{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T17:57:15Z","timestamp":1784570235945,"version":"3.55.0"},"reference-count":42,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Educ"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Medical school admission pathways are designed to select suitable applicants, with different approaches potentially impacting students\u2019 learning behaviors and performance.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to compare students\u2019 self-regulated learning (SRL) strategies, assessment engagement statistics (AES), nongrading evaluation (Outstanding [\u201cO\u201d]\/Satisfactory [\u201cS\u201d]\/Unsatisfactory [\u201cU\u201d]) preferences, and academic performance across admission pathways, and analyze correlations and linear regression models among summative scores, AES, and course learning outcome (CLO) scores.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n This mixed methods retrospective observational and cross-sectional survey study used census sampling with selection criteria of all enrolled first-year medical students in 2021 (N=319) across 4 admission pathways: academic (n=23), quota (n=6), test (n=261), and rural (n=29). Demographics included age (19\u201024 years) and sex (167\/319, 52.4% male). AES, CLO scores, and summative scores were obtained from institutional databases. Two system-embedded institutional questionnaires assessed SRL strategies (316\/319, 99.1% response rate) and \u201cO\u201d\/\u201cS\u201d\/\u201cU\u201d preferences (299\/319, 93.7% response rate). Outcome measures included SRL strategies, AES, \u201cO\u201d\/\u201cS\u201d\/\u201cU\u201d preferences, CLO scores, and summative scores. Statistical significance was set at\n P<\/jats:italic>\n <.05.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n When compared among pathways, using one-way ANOVA with Fisher least significant difference post hoc tests, the academic group reported significantly higher mean (with 95% CI) goal setting (4.35, 4.07\u20104.63), enthusiasm (4.43, 4.18\u20104.69), and lower stress during study (2.64, 2.15\u20103.12), while the rural group showed higher pre-examination stress (4.38, 4.10\u20104.66) (all\n P<\/jats:italic>\n <.05). Most academic (14\/22, 63.6%), quota (5\/6, 83.3%), and test students (132\/243, 54.3%) preferred \u201cO\u201d\/ \u201cS\u201d\/\u201cU,\u201d while the rural students preferred \u201cS\u201d\/\u201cU\u201d (13\/28, 46.4%). The academic group showed significantly higher CLO and summative scores but fewer total and intentional attempts and instances of first-pass and highest scoring attempts (all\n P<\/jats:italic>\n <.05), whereas the rural group showed significantly lower CLO and summative scores and higher instances of first-pass and highest scoring attempts (all\n P<\/jats:italic>\n <.05). For correlation analyses, using Pearson correlation coefficient, summative scores were positively correlated with CLO scores and number of passings and negatively with first-pass attempts. For multiple linear regression analyses, summative scores were positively influenced by number of passings for each CLO and CLO scores and negatively influenced by instances of first-pass attempts and highest scoring attempts. Overall, the academic group demonstrated higher academic performance and fewer attempts and instances of first-pass and highest scoring attempts, while the rural group showed lower academic performance, requiring more attempts for first-passing CLOs.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Admission pathways significantly influence students\u2019 SRL strategies, AES, evaluation preferences, and academic performance. This study is innovative in analyzing these interconnected components within a single cohort, unlike prior research that examined them separately. By integrating assessment-engagement analytics with SRL data, it offers equity-oriented evidence on how admission systems shape learning behaviors and academic trajectories. These findings provide actionable insights for inclusive curriculum design and early identification of at-risk students. Real-world implications include targeted mentoring, SRL-focused interventions, and assessment reforms balancing academic rigor with psychological safety.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/68636","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T20:37:15Z","timestamp":1770064635000},"page":"e68636-e68636","source":"Crossref","is-referenced-by-count":3,"title":["Influence of Admission Pathways on Learning Strategies, Assessment Engagement, and Academic Performance Among First-Year Medical Students: Mixed Methods Retrospective Observational and Cross-Sectional Survey Study"],"prefix":"10.2196","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1065-7762","authenticated-orcid":false,"given":"Issarawan","family":"Keadkraichaiwat","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8790-1300","authenticated-orcid":false,"given":"Chantacha","family":"Sitticharoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8371-8450","authenticated-orcid":false,"given":"Punyapat","family":"Maprapho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0759-9242","authenticated-orcid":false,"given":"Nisa","family":"Jangboon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6088-1056","authenticated-orcid":false,"given":"Nadda","family":"Wannarat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,2,2]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","DOI":"10.1186\/s12909-023-04251-y","article-title":"Admission criteria and academic performance in medical school","volume":"23","author":"Tamimi","journal-title":"BMC Med Educ"},{"issue":"8","key":"R2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2017-017276","article-title":"Examining the predictors of academic outcomes for indigenous M\u0101ori, Pacific and rural students admitted into medicine via two equity pathways: a retrospective observational study at the University of Auckland, Aotearoa New Zealand","volume":"7","author":"Curtis","journal-title":"BMJ Open"},{"issue":"1","key":"R3","doi-asserted-by":"publisher","DOI":"10.1186\/s12909-022-03768-y","article-title":"Prior degree and academic performance in medical school: evidence for prioritising health students and moving away from a bio-medical science-focused entry stream","volume":"22","author":"Aston-Mourney","journal-title":"BMC Med Educ"},{"key":"R4","unstructured":"TCAS64 round 3 application guide. version 1. 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