Understanding the Impact of Interaction Elements on MOOCs Continuance Intention Among Undergraduates: An Extended Expectation Confirmation Model

This study aims to investigate the influence of interaction on undergraduates’ continuance intention to use Massive Open Online Courses based on the Expectation Confirmation Model (ECM) and to examine the moderating effect of gender. 235 undergraduates were randomly sampled and surveyed, providing self-reports on 10 constructs (student-student interactions, student-teacher interactions, student-content interactions, controllability, responsiveness, confirmation, perceived usefulness, satisfaction, and continuance intention). The Partial Least Squares Structural Equation Modelin was employed for data analysis. The findings indicate that student-teacher interactions, student-content interactions, controllability, and responsiveness have a significant positive impact on undergraduates’ continuance intention to use Massive Open Online Courses. However, student-student interactions do not show a significant relationship with continuance intention. Additionally, no significant gender differences were found concerning the influence of perceived usefulness and satisfaction on continuance intention. The study also discusses the theoretical and practical impacts of undergraduates’ use of Massive Open Online Courses.

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Publication Details

Journal
SAGE Open
Published
2025-04-01
DOI
https://doi.org/10.1177/21582440251342171
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00

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article

Understanding the Impact of Interaction Elements on MOOCs Continuance Intention Among Undergraduates: An Extended Expectation Confirmation Model

Jiangting Liu, Hongzhu Long
SAGE Open
Online Learning and Analytics
article

Understanding the Impact of Interaction Elements on MOOCs Continuance Intention Among Undergraduates: An Extended Expectation Confirmation Model

Jiangting Liu, Hongzhu Long
article en

Abstract

This study aims to investigate the influence of interaction on undergraduates’ continuance intention to use Massive Open Online Courses based on the Expectation Confirmation Model (ECM) and to examine the moderating effect of gender. 235 undergraduates were randomly sampled and surveyed, providing self-reports on 10 constructs (student-student interactions, student-teacher interactions, student-content interactions, controllability, responsiveness, confirmation, perceived usefulness, satisfaction, and continuance intention). The Partial Least Squares Structural Equation Modelin was employed for data analysis. The findings indicate that student-teacher interactions, student-content interactions, controllability, and responsiveness have a significant positive impact on undergraduates’ continuance intention to use Massive Open Online Courses. However, student-student interactions do not show a significant relationship with continuance intention. Additionally, no significant gender differences were found concerning the influence of perceived usefulness and satisfaction on continuance intention. The study also discusses the theoretical and practical impacts of undergraduates’ use of Massive Open Online Courses.

SAGE OpenVol. 15(2)
Chongqing Vocational Institute of Engineering (CN)
Chongqing Municipal Education Commission
Openalex Percentile: Top 85%
Online Learning and Analytics
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Understanding the Impact of Interaction Elements on MOOCs Continuance Intention Among Undergraduates: An Extended Expectation Confirmation Model — Jiangting Liu, Hongzhu Long · SAGE Open (2025) | TGRS Research Map | TGRS