Motivating Students in Computer Science
Purpose and Research Questions
The aim of the Motivating Students in Computer Science project is to study factors that affect students motivation in undergraduate and graduate computer science courses. The projects began in Fall 2019 and have researched questions such as:
— How do students’ perceptions of the motivational climate in courses vary by gender, race/ethnicity, and major?
— How can instructors and teaching assistants create motivational climates that are inclusive and equitable for all students?
— What interventions are effective in training teaching assistants how to best help undergraduate students?
— To what extent do students’ perceptions of the motivational climate in courses predict their effort and achievement?
— How do students’ perceptions of the motivational climate vary across face-to-face, online, and hybrid courses?
— What factors predict whether students remain in or drop out of computer science courses?
News
— MUSIC for TAs: Increasing engagement within computer science, in the classroom and beyond
Theoretical Framework
Based on the research of motivation scientists, one of the basic premises of our research is that instructors can create an inclusive and equitable motivational climate by designing courses that consider students’ perceptions of the five MUSIC model components, as shown here:
Funding
Our research has been funded by the National Science Foundation and the Virginia Tech Pathways Grant Program through the Office of Undergraduate Education.
— Jones, B. D. (PI, 40%), Ellis, M. (Co-PI, 40%), Kim, I. (Co-PI, 20%). (August 1, 2023 to July 31, 2025; NSF Award #IUSE-2315574). Training Computer Science Teaching Assistants to Motivate Students. National Science Foundation, $399,592.
— Jones, B. D. (Co-PI, 50%), & Ellis, M. (Co-PI, 50%). (2022). Redesigning Computer Science Courses to Motivate and Retain Students. Pathways Grant Program, $10,000.
Findings
Our research is ongoing and we will update this page as we have more presentations and publications.
Jones, B. D., Zhu, X., Ellis, M., Fenerci, H., & Ambarkutuk, Z. (2023, August). Relationships between course motivational climate and students’ computer science beliefs and goals. Research to be presented at the annual convention of the American Psychological Association, Washington DC.
Ellis, M., Jones, B. D., Fenerci, H, & McCarty. (2023, June). Assessing the motivational climate in computer science courses to improve instruction. Research presented at the Illinois Computer Science Summer Teaching Workshop, Illinois University, virtual meeting.
Fenerci, H., Kaplan, A., Jones, B. D., & Ellis, M. (2023, April). Challenges in capturing motivational climate as a complex dynamic system: Application with the MUSIC Model of Motivation. Research presented at the annual meeting of the American Educational Research Association, Chicago, IL.
Jones, B. D., Ellis, M., Gu, F., & Fenerci, H. (2023, April). Course perceptions predict effort and achievement in an engineering course: Comparing genders, ethnicities, and majors. Paper presented at the annual meeting of the American Educational Research Association, Chicago, IL.
Ellis, M., Jones, B. D., Fenerci, H., & Gu, F. (2023, February). Differences in motivational climate in face-to-face, online, and hybrid courses. Research presented at the Conference on Higher Education Pedagogy, Blacksburg, VA.
— Students’ effort and achievement was higher in online and hybrid courses, and the motivational climate was the same or better than face-to-face courses.
— The findings indicate that with careful planning, a first-year computer science and engineering course can be successfully transitioned from face-to-face to online and then to hybrid. Students were more motivated and learned more with the new hybrid course design.
Research Team at Virginia Tech
Margaret Ellis, Brett Jones, Hande Fenerci, Inyoung Kim, Xiao, Zhu, Jenni Gallagher, Zeynep Ambarkutuk