Stress Analytics

Being new to STEM can be stressful. While newcomer stress can resolve itself over time, it can also foreshadow issues like a lack of a sense of belonging, loss of interest, and ultimately intent to leave the field. While human instructors are seen as responsible for creating caring cultures in the classroom, this is not always feasible in higher education, as they must often deal with large class sizes, competing responsibilities, and a lack of indicators to signal and intervene on the student experience. Adding urgency to the matter, prior work suggests that silent struggles can be more common and detrimental to race and gender minorities in STEM. How might we scalably track and support emotional struggles in STEM classrooms? Can we support affect with targeted use of data, complementing its current use for pushing performance and accountability? This project addresses these questions through a mix of experimental and design research that focuses on novice affect in STEM.

Publications

• Sung., G., & Schneider, B. (2023). Proposing the Multimodal Learning Analytics Platform for Social Emotional Learning. In Proceedings of the 17th International Conference of the Learning Sciences (pp. 2122-2123). International Society of the Learning Sciences.
• Sung, G., Hassan, J., & Schneider, B. (2022). Towards Automated Tracking of Affect: Testing the Use of Continuous Self-Reports and Multimodal Metrics. International Conference of the Learning Sciences. Sung, G., Bhinder, H., Feng, D., & Schneider, B. (2023). Stressed or engaged? Addressing the Mixed Significance of Physiological Activity during Constructivist Learning. Computers & Education, 199, 104784.