{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T22:36:01Z","timestamp":1774218961310,"version":"3.50.1"},"reference-count":13,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T00:00:00Z","timestamp":1757894400000},"content-version":"vor","delay-in-days":257,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100012024","name":"Multimedia University","doi-asserted-by":"publisher","award":["MMUE\/220023"],"award-info":[{"award-number":["MMUE\/220023"]}],"id":[{"id":"10.13039\/100012024","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Applied Computational Intelligence and Soft Computing"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>In today\u2019s mobile communication society, the integration of mobile technology in education has revolutionised learning through m\u2010Learning. This approach leverages wireless mobile technology and computing, enabling learners to access educational resources anytime and anywhere, thereby enhancing flexibility and freedom. Mobile devices, such as smartphones, tablets and PDAs, facilitate m\u2010Learning by providing mobility and interactive learning environments. M\u2010Learning is characterised by its personalised, collaborative, and ubiquitous nature, offering learners context\u2010aware experiences tailored to their immediate surroundings and needs. Context awareness plays a pivotal role in m\u2010Learning, distinguishing it from traditional education by dynamically adapting content delivery based on factors beyond just location, including time, network conditions and user preferences. This adaptability poses significant challenges in designing effective teaching strategies that meet diverse learner requirements. To address these challenges, this study explores the application of machine learning techniques\u2014specifically \u201cArtificial Neural Networks (ANN), K\u2010Nearest Neighbours (KNN) and Adaptive Neuro\u2010Fuzzy Inference Systems (ANFIS)\u201d\u2014in developing a Context\u2010Aware m\u2010Learning platform. Performance comparisons based on RMSE, MAE and accuracy metrics reveal ANFIS as the optimal method for enhancing the proposed m\u2010Learning system, aligning with the contextual demands and parameters defined for effective mobile education. ANFIS\u2019s ability to minimise absolute prediction errors more effectively than the other methods. In terms of accuracy, ANFIS again leads the performance metrics, achieving an accuracy of 82.46% with 10 neurons. In comparison, ANN and KNN achieved accuracies of 81.17% and 80.74%, respectively. These accuracy values indicate that ANFIS not only reduces prediction errors but also consistently delivers higher predictive accuracy. This research contributes to advancing the field by providing insights into leveraging machine learning for adaptive and context\u2010aware educational technologies, thereby optimising learning experiences in today\u2019s mobile\u2010centric educational landscape.<\/jats:p>","DOI":"10.1155\/acis\/6982455","type":"journal-article","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T06:39:52Z","timestamp":1758004792000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Optimising Content Recommendations in Context\u2010Aware Mobile Learning Platform Through Machine Learning"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1190-9290","authenticated-orcid":false,"given":"Sudhindra B.","family":"Deshpande","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9217-6390","authenticated-orcid":false,"given":"Goh Kah Ong","family":"Michael","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0869-7100","authenticated-orcid":false,"given":"Rakesh J.","family":"Kadkol","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6021-7592","authenticated-orcid":false,"given":"N. 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Enhancing Content Recommendation System Using Semantic Awareness With Flamingo Search Optimization and Bi-LSTM IEEE Conference Publication IEEE Xplore 2023 https:\/\/ieeexplore.ieee.org\/document\/10169669.","DOI":"10.1109\/ICSCSS57650.2023.10169669"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.23939\/csn2022.01.001"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-01835-9"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2016.03.013"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.14569\/ijacsa.2022.0131036"}],"container-title":["Applied Computational Intelligence and Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/acis\/6982455","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1155\/acis\/6982455","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/acis\/6982455","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T11:46:30Z","timestamp":1772970390000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/acis\/6982455"}},"subtitle":[],"editor":[{"given":"Ridha","family":"Ejbali","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":13,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["10.1155\/acis\/6982455"],"URL":"https:\/\/doi.org\/10.1155\/acis\/6982455","archive":["Portico"],"relation":{},"ISSN":["1687-9724","1687-9732"],"issn-type":[{"value":"1687-9724","type":"print"},{"value":"1687-9732","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"2025-05-10","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-22","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"6982455"}}