Elementary Students’ Problem-Solving and Visual Attention in a Physiological Computing Environment: A Cross-Case Study

• In Event: Sunday Roundtable Session 11:25 am
  In Roundtable Session: Engaging the Educator: Technology and Cognition Research Developed for and Led by Teachers (Table 16)

Abstract

Previous research has incorporated physiological data such as heart rate and footsteps to enrich K-12 students’ STEM and computing learning experiences. This study employs a novel physiological computing environment where elementary learners use their own real-time physiological data (i.e., muscle energy) in constructing computer programs. By synergistically integrating screen recording data, students’ think-aloud verbalizations, and eye-tracking data, this cross-case analysis provided insights into the three participants’ different strategies to approach the programming task, the challenges encountered when applying conceptual knowledge to on programming, and their visual attention during the problem-solving processes. The results also revealed that the participants consistently devoted more attention to the codes and programming area during problem-solving, with minimal attention to the program output.

Authors

• Ruohan Liu, Seattle University

• Feiya Luo, University of Alabama

• Idowu David Awoyemi, University of Alabama

• Chris S. Crawford, University of Alabama