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Interact."],"published-print":{"date-parts":[[2025,10,18]]},"abstract":"<jats:p>As AI tools become increasingly integrated into cognitively demanding tasks, like note-taking, questions remain about whether they enhance or compromise 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.<\/jats:p>","DOI":"10.1145\/3757632","type":"journal-article","created":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T16:59:10Z","timestamp":1760633950000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["More AI Assistance Reduces Cognitive Engagement: Examining the AI Assistance Dilemma in AI-Supported Note-Taking"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0774-223X","authenticated-orcid":false,"given":"Xinyue","family":"Chen","sequence":"first","affiliation":[{"name":"University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9457-5467","authenticated-orcid":false,"given":"Kunlin","family":"Ruan","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8272-6552","authenticated-orcid":false,"given":"Kexin Phyllis","family":"Ju","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7760-1496","authenticated-orcid":false,"given":"Nathan","family":"Yap","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5551-0815","authenticated-orcid":false,"given":"Xu","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,10,16]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Design, implementation and evaluation of an LLM-powered meeting recap system. arXiv preprint arXiv:2307.15793","author":"Asthana Sumit","year":"2023","unstructured":"Sumit Asthana, Sagih Hilleli, Pengcheng He, and Aaron Halfaker. 2023. 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