Transforming Outcome-Based Education with Machine Learning
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| Title: | Transforming Outcome-Based Education with Machine Learning |
|---|---|
| Language: | English |
| Authors: | D. Vetrithangam, Puneet Kumar, Jaspreet Singh Batth, B. Arunadevi, V. Saravanan |
| Source: | Springer. 2026. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail:customerservice@springernature.com; Web site: http://www.springer.com |
| Peer Reviewed: | N |
| Page Count: | 286 |
| Publication Date: | 2026 |
| Intended Audience: | Teachers; Researchers; Policymakers |
| Document Type: | Book Collected Works - General |
| Descriptors: | Educational Change, Outcome Based Education, Electronic Learning, Educational Trends, Ethics, Educational Technology, Technology Uses in Education, Technology Integration, Evaluation Methods, Curriculum Design, Teaching Methods, Individualized Instruction, Early Intervention, Decision Making, Educational Innovation, Educational Improvement |
| DOI: | 10.1007/978-981-95-4925-2 |
| ISBN: | 978-981-9549-24-5 |
| Abstract: | This book explores the application of machine learning (ML) in outcome-based education (OBE) and its transformative potential to enhance learning effectiveness. It examines how ML can be seamlessly integrated into various dimensions of OBE to optimize assessment techniques, personalize curriculum design, and modernize teaching methodologies. Emphasizing practical implementation, the book highlights how ML enables personalized learning experiences, supports early intervention strategies, and promotes data-driven decision-making for continuous improvement. Serving as a valuable resource for educators, researchers, and policymakers, it provides actionable insights into leveraging the power of ML to drive innovation and improve educational outcomes. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | ED680688 |
| Database: | ERIC |
| Abstract: | This book explores the application of machine learning (ML) in outcome-based education (OBE) and its transformative potential to enhance learning effectiveness. It examines how ML can be seamlessly integrated into various dimensions of OBE to optimize assessment techniques, personalize curriculum design, and modernize teaching methodologies. Emphasizing practical implementation, the book highlights how ML enables personalized learning experiences, supports early intervention strategies, and promotes data-driven decision-making for continuous improvement. Serving as a valuable resource for educators, researchers, and policymakers, it provides actionable insights into leveraging the power of ML to drive innovation and improve educational outcomes. |
|---|---|
| ISBN: | 978-981-9549-24-5 |
| DOI: | 10.1007/978-981-95-4925-2 |
