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Exploring the factors influencing college students' learning satisfaction in generative AI-supported MOOCs learning
Frontiers in Psychology
|November 12, 2025
Summary
Learner satisfaction in Massive Open Online Courses (MOOCs) with Generative AI (GenAI) is high, but teacher-student interaction impacts satisfaction negatively. Optimizing GenAI integration requires balancing human-computer roles and emotional support.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
- Online Learning
Background:
- Massive Open Online Courses (MOOCs) are increasingly incorporating Generative AI (GenAI) for personalized learner support.
- The specific factors influencing learner satisfaction in these GenAI-enhanced MOOC environments are not well understood.
- This study investigates the learning experience in GenAI-supported MOOCs from multiple dimensions.
Purpose of the Study:
- To construct and validate a model of factors influencing college students' learning satisfaction (LS) in GenAI-supported MOOCs.
- To analyze the impact of the GenAI-supported learning environment (LE), teacher-student interaction (TSI), student-student interaction (SSI), and learning outcomes (LO) on LS.
- To provide empirical evidence for enhancing GenAI application in MOOCs.
Main Methods:
- A quantitative approach using questionnaire data from 402 college students in GenAI-supported MOOC courses.
- Structural Equation Modeling (SEM) was employed for data analysis using IBM SPSS 25 and AMOS 26.
- The study validated a theoretical model of satisfaction influencing factors.
Main Results:
- Overall learner satisfaction in GenAI-supported MOOCs is high, meeting most learning needs.
- The learning environment (LE) positively influences LS indirectly through learning outcomes (LO).
- Teacher-student interaction (TSI) significantly impacts learning outcomes (LO) but negatively affects satisfaction, potentially due to emotional detachment or unmet expectations.
- Student-student interaction (SSI) enhances learning outcomes (LO) but does not directly impact satisfaction, indicating underutilization of peer collaboration.
Conclusions:
- GenAI-supported MOOCs show high potential for learner satisfaction, contingent on translating environmental perceptions into tangible learning outcomes.
- Addressing the negative impact of teacher-student interaction on satisfaction is crucial, possibly by improving teachers' GenAI collaboration skills and balancing human-computer roles.
- Future research should focus on strengthening emotional support and fully leveraging peer interaction within GenAI-enhanced MOOCs to maximize learner satisfaction.
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