Evidence map›Paper›PMID 41221187›Full record

ArticleFrontiers in psychology2025

Exploring the factors influencing college students' learning satisfaction in generative AI-supported MOOCs learning environment: a learning experience framework perspective.

Peipei Lv, Xin Wang, Yong Nie, Ruixin Wu, Lu Wang

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Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Peipei Lv *Faculty of Education, Shaanxi Normal University, Xi'an, China.
Xin Wang *Faculty of Education, Shaanxi Normal University, Xi'an, China.
Yong NieFaculty of Education, Shaanxi Normal University, Xi'an, China.
Ruixin WuFaculty of Education, Shaanxi Normal University, Xi'an, China.
Lu WangTeaching Center, Guangzhou Open University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Massive Open Online Courses (MOOCs) are gradually integrating GenAI technologies to provide personalized support. However, the mechanisms underlying the factors influencing learners' satisfaction in GenAI-supported MOOCs remain unclear. Under learning experience perspective, this study constructs a model of factors influencing college students' learning satisfaction (LS) that includes four dimensions: GenAI-supported MOOC learning environment (LE), teacher-student interaction (TSI), student-student interaction (SSI) and learning outcomes (LO). Method: Data from 402 college students' questionnaires were collected in GenAI-supported MOOC courses, which was analyzed by IBM SPSS 25 and AMOS 26 software platforms. A structural equation model (SEM) was used to validate the theoretical model of satisfaction influencing factors. Results and discussion: Results found that: (1) students' overall LS in GenAI-supported MOOCs is high, indicating the environment can satisfy students' most learning needs; (2) although LE does not directly affect LS, it positively influences LS through the mediation of LO, which suggests that learners' perception of LE needs to be translated into the actual LO before it can improve LS; (3) TSI has a significant positive impact on LO, but a negative impact on satisfaction, indicating that GenAI intervention may lead to emotional detachment or excessive expectations; (4) SSI promotes LO, but does not have a significant impact on LS, reflecting that the value of peer collaboration has not been fully embodied in GenAI environment. In GenAI-supported MOOCs, improving teachers' GenAI collaboration ability, balancing human-computer roles, and strengthening emotional support are the future directions to enhance LS. This study provides empirical evidence for the in-depth application and effect enhancement of GenAI in MOOCs.

Indexed as

college studentsGenAIlearning experiencelearning satisfactionMOOCs learning environment

Identifiers

PMID41221187
PMCPMC12597930

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.