Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Kumar, Ajay; Tak, Tan Kuan; Ali, S Md Shakir; Haque, Mustafizul; Paralkar, Tejasvini Alok; Pravin Kshirsagar, R.; Upreti, Kamal Title A name given to the resource Predictive Modeling of Student Learning Outcomes Through Cognitive and Emotional Skill Integration Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived International Research Journal of Multidisciplinary Scope;Volume;6;Issue;1;pp.892-910 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.47857/irjms.2025.v06i01.02895" target="_blank" rel="noreferrer noopener">https://doi.org/10.47857/irjms.2025.v06i01.02895</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85218767526?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85218767526?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kumar A., Indraprastha Engineering College, Ghaziabad, India; Tak T.K., Singapore Institute of Technology, Singapore; Ali S.M.S., Auroras PG College, Hyderabad, India; Haque M., Dr. D.Y. Patil Vidyapeeth's Centre For Online Learning, Dr. D.Y. Patil Vidyapeeth (Deemed To Be University), Pune, India; Paralkar T.A., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Nagpur Campus, India; Pravin Kshirsagar R., Department of Electronics &amp; Telecommunication Engineering, JD College of Engineering &amp; Management, Maharashtra, Nagpur, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR Campus, Ghaziabad, India Description An account of the resource The interplay of factors, including both cognitive and non-cognitive, plays a significant role in the learning patterns of students. However, the majority of the research conducted on such issues mainly puts forward the role of cognitive skills but forgets that a very important role is played by the non-cognitive factor, specifically motivation and emotional intelligence. Therefore, this study focuses on bridging that gap by investigating the combined influence of cognitive and non-cognitive factors on the learning capacities of engineering students during their transition to higher education. A two-year longitudinal study on engineering students of AITAM, Tekele, India was considered in relation to their academic performance, learning preference, and socio-emotional aspects. The approach adopted makes use of predictive analytics. It is deployed here as machine learning algorithms in the form of Logistic Regression (LR), Naive Bayes, k-Nearest Neighbors (k-NN), Decision Trees (DT), and Support Vector Machines (SVM) to classify the learners into very fast, fast, average, and slow learners. The algorithm of k-NN also achieved the highest accuracy classification and showed good robustness for learning the students' learning rates. This study underscores the combination of new teaching approaches as well as personalized self-learning methods to enhance learning performance, especially for slow learners. Indeed, the outcome gives avenues for much more extensive studies done on large datasets using advanced algorithms which can be applied across a range of educational fields to support tailored learning interventions. 2025, Iquz Galaxy Publisher. All rights reserved. Subject The topic of the resource Classification; Cognitive Learning; Education; Machine Learning; Non-Cognitive Learning; Student Performance Publisher An entity responsible for making the resource available Iquz Galaxy Publisher Relation A related resource ISSN: 2582631X; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online