Exploring the Potential of Generative AI for Academic Support in Open and Distance Learning: A Case Study of Learner Experiences

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Authors: Sefa Emre Öncü, Merve Gevher, Erdem Erdoğdu, Serpil Koçdar
Cited by: 1

Abstract

This exploratory case study provides an in-depth analysis of the potential of generative artificial intelligence (GenAI) to enhance academic support in open and distance learning (ODL) systems. The study examined learner experiences with a GenAI-based academic support application in an online web publishing course over a semester, focusing on two phases: free use and structured use. Data were collected through semi-structured interviews and dialogue transcripts from 10 distance learners. Findings highlighted both continuity and transformation in learner practices. In both phases, GenAI was valued for time-saving and accurate responses aligned with course materials. Structured tasks in phase 2 encouraged more purposeful engagement, including systematic self-assessment and information verification. Despite technical challenges such as device incompatibility and occasional hallucinations, learners expressed motivation, satisfaction, and a demand for institutional integration. The results, while preliminary, suggest that GenAI-based academic support holds strong potential for broader implementation in large-scale open universities, offering a pathway to balancing quality, access, and cost in addressing the enduring challenges of mass higher education.

Fields of Study & Subjects

Online Learning and Analytics AI in Service Interactions Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
The International Review of Research in Open and Distributed Learning
Publisher
Athabasca University Press
Volume
27
Issue
2
Pages
67–82
Publication date
6 May 2026
Language
EN