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More AI Assistance Reduces Cognitive Engagement: Examining the AI Assistance Dilemma in AI-Supported Note-Taking

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arxiv 2509.03392 v1 pith:4IAWZRB3 submitted 2025-09-03 cs.HC

More AI Assistance Reduces Cognitive Engagement: Examining the AI Assistance Dilemma in AI-Supported Note-Taking

classification cs.HC
keywords assistancecognitiveengagementautomatednote-takingdesigningdilemmaintermediate
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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As AI tools become increasingly embedded in cognitively demanding tasks such as note-taking, questions remain about whether they enhance or undermine cognitive engagement. This paper examines the "AI Assistance Dilemma" in note-taking, investigating how varying levels of AI support affect user engagement and comprehension. In a within-subject experiment, we asked participants (N=30) to take notes during lecture videos under three conditions: Automated AI (high assistance with structured notes), Intermediate AI (moderate assistance with real-time summary, and Minimal AI (low assistance with transcript). Results reveal that Intermediate AI yields the highest post-test scores and Automated AI the lowest. Participants, however, preferred the automated setup due to its perceived ease of use and lower cognitive effort, suggesting a discrepancy between preferred convenience and cognitive benefits. Our study provides insights into designing AI assistance that preserves cognitive engagement, offering implications for designing moderate AI support in cognitive tasks.

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Cited by 1 Pith paper

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  1. Hint-Writing with Deferred AI Assistance: Fostering Critical Engagement in Data Science Education

    cs.HC 2026-04 unverdicted novelty 4.0

    In a randomized experiment with 97 graduate students, deferred AI assistance produced the highest-quality hints and helped students spot more code mistakes than independent writing or immediate AI help.