Proactive AI Support and Student Learning: A Retrospective Record of a Randomized Study
Year: 2026
Type: preprint
Abstract: This registration documents a completed nine-week study of proactive versus student-initiated AI learning support. Within 18 university classes, 480 undergraduate students were assigned to four conditions in a 2 × 2 design combining support initiation (proactive or student-initiated) with EEG-summary availability (available or unavailable). The study examined self-regulated learning, course-task performance, performance when AI support was temporarily withdrawn, and transfer to new tasks completed without AI. It also examined daily learning records, AI interaction events, EEG-derived features, and a later evaluative-judgement assessment. This record describes the study design, outcome definitions, and analyses reported in the manuscript. It was prepared after data collection and analysis; it is not a prospective preregistration.
Source: OSF Preprints (OSF Preprints)
Author: Yindong Dong
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7222551297
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