{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T20:31:21Z","timestamp":1772569881391,"version":"3.50.1"},"reference-count":68,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T00:00:00Z","timestamp":1733961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deputyship of Research and Innovation, Ministry of Education in Saudi Arabia","award":["KFU241465"],"award-info":[{"award-number":["KFU241465"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Personality represents enduring patterns, providing insights into an individual\u2019s aptitude and behavior. Integrating these insights with learning tendencies shows promise in enhancing learning outcomes, optimizing returns on investment, and reducing dropout rates. This interdisciplinary study integrates techniques in advanced artificial intelligence (AI) with human psychology by analyzing data from the trades of Technical and Vocational Education and Training (TVET) education, by combining them with individual personality traits. This research aims to address dropout rates by providing personalized trade recommendations for TVET, with the goal of optimizing outcome-based personalized learning. The study leverages advanced AI techniques and data from a nationwide TVET program, including information on trades, trainees\u2019 records, and the Big Five personality traits, to develop a Personality-Aware TVET Course Recommendation System (TVET-CRS). The proposed framework demonstrates an accuracy rate of 91%, and a Cohen\u2019s Kappa score of 0.84, with an NMAE at 0.04 and an NDCG at 0.96. TVET-CRS can be effectively integrated into various aspects of the TVET cycle, including dropout prediction, career guidance, on-the-job training assessments, exam evaluations, and personalized course recommendations.<\/jats:p>","DOI":"10.3390\/info15120803","type":"journal-article","created":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T04:52:49Z","timestamp":1733979169000},"page":"803","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Personality-Aware Course Recommender System Using Deep Learning for Technical and Vocational Education and Training"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3911-4032","authenticated-orcid":false,"given":"Rana Hammad","family":"Hassan","sequence":"first","affiliation":[{"name":"School of Systems and Technology, University of Management and Technology, Lahore 54770, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0651-5297","authenticated-orcid":false,"given":"Malik Tahir","family":"Hassan","sequence":"additional","affiliation":[{"name":"School of Systems and Technology, University of Management and Technology, Lahore 54770, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3768-6045","authenticated-orcid":false,"given":"Muhammad Shujah Islam","family":"Sameem","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, Al Hofuf 31982, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2896-3162","authenticated-orcid":false,"given":"Muhammad Aasim","family":"Rafique","sequence":"additional","affiliation":[{"name":"Department of Information Systems, College of Computer Science and Information Technology, King Faisal University, Al Hofuf 31982, Saudi Arabia"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2409","DOI":"10.1007\/s10462-021-10063-7","article-title":"A survey on personality-aware recommendation systems","volume":"55","author":"Dhelim","year":"2022","journal-title":"Artif. 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