Previous research has incorporated physiological data such as heart rate and footsteps to enrich K-12 students’ STEM and computing learning experiences. This qualitative study piloted a series of lessons leveraging a novel physiological computing environment with a small group of fifth-grade girls (n=5). The purpose of this study was to understand (1) how the physiological computing lesson activities promoted changes in the students’ conceptual understanding of conditional logic and variables and their diverse perspectives in computing (RQ1), and (2) how the students approached problem-solving and what their visual attention looked like during physiological computing (RQ2). For RQ 1, we collected and analyzed all five students’ conceptual drawings, computing artifacts, and recorded classroom conversations to reveal students’ conceptual understanding and perspectives. For RQ 2, we selected 3 cases where the girls used their own real-time physiological data (i.e., muscle energy) in constructing computer programs. We synergistically integrated their screen recordings, think-aloud verbalizations, and eye-tracking quantitative metrics data with visualizations to present cross-case findings on their visual attention during problem-solving.