{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T11:41:40Z","timestamp":1782301300428,"version":"3.54.5"},"reference-count":22,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"General Royalty System of Colombia (SGR\u2014Sistema General de Regal\u00edas)","award":["BPIN-2021000100186"],"award-info":[{"award-number":["BPIN-2021000100186"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MTI"],"abstract":"<jats:p>The rapid expansion of virtual education has highlighted both its opportunities and limitations. Conventional virtual learning environments tend to lack flexibility, often applying standardized methods that do not account for individual learning differences. In contrast, Artificial Intelligence (AI) empowers the creation of customized educational experiences that address specific student needs. Such personalization is essential to mitigate educational inequalities, particularly in areas with limited infrastructure, scarce access to trained educators, and varying levels of digital literacy. This study explores the role of AI in advancing virtual education, with particular emphasis on supporting differentiated learning. It begins by selecting an appropriate pedagogical model to guide personalization strategies and proceeds to investigate the application of AI techniques across three key areas: the characterization of educational resources, the detection of learning styles, and the recommendation of tailored content. The primary contribution of this research is the development of a scalable framework that can be adapted to a variety of educational contexts, with the goal of enhancing the effectiveness and personalization of virtual learning environments through AI.<\/jats:p>","DOI":"10.3390\/mti9070069","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T08:22:07Z","timestamp":1751530927000},"page":"69","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Innovating Personalized Learning in Virtual Education Through AI"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1294-137X","authenticated-orcid":false,"given":"Luis","family":"Fletscher","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, Universidad de Antioquia, Medell\u00edn 050010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4867-4352","authenticated-orcid":false,"given":"Jhon","family":"Mercado","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Universidad de Antioquia, Medell\u00edn 050010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alvaro","family":"G\u00f3mez","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Universidad de Antioquia, Medell\u00edn 050010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos","family":"Mendoza-Cardenas","sequence":"additional","affiliation":[{"name":"Twitch Interactive Inc., San Francisco, CA 94104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.1007\/s10648-021-09615-8","article-title":"A systematic review of research on personalized learning: Personalized by whom, to what, how, and for what purpose (s)?","volume":"33","author":"Bernacki","year":"2021","journal-title":"Educ. Psychol. Rev."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Fu, Y., Weng, Z., and Wang, J. (2024). Examining AI Use in Educational Contexts: A Scoping Meta-Review and Bibliometric Analysis. Int. J. Artif. Intell. Educ.","DOI":"10.1007\/s40593-024-00442-w"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"7519","DOI":"10.1109\/ACCESS.2021.3049446","article-title":"Predicting at-risk students at different percentages of course length for early intervention using machine learning models","volume":"9","author":"Adnan","year":"2021","journal-title":"IEEE Access"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"103676","DOI":"10.1016\/j.compedu.2019.103676","article-title":"An overview and comparison of supervised data mining techniques for student exam performance prediction","volume":"143","author":"Tomasevic","year":"2020","journal-title":"Comput. Educ."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zerkouk, M., Mihoubi, M., Chikhaoui, B., and Wang, S. (2025). Predicting Online Education Dropout: A new Machine Learning Model based on Sentiment Analysis, Socio-demographic, and Behavioral Data. Int. J. Artif. Intell. Educ.","DOI":"10.1007\/s40593-025-00472-y"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"75264","DOI":"10.1109\/ACCESS.2020.2988510","article-title":"Artificial Intelligence in Education: A Review","volume":"8","author":"Chen","year":"2020","journal-title":"IEEE Access"},{"key":"ref_7","first-page":"100017","article-title":"An Integrative Debate on Learning Styles and the Learning Process","volume":"2","author":"Dantas","year":"2020","journal-title":"Soc. Sci. Humanit. Open"},{"key":"ref_8","unstructured":"Fleming, N., and Baume, D. (2006). Learning Styles Again: Varking Up the Right Tree!, Educational Developments, SEDA Ltd."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"193","DOI":"10.5465\/amle.2005.17268566","article-title":"Learning Styles and Learning Spaces: Enhancing Experiential Learning in Higher Education Experience-Based Learning Systems","volume":"4","author":"Kolb","year":"2005","journal-title":"Acad. Manag. Learn. Educ."},{"key":"ref_10","first-page":"103","article-title":"Honey-Alonso Learning Styles Questionnaire: An Analysis of its Psychometric Properties in College Students","volume":"10","author":"Freiberg","year":"2012","journal-title":"Summa Psicol\u00f3gica Ust."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/1468-2389.00099","article-title":"The Dimensionality of Honey and Mumford\u2019s Learning Styles Questionnaire","volume":"7","author":"Swailes","year":"1999","journal-title":"Int. J. Sel. Assess."},{"key":"ref_12","unstructured":"Coffield, F., Moseley, D., Hall, E., and Ecclestone, K. (2004). Learning Styles and Pedagogy in Post-16 Learning: A Systematic and Critical Review, Learning and Skills Research Centre."},{"key":"ref_13","unstructured":"Felder, R.M. (2025, June 26). Learning and Teaching Styles in Engineering Education. Available online: http:\/\/www.ncsu.edu\/felder-public\/ILSpage.html."},{"key":"ref_14","first-page":"73","article-title":"A framework for assessing lmss e-courses content type compatibility with learning styles dimensions","volume":"16","author":"Kouis","year":"2020","journal-title":"J. E-Learn. Knowl. Soc."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s11423-018-9634-6","article-title":"Use of Felder and Silverman learning style model for online course design","volume":"67","author":"Aldraiweesh","year":"2019","journal-title":"Educ. Technol. Res. Dev."},{"key":"ref_16","first-page":"101","article-title":"Smart learning using personalised recommendations in web-based learning systems using artificial bee colony algorithm to improve learning performance","volume":"16","author":"Venkatesh","year":"2020","journal-title":"Electron. Gov. Int. J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"94","DOI":"10.12962\/j20882033.v33i2.13665","article-title":"Student behaviour analysis to detect learning styles using decision tree, naive bayes, and k-nearest neighbor method in moodle learning management system","volume":"33","author":"Sianturi","year":"2022","journal-title":"IPTEK J. Technol. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"100003","DOI":"10.1016\/j.caeai.2020.100003","article-title":"A fuzzy expert system-based adaptive learning approach to improving students\u2019 learning performances by considering affective and cognitive factors","volume":"1","author":"Hwang","year":"2020","journal-title":"Comput. Educ. Artif. Intell."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1007\/s10639-018-9788-1","article-title":"Rule based adaptive user interface for adaptive e-learning system","volume":"24","author":"Kolekar","year":"2019","journal-title":"Educ. Inf. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.future.2017.02.049","article-title":"A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining","volume":"72","author":"Tarus","year":"2017","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_21","unstructured":"Moodle Docs (2025, April 05). Database Schema Introduction. Available online: https:\/\/moodledev.io\/docs\/apis\/core\/dml\/database-schema."},{"key":"ref_22","first-page":"46","article-title":"A psychometric analysis of reliability and validity of the index of learning styles (ILS)","volume":"7","author":"Parslow","year":"2015","journal-title":"Int. J. Psychol. Stud."}],"container-title":["Multimodal Technologies and Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2414-4088\/9\/7\/69\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:03:53Z","timestamp":1760033033000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2414-4088\/9\/7\/69"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,3]]},"references-count":22,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7]]}},"alternative-id":["mti9070069"],"URL":"https:\/\/doi.org\/10.3390\/mti9070069","relation":{},"ISSN":["2414-4088"],"issn-type":[{"value":"2414-4088","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,3]]}}}