{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T06:08:12Z","timestamp":1788761292126,"version":"build-2803163510"},"reference-count":90,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:p>The rapid development of artificial intelligence (AI) has driven the emergence of new quality productive forces, reshaping talent demands in the digital era. In response to this transformation, this study explores a comprehensive reform of the talent cultivation model in computer-related majors, deeply integrating AI technologies into the curriculum, teaching methods, and practical training. Grounded in the \u201cnew engineering\u201d educational philosophy, the proposed model emphasizes interdisciplinary integration, personalized learning, and collaborative education, aligning with the education, science, and talent strategy outlined in the 20th National Congress of the Communist Party of China. This strategy highlights the importance of using education to drive technological innovation and cultivate high-quality talent with innovative thinking and practical skills. The reform framework includes course restructuring, smart teaching integration, interdisciplinary collaboration, practice-oriented learning enhancement, and a comprehensive evaluation system. This model uses the comprehensive evaluation system to systematically assess students\u2019 technical proficiency, innovation awareness, and practical problem-solving skills, providing data-driven insights to support educational reform and optimize teaching strategies. The reform framework has been phased in across four undergraduate programs, aiming to establish a replicable and scalable talent cultivation model under the paradigm of AI-driven educational transformation. Preliminary results show significant improvements in students\u2019 technical capabilities, innovation capacity, and readiness to solve real-world challenges.<\/jats:p>","DOI":"10.3389\/fpsyg.2026.1790916","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T05:33:15Z","timestamp":1788759195000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["AI-driven educational reform: enhancing talent cultivation in computer-related majors for the digital era"],"prefix":"10.3389","volume":"17","author":[{"given":"Jun","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Shenyang University of Chemical Technology","place":["Shenyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengfei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Shenyang University of Chemical Technology","place":["Shenyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,7]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.2196\/48291","article-title":"Large language models in medical education: opportunities, challenges, and future directions (preprint)","author":"Abd-Alrazaq","year":"2023","journal-title":"JMIR Med. 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