View in EDS PDF Full Text

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

Saved in:
Bibliographic Details
Title: Exploring the Potential of Generative AI for Academic Support in Open and Distance Learning: A Case Study of Learner Experiences.
Authors: Öncü, Sefa Emre1, Gevher, Merve1, Erdoğdu, Erdem1, Koçdar, Serpil1
Source: International Review of Research in Open & Distributed Learning. May2026, Vol. 27 Issue 2, p67-82. 16p.
Subject Terms: *Generative artificial intelligence, *Academic support programs, *Field research, *Higher education, *Open learning, *Online education, *Student engagement, Artificial intelligence in education
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. [ABSTRACT FROM AUTHOR]
Copyright of International Review of Research in Open & Distributed Learning is the property of Governors of Athabasca University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: ehh
DbLabel: Education Research Complete
An: 193542266
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Exploring the Potential of Generative AI for Academic Support in Open and Distance Learning: A Case Study of Learner Experiences.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Öncü%2C+Sefa+Emre%22">Öncü, Sefa Emre</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Gevher%2C+Merve%22">Gevher, Merve</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Erdoğdu%2C+Erdem%22">Erdoğdu, Erdem</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Koçdar%2C+Serpil%22">Koçdar, Serpil</searchLink><relatesTo>1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Review+of+Research+in+Open+%26+Distributed+Learning%22">International Review of Research in Open & Distributed Learning</searchLink>. May2026, Vol. 27 Issue 2, p67-82. 16p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Academic+support+programs%22">Academic support programs</searchLink><br />*<searchLink fieldCode="DE" term="%22Field+research%22">Field research</searchLink><br />*<searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br />*<searchLink fieldCode="DE" term="%22Open+learning%22">Open learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Online+education%22">Online education</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+engagement%22">Student engagement</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence+in+education%22">Artificial intelligence in education</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Review of Research in Open & Distributed Learning is the property of Governors of Athabasca University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=193542266
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 67
    Subjects:
      – SubjectFull: Generative artificial intelligence
        Type: general
      – SubjectFull: Academic support programs
        Type: general
      – SubjectFull: Field research
        Type: general
      – SubjectFull: Higher education
        Type: general
      – SubjectFull: Open learning
        Type: general
      – SubjectFull: Online education
        Type: general
      – SubjectFull: Student engagement
        Type: general
      – SubjectFull: Artificial intelligence in education
        Type: general
    Titles:
      – TitleFull: Exploring the Potential of Generative AI for Academic Support in Open and Distance Learning: A Case Study of Learner Experiences.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Öncü, Sefa Emre
      – PersonEntity:
          Name:
            NameFull: Gevher, Merve
      – PersonEntity:
          Name:
            NameFull: Erdoğdu, Erdem
      – PersonEntity:
          Name:
            NameFull: Koçdar, Serpil
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 14923831
          Numbering:
            – Type: volume
              Value: 27
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: International Review of Research in Open & Distributed Learning
              Type: main
ResultId 1