Chatbots as scaffolding tools
An active learning model to empower diverse learners
Bibliographic Data
| ID | 12427774 |
|---|---|
| Authors | Hariharan Ravi (0000-0002-6125-339X, International Institute of Business Studies – Bangalore Airport Campus PG Department of Management, , Bengaluru, corresponding author), R Vedapradha (United States Department of Commerce), Vedapradha R (St Joseph’s College of Commerce Department of Commerce and Management, , Bengaluru) |
| Year | 2025 |
| Volume | 33 |
| Issue | 2 |
| Pages | 283-297 |
| Publication date | 2025-05-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | On the Horizon The International Journal of Learning Futures (JOURNAL) |
| Journal identifiers | ISSN: 1074-8121 • E-ISSN: 2054-1708 |
| Publisher | Emerald Publishing Limited (PUBLISHER • GB) |
| DOI | 10.1108/oth-07-2024-0035 |
| OpenAlex | W4410044427 |
| Language | EN |
| Citations received | 1 |
| References cited | 61 |
Purpose This study aims to investigate the scope of integrating educational bots using the Active Learning Model (ALM) within the Learning Management System to empower diverse learners in higher educational institutions (HEIs) focused on improving their academic performance. It also explores the deliberations of these chatbots to ensure accessibility through personalised experience and better opportunities for underprivileged students through community service by HEIs. Design/methodology/approach The systematic sampling method was adopted to collect responses from the 480 students of post-graduate departments in HEIs situated in Bangalore, Hyderabad, Trivandrum and Chennai. JASP V.18 was used to perform the Simple Percentage Analysis, Exploratory Factor Analysis and Structural Equation Modelling to validate the hypothesis. ALM dimensions resulted in personalised learning, intelligent tutoring, language learning, learning analytics and accessibility. Findings Personalised learning, intelligent tutoring and earning analytics are the key indicators of ALM dimensions. Intelligent tutoring is the highest predictor of personalised learning in educational chatbots. Personalised learning of educational chatbots significantly impacts accessibility to diverse learners among HEIs. Originality/value This study covers the complexities of educational chatbots, the theoretical foundations of active learning and a methodology for using the ALM in HEIs. It offers an interdisciplinary approach that provides insights and recommendations that will guide future educational practices and policy creation and promote robust research, ultimately advancing inclusive education in the digital era
Active learning (machine learning · Human–computer interaction · Mathematics education · Programming language · Scaffold · AI in Service Interactions · Computer Science · E-Learning and Knowledge Management · Online Learning and Analytics · Psychology · Artificial Intelligence
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| Citations per year | 1 |
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| Citation span | 2026 - 2026 (1) |
| Highly cited | No |