An Empirical Study of Adaptive Feedback to Enhance Cognitive Ability in Programming Learning among College Students: A Perspective Based on Multimodal Data Analysis.

This article investigates the impact of an adaptive feedback strategy on enhancing the cognitive ability of first-year university students learning introductory programming. The study employed a quasi-experimental design with 65 students divided into experimental and control groups, where the experimental group received personalized adaptive feedback combining computer-automated grading and teacher manual correction, while the control group received traditional non-differential feedback. Using multimodal data—including cognitive ability tests (memory, reasoning, attention), programming examinations, programming self-efficacy questionnaires, and electroencephalogram (EEG) measurements focusing on the P300 component—the findings indicate that adaptive feedback significantly improves learners' cognitive ability, academic performance, cognitive processing speed and accuracy, and programming self-efficacy. The study concludes that adaptive feedback is an effective method for fostering cognitive development and self-efficacy in programming education, though it notes limitations related to generalizability beyond introductory programming and calls for further research on specific feedback types and learner characteristics.