By Rebecca Glazier and Matthew Pietryka

This post originally appeared on the Active Learning in Political Science Blog. You can view the original post here: https://activelearningps.com/2023/05/08/engaging-students-through-collaborative-research-projects/.

Many professors are struggling to engage their students, who are often disengaged and burned out. To address these issues and improve student retention, universities are increasingly turning to edtech solutions or big data—everything from predictive analytics to chatbots in discussion boards. These remedies tend to be far removed from students’ daily lives. In contrast, as professors, we are with students in the classroom every day. And this experience often prepares us to know best how to engage our students.

Dr. Rebecca Glazier

In a new, open-access article we just published in Education Sciences, “Learning through Collaborative Data Projects: Engaging Students and Building Rapport,” we illustrate how faculty can engage students through collaborative data projects. Rather than relying on top-down university solutions, faculty can use the content of their own courses to involve students in collaborative projects that build rapport and make them feel included and engaged in the course. We see these collaborative data projects as another kind of active learning—getting students thinking outside of the textbook and involved in contributing to a project that is bigger than themselves.

We used data from more than 120 students over two semesters and our results suggest that most students find these collaborative data projects more enjoyable than typical college assignments. And students report the projects make them feel the professor is invested in their learning.

Dr. Matthew Pietryka

The article we wrote detailing these projects is open access (you can check it out here: https://www.mdpi.com/2227-7102/12/12/897). It provides advice on implementing these projects as well as the R code used to create individualized reports for students participating in the collaborative data projects. The individualized reports help develop rapport between the professor and each student. And this programmatic approach allows professors to scale up these reports to accommodate classes with hundreds of students. Building rapport and doing active learning is something considered possible only in smaller classes, but our approach demonstrates how it can be done in large classes as well—with significantly positive results.

At a time when many faculty members are struggling to engage students, we can take matters into our own hands by designing projects for our classes that draw students in and build rapport with them. It doesn’t take expensive edtech solutions or top-down directives. Mostly, it takes thoughtful pedagogy and prioritizing student connection.

If you want to know more, or you just like podcasts, here is a recent episode on the Teaching in Higher Ed Podcast on this research: https://teachinginhighered.com/podcast/engaging-students-through-collaborative-research-projects/

Rebecca A. Glazier is a political science professor in the School of Public Affairs at the University of Arkansas at Little Rock. She studies the scholarship of teaching and learning and is passionate about improving the quality of online education. Dr. Glazier is the author of “Connecting in the Online Classroom: Building Rapport between Teachers and Students” (Johns Hopkins University Press, 2021). She is also the Director of the Little Rock Congregations Study, a longitudinal, community-based research project on religion and community engagement.  More information about her research is available on her website: http://www.rebeccaglazier.net/. She can be reached via email at rebecca.glazier@gmail.com.

Matthew Pietryka is an associate professor in the Florida State University Political Science department. His research examines how individuals’ political attitudes and voting behavior are influenced by the people around them. He teaches courses on political behavior, political psychology, media and politics, social network analysis, research methods, and R programming.