Self-Efficacy, Cognitive Load, and Emotional Reactions in Collaborative Algorithms Labs - A Case Study

While previous research has investigated psychological factors in introductory programming courses, only little is known about their impact in algorithms courses. Similarly, despite the importance of collaborative problem solving in both academic and non-academic settings, only a small number of studies reports on group work in domains other than programming. In our case study, we focused on the labs of an introductory algorithms course. We measured the cognitive load of the lab assignments as well as the students' emotional reaction to them. We connect these observations to self-efficacy, performance, psychological traits, and help-seeking behavior as well as to the insights gained from a comprehensive set of follow-up interviews. Even though our study is a small-scale study, the results from applying both quantitative and qualitative methods frame directions for both pedagogic interventions and further (revalidation) studies related to the connection of non-cognitive factors, learning experiences, and performance in collaborative algorithms labs.

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