{"ID":2875069,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.03392","arxiv_id":"2509.03392","title":"More AI Assistance Reduces Cognitive Engagement: Examining the AI Assistance Dilemma in AI-Supported Note-Taking","abstract":"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.","short_abstract":"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 comprehens...","url_abs":"https://arxiv.org/abs/2509.03392","url_pdf":"https://arxiv.org/pdf/2509.03392v1","authors":"[\"Xinyue Chen\",\"Kunlin Ruan\",\"Kexin Phyllis Ju\",\"Nathan Yap\",\"Xu Wang\"]","published":"2025-09-03T15:15:39Z","proceeding":"cs.HC","tasks":"[\"cs.HC\"]","methods":"[]","has_code":false}