ItemArticle

Predictive Modeling of Student Learning Outcomes Through Cognitive and Emotional Skill Integration

Title
Predictive Modeling of Student Learning Outcomes Through Cognitive and Emotional Skill Integration
Creator
Kumar, Ajay; Tak, Tan Kuan; Ali, S Md Shakir; Haque, Mustafizul; Paralkar, Tejasvini Alok; Pravin Kshirsagar, R.; Upreti, Kamal
Description
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.
Source
International Research Journal of Multidisciplinary Scope;Volume;6;Issue;1;pp.892-910
Date
01-01-2025
Publisher
Iquz Galaxy Publisher
Subject
Classification; Cognitive Learning; Education; Machine Learning; Non-Cognitive Learning; Student Performance
Coverage
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 & Telecommunication Engineering, JD College of Engineering & Management, Maharashtra, Nagpur, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR Campus, Ghaziabad, India
Rights
All Open Access; Gold Open Access
Relation
ISSN: 2582631X;
Format
online
Language
English
Type
Article

Citation

Kumar, Ajay; Tak, Tan Kuan; Ali, S Md Shakir; Haque, Mustafizul; Paralkar, Tejasvini Alok; Pravin Kshirsagar, R.; Upreti, Kamal, “Predictive Modeling of Student Learning Outcomes Through Cognitive and Emotional Skill Integration,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/23626.

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