The Disconnect Between Science and Practice: Concerns of Graduate Students

Sophie Kay, Georgia Institute of Technology, & Md Allama Ikbal Sijan, Montclair State University

Many enter the field of industrial-organizational (I-O) psychology in order to drive change and improve the workplace for employees. However, many students feel that there is a major disconnect between their day-to-day activities as a master’s or PhD student (e.g., reading research papers, collecting data, writing journal articles) and the actual implementation of theories into practice. The divide between science and practice in I-O has long been noted and discussed (e.g., Cascio & Aguinis, 2008; Dunnette, 1990; Hakel, 1994; Rynes, 2012). This prominent challenge is highly apparent to us as a current I-O PhD student (Sijan) and a recent I-O PhD graduate currently working in industry (Sophie). In this article, we focus on the graduate student perspective on this divide. We briefly discuss the concerns of students and share ideas on how to bridge the gap between these two areas.

Graduate Student Concerns

Due to the extensive divide between science and practice, many I-O PhD students often find themselves ill prepared, or at least anxious as to their readiness, as they graduate and transition into industry. Considering the current global economic landscape and the competitive job market, it becomes imperative that I-O programs equip their students with the essential experiences and KSAOs necessary to not only prepare them for the industry but also empower them to become valuable contributors capable of driving meaningful organizational change.

Sijan’s Perspective as a Current PhD Student

As a current second-year PhD student, my first concern revolves around the balance between theory and practical knowledge in I-O education. In the classroom setting, I often find myself immersed in theories, needing to digest a significant number of scientific, peer-reviewed articles. It's unclear how much of this extensive information we are expected to retain. It seems fairly common that program curricula do not differentiate between the most crucial concepts and the less relevant or outdated ones, which could lead students to investing a lot of time in information that may not be critical for industry roles. For example, there are a large number of leadership theories in current literature, each offering a different perspective. It's challenging to figure out which of these theories are actually applicable for improving leadership in practical, real-world situations.

In my statistics class, I am learning complex concepts like multilevel modeling, Bayesian statistics, and machine learning. Although these are undoubtedly valuable, I’ve heard some industry professionals suggest that the basics, like correlation, t-tests, and ANOVA, are what truly matter in daily work. Yet, job postings often request experience with more advanced statistics. I have also heard from practitioners that the “cleaner” datasets we practice with in an academic setting tend to differ (by a large margin) from messier real-world data. I often worry that my experience with academic datasets will not prepare me well for an industry role. Additionally, many positions require several years of experience, leaving me to wonder if I'm underqualified to secure my job of interest immediately after completing my PhD program.

Finally, I am worried that there are so many potential career paths within this field that I may not discover my true passion until I'm actually working in the industry. Although I have a general idea about my career interests, I often tend to question it. I am also grappling with the question of whether to become a generalist or specialize in a specific area. Furthermore, I am also concerned that I-O psychology might still not be widely recognized in the business world, potentially putting us at a disadvantage when competing for positions against MBA graduates or data scientists.

Sophie’s Perspective as a Recent Graduate

During my own PhD program, I had been undecided on academia versus industry. I was lucky enough to intern at two different Fortune 50 organizations (State Farm and Facebook) during the summers following my third and fourth years of graduate school. These opportunities led me to my current role at Meta (formerly Facebook) on their People Analytics team. Although I only completed my PhD 4.5 years ago, I recently realized I have a useful perspective around the transition from academia to industry. More specifically, I began mentoring a group of graduate students through my involvement in Asians in I/O earlier this year. After a few months into mentoring and a handful of LinkedIn messages from strangers asking to chat one on one, I realized a lot of students had similar questions and concerns. I decided to post on LinkedIn to field questions in an attempt to consolidate questions and post answers publicly. The response was overwhelming. I received almost 300 reactions to my post, over 100 new connection requests, and dozens of comments and direct messages with questions and requests to chat.

Through these interactions, it became clear that there is a gap in self-efficacy in the transition between academia and industry. There are largely three common themes to my conversations: (a) what my daily life and career development look like as a practitioner, (b) what skills to focus on to get jobs, (c) clarity on whether they are getting the training they need for industry. Many are worried about their skill sets and doubt their abilities because they do not know much about industry jobs. Honestly, I felt the same when I started my first internship. I believe there is a lot we can do to better prepare and support graduate students while simultaneously building more and stronger connections between academics and practitioners.

Bridging the Gap for Students

Of the aforementioned articles that have written about the scientist–practitioner gap, all have discussed potential solutions (e.g., Aguinis & Cascio, 2008; Cascio & Aguinis, 2008; Rynes, 2012). However, none are focused solely on the student perspective. We propose a handful of ideas at different levels (student, professor, program, and SIOP) to reduce the scientist–practitioner gap with a focus on graduate students.

Student Level

Internships to acquire real work experience are the most obvious path for students to pursue to prepare themselves for industry jobs postgraduation. Although summer internships offer valuable insights, their brevity limits the depth of experience gained. Encouraging part-time, year-long internships within the I-O curriculum would undoubtedly enhance students' readiness for the industry. This would be particularly useful for students who are unsure whether they want to go academic or applied at the time of applying for graduate school.

Furthermore, the establishment of in-house consulting clubs or groups led by students (and supervised by faculty) could prove highly beneficial. These student-driven organizations can offer students the opportunity to gain leadership experience, tackle real-world problems informed by their classroom learning, and refine their communication skills through interaction with various stakeholders. However, it's crucial to emphasize that building and sustaining such clubs may require university support and resources. Notably, institutions like Columbia University and Montclair State University (and others) have successfully established such clubs within their I-O programs, setting examples for other universities to follow.

Additionally, universities can explore mentorship programs, where students are paired with alumni who can provide guidance and offer mock projects that simulate real-world scenarios without breaching any organizational confidentiality. Although this concept may seem ambitious, the establishment of such systems would undeniably contribute to the growth of the I-O students by bridging the gap between academia and industry.

Professor Level

We believe it is essential for individual classes to incorporate a practical element. For instance, final projects could involve crafting real-world solutions for organizations, such as designing selection systems, assessing whether adverse impact has occurred, or devising performance management strategies. Although some I-O professors undoubtably do this already (e.g., Motahari et al., 2023), they may not require students to deliver presentations or create documents for nontechnical audiences. This is an aspect we believe professors should consider, potentially even inviting industry-based colleagues to help review and provide feedback.

Program Level

Undoubtedly, I-O programs could benefit from hiring faculty members or adjuncts with applied experience. At a smaller scale, departments, programs, or individual professors could invite practitioners as guest lecturers or colloquia speakers and have them lead workshops on their expertise, as done by organizations like METRO (New York Metropolitan Association of Applied Psychology). To address logistical challenges for students, localizing such events and integrating them into the program curriculum will maximize benefits.

Additionally, we believe I-O psychology programs should actively encourage student involvement in volunteer opportunities. This will not only enhance the influence of the I-O community on society but also will offer valuable training for aspiring I-O psychologists (Albritton et al., 2023). Collaborating with organizations like Volunteer Program Assessment (VPA), which provides volunteer programs for organizational effectiveness in partnership with eight universities, can be a strategic way for I-O programs to foster such engagement (Albritton et al., 2023).

SIOP at Large: Sophie’s “Pie in the Sky” Idea

One opportunity I identified as a PhD student was the need for students to acquire data for their research and the number of organizations that could benefit from I-O. It seemed like a win–win situation that could truly benefit both parties! I always wondered if students might be able to obtain applied data for their master’s theses and dissertations by connecting with local organizations, ideally with a stipend. A few of my classmates were able to collect data or use archival employee data through internships, but this was rare. Further, some professors warned against this due to the additional hoops needed to jump through and potential lack of control (e.g., limits to survey items or length).

My “pie in the sky” vision is that a central group of I-O psychologists, perhaps through SIOP or the SIOP Foundation, build relationships with nonprofits and small businesses that cannot afford I-O consulting but are open to data collection within their organization. Students conduct the applied research and use the data for master’s theses, dissertations, and other academic pursuits. As mentioned in Tippins et al. (2023), nonprofits and small businesses may be more inclined to share the details of successful programs compared to organizations that see these programs as a competitive edge. This said, students and their advisors could publish the findings, further advancing I-O as a science. Much of the research done within organizations to date remains concealed due to competition, legal risk, and concerns of public reputation, which is arguably limiting advancement within our field.

Although academic faculty can certainly provide some guidance to students doing this work, they may not have the full skillset to conduct applied research or implement changes in an organization. Experienced practitioners are the ideal candidate to mentor students from a skillset perspective. Although working practitioners have limited time, Tippins et al. (2023) highlights that there are I-Os willing to volunteer their time to support charitable organizations. This would be a fantastic learning opportunity for students interested in industry, producing datasets from a variety of workplaces that would help advance science while benefiting organizations at a low cost. Getting this initiative underway and eventually to scale would be challenging, but I believe it would be beneficial for students, their professors, mentors, small businesses and nonprofits, and I-O as a science.

A related endeavor that I have been involved in outside the I-O space is the PSEG Institute for Sustainability Studies’ Green Teams program. This program provides training and guidance for teams of five students to address sustainability issues identified by host corporations, organizations, nonprofits, municipalities, and community groups over a period of 10 weeks (see Kay et al., 2018 for further detail). This partnership between academia and business provides a valuable opportunity for students to learn hands-on in a business setting while under the supervision of a leadership team. The collaboration with organizations allows students to learn firsthand how businesses function, gain experience in an applied context, and develop a variety of skills such as teamwork, communication, presenting, and writing. I believe a similar model at the graduate level could be adopted by SIOP, perhaps first as a summer pilot and later into longer term projects.

We recognize that equipping I-O students with practical, real-world experience is undeniably challenging. However, we believe the benefits would extend not only to the students themselves but also to their professors, practitioners, and the broader I-O community. We hope this article was thought-provoking for students, professors, and practitioners. If you have comments, ideas, concerns, or respectful disagreements, feel free to send us a message on LinkedIn (linkedin.com/in/sophiekay; linkedin.com/in/allamaikbalsijan/) or email (drsophiekay@gmail.com; sijana1@montclair.edu). 

References

Aguinis, H., & Cascio, W. F. (2008). Narrowing the science–practice divide: A call to action. The Industrial-Organizational Psychologist, 46(2), 27-34.

Albritton, B. H., Meyer, K. A., Holladay-Sandidge, H. D., Zhou, S., Woznyj, H. M., & Rogelberg, S. G. (2023). Enhancing graduate student education through meaningful volunteer efforts. Industrial and Organizational Psychology, 16(4), 462-467.

Cascio, W. F., & Aguinis, H. (2008). Research in industrial and organizational psychology from 1963 to 2007: Changes, choices, and trends. Journal of Applied Psychology, 93(5), 1062-1081.

Dunnette, M. D. (1990). Blending the science and practice of industrial and organizational psychology: Where are we and where are we going? In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed., Vol. 1, pp. 1–27). Consulting Psychologists Press.

Hakel, M. D. (1994). The past, present, and future of OB applications by consulting academicians. In J. Greenberg (Ed.), Organizational behavior: The state of the science (pp. 275–287). Erlbaum.

Kay, M. J., Kay, S. A., & Tuinanga, A. (2018). Green teams: A collaborative training model. Journal of Cleaner Production, 176, 909-919.

Motahari, S., LeNoble, C. A., Kateli, M., & Lipman, K. (2023). Engaging graduate students in nonprofit consulting experiences. Industrial and Organizational Psychology: Perspectives on Science and Practice. 16(4), 473-478. doi:10.1017/iop.2023.68

Rynes, S. L. (2012). The research-practice gap in industrial-organizational psychology and related fields: Challenges and potential solutions. In S. W. J. Kozlowski (Ed.), Oxford handbook of industrial and organizational psychology (Vol. 1, pp. 409–452). Oxford University Press.

Tippins, N., Hakel, M., Grabow, K., Kolmstetter, E., Moses, J., Oliver, D., & Scontrino, P. (2023). Industrial-organizational psychologists and volunteer work. Industrial and Organizational Psychology, 16(4), 421-432. doi:10.1017/iop.2023.70