show that these newer tools are propelling organizations’ overall AI adoption. The share of organizations that have adopted AI overall remains steady, at least for the moment, with 55 percent of respondents reporting that their organizations have adopted AI. Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function, suggesting that AI use remains limited in scope. Product and service development and service operations continue to be the two business functions in which respondents most often report AI adoption, as was true in the previous four surveys. And overall, just 23 percent of respondents say at least 5 percent of their organizations’ EBIT last year was attributable to their use of AI—essentially flat with the previous survey—suggesting there is much more room to capture value.

Organizations continue to see returns in the business areas in which they are using AI, and they plan to increase investment in the years ahead. We see a majority of respondents reporting AI-related revenue increases within each business function using AI. And looking ahead, more than two-thirds expect their organizations to increase their AI investment over the next three years.

The online survey was in the field April 11 to 21, 2023, and garnered responses from 1,684 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 913 said their organizations had adopted AI in at least one function and were asked questions about their organizations’ AI use. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

The survey content and analysis were developed by Michael Chui , a partner at the McKinsey Global Institute and a partner in McKinsey’s Bay Area office, where Lareina Yee is a senior partner; Bryce Hall , an associate partner in the Washington, DC, office; and senior partners Alex Singla and Alexander Sukharevsky , global leaders of QuantumBlack, AI by McKinsey, based in the Chicago and London offices, respectively.

They wish to thank Shivani Gupta, Abhisek Jena, Begum Ortaoglu, Barr Seitz, and Li Zhang for their contributions to this work.

This article was edited by Heather Hanselman, an editor in the Atlanta office.

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