{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T09:24:42Z","timestamp":1787217882812,"version":"build-2736575974"},"reference-count":79,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T00:00:00Z","timestamp":1787184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behav. Sci.","Behavioral Sciences"],"abstract":"<jats:p>Most research on learning emphasizes knowledge learning, yet an equally important skill is knowing when to stop. This study examined learning cessation\u2014when to disengage from further attempts once performance has stabilized\u2014and its relation to academic performance. A sample of 183 undergraduates completed three perceptual discrimination problems varying in solvability and mastery criteria. Performance curves were analyzed by measuring error rates, allowing for the measurement of performance within the learning and cessation phases. Learners demonstrated wide variability across all three problem types, persisting well beyond the point at which continued attempts offered additional value. Individual differences in cessation behavior were associated with academic outcomes, though the pattern varied by problem type and outcome measure. Efficient cessation in a solvable task predicted higher ACT scores and high school GPA, while more attempts on the unsolvable problem showed a positive association with ACT performance and university GPA. Findings highlight the educational relevance of regulation efficiency, suggesting that the ability to regulate not only how long to attempt learning but also when to cease is a critical dimension of effective learning.<\/jats:p>","DOI":"10.3390\/bs16081436","type":"journal-article","created":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T08:10:20Z","timestamp":1787213420000},"page":"1436","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Individual Differences in Learning and Cessation Predict Academic Performance"],"prefix":"10.3390","volume":"16","author":[{"given":"Ashley L.","family":"Macchione","sequence":"first","affiliation":[{"name":"Department of Psychological Sciences and Counseling, Youngstown State University, Youngstown, OH 44555, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1553-7682","authenticated-orcid":false,"given":"Jeffrey","family":"Coldren","sequence":"additional","affiliation":[{"name":"Department of Psychological Sciences and Counseling, Youngstown State University, Youngstown, OH 44555, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1037\/a0035098","article-title":"The diminishing criterion model for metacognitive regulation of time investment","volume":"143","author":"Ackerman","year":"2014","journal-title":"Journal of Experimental Psychology-General"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1002\/tl.465","article-title":"Problem-based learning","volume":"2011","author":"Allen","year":"2011","journal-title":"New Directions for Teaching and Learning"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1037\/h0033572","article-title":"Ingredients for a theory of instruction","volume":"27","author":"Atkinson","year":"1972","journal-title":"American Psychologist"},{"key":"ref_4","unstructured":"Bazerman, M. 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