{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T16:11:34Z","timestamp":1772986294723,"version":"3.50.1"},"reference-count":85,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Prince Sultan University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In smart education, adaptive e-learning systems personalize the educational process by tailoring it to individual learning styles. Traditionally, identifying these styles relies on learners completing surveys and questionnaires, which can be tedious and may not reflect their true preferences. Additionally, this approach assumes that learning styles are fixed, leading to a cold-start problem when automatically identifying styles based on e-learning platform behaviors. To address these challenges, we propose a novel approach that annotates unlabeled student feedback using multi-layer topic modeling and implements the Felder\u2013Silverman Learning Style Model (FSLSM) to identify learning styles automatically. Our method involves learners answering four FSLSM-based questions upon logging into the e-learning platform and providing personal information like age, gender, and cognitive characteristics, which are weighted using fuzzy logic. We then analyze learners\u2019 behaviors and activities using web usage mining techniques, classifying their learning sequences into specific styles with an advanced deep learning model. Additionally, we analyze textual feedback using latent Dirichlet allocation (LDA) for sentiment analysis to enhance the learning experience further. The experimental results demonstrate that our approach outperforms existing models in accurately detecting learning styles and improves the overall quality of personalized content delivery.<\/jats:p>","DOI":"10.3390\/info15050277","type":"journal-article","created":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T11:18:17Z","timestamp":1715599097000},"page":"277","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Enhancing E-Learning Adaptability with Automated Learning Style Identification and Sentiment Analysis: A Hybrid Deep Learning Approach for Smart Education"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-9107-8414","authenticated-orcid":false,"given":"Tahir","family":"Hussain","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Central South University, 932 South Lushan Rd, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7078-9068","authenticated-orcid":false,"given":"Lasheng","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Central South University, 932 South Lushan Rd, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6423-9809","authenticated-orcid":false,"given":"Muhammad","family":"Asim","sequence":"additional","affiliation":[{"name":"EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia"},{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou 510006, China"}]},{"given":"Afaq","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Central South University, 932 South Lushan Rd, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6947-3717","authenticated-orcid":false,"given":"Mudasir Ahmad","family":"Wani","sequence":"additional","affiliation":[{"name":"EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e29175","DOI":"10.1016\/j.heliyon.2024.e29175","article-title":"Teachers\u2019 perspectives on effective English language teaching practices at the elementary level: A phenomenological study","volume":"10","author":"Imran","year":"2024","journal-title":"Heliyon"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Farooq, U., Naseem, S., Mahmood, T., Li, J., Rehman, A., Saba, T., and Mustafa, L. 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