Cognitive and behavioral engagement challenges in open and distance learning and potential solutions from artificial intelligence

Introduction Open and Distance Learning (ODL) broadens educational access but often limits student engagement due to cognitive overload and weak self-regulation. Artificial Intelligence (AI) offers potential solutions through adaptive support. Methods This study employed a qualitative descriptive case study. Data from two focus group interviews, reflective reports, and LMS records were analyzed using reflexive thematic analysis and triangulation. Results Students reported cognitive challenges such as processing complex content, information overload, and limited academic writing and quantitative skills, alongside behavioral challenges including procrastination, task prioritization, and difficulties with independent learning. Triangulation confirmed these patterns. Discussion Targeted support measures such as structured study planners, writing guidance, and tailored resource recommendations can help learners strengthen self-regulation and engagement. Embedding such supports into ODL can reduce overload and sustain active participation.

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Publication Details

Journal
Frontiers in Education
Published
2025-10-10
DOI
https://doi.org/10.3389/feduc.2025.1610148
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Cognitive and behavioral engagement challenges in open and distance learning and potential solutions from artificial intelligence

Aidah Abdul Karim, Fariza Khalid, Yanxing Xue
Frontiers in Education
Innovative Teaching and Learning Methods
article

Cognitive and behavioral engagement challenges in open and distance learning and potential solutions from artificial intelligence

Aidah Abdul Karim, Fariza Khalid, Yanxing Xue
article en

Abstract

Introduction Open and Distance Learning (ODL) broadens educational access but often limits student engagement due to cognitive overload and weak self-regulation. Artificial Intelligence (AI) offers potential solutions through adaptive support. Methods This study employed a qualitative descriptive case study. Data from two focus group interviews, reflective reports, and LMS records were analyzed using reflexive thematic analysis and triangulation. Results Students reported cognitive challenges such as processing complex content, information overload, and limited academic writing and quantitative skills, alongside behavioral challenges including procrastination, task prioritization, and difficulties with independent learning. Triangulation confirmed these patterns. Discussion Targeted support measures such as structured study planners, writing guidance, and tailored resource recommendations can help learners strengthen self-regulation and engagement. Embedding such supports into ODL can reduce overload and sustain active participation.

Frontiers in EducationVol. 10
National University of Malaysia (MY)
Openalex Percentile: Top 69%
Innovative Teaching and Learning Methods
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