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Artificial Intelligence-Based System for Detecting Attention Levels in Students
Published on: December 15, 2023
Evaluating University Student Classroom Engagement, Reflective Expression, and Prosocial Intention Using Behavioral
1Nanchang Institute of Technology; hushuoli2025@163.com.
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To address the need for multidimensional assessments of student involvement beyond traditional metrics, this protocol describes a structured approach for evaluating classroom engagement, reflective expression, learning analytics activity, and prosocial intention in undergraduate courses. The protocol combines interval-based behavioral observation, weekly structured reflective writing, de-identified learning-management-system records, and a pre/post prosocial-intention questionnaire. The revised procedures provide a reproducible behavioral coding model, reflective-expression rubric with score examples, software and data-management steps, and explicit troubleshooting guidance for observer disagreement, missing platform records, low reflection submission rates, poor camera visibility, participant attrition, and inconsistent prerequisite knowledge. This protocol should be used when researchers need a low-intrusion, reproducible way to combine live classroom behavior, student self-interpretation, and routine learning management system (LMS) activity during undergraduate instruction. It is less suitable for fully asynchronous courses without observable interaction, settings that prohibit independent observation or record linkage, or studies requiring biometric or emotion-recognition inference. The representative results are reported from the implemented empirical application after verified ethics approval, de-identification of course records, and repository preparation.
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