ArticleFrontiers in psychology2025
Understanding continued use of smart learning platforms: psychological wellbeing in an extended TAM-ISCM model.
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 9 papers.
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Who cites it
9 citing papers in PubMed.
- Determinants of Learners' Continuance Intention in Informal Video Learning: Evidence from YouTube.Behavioral sciences (Basel, Switzerland) · 2026Article
- Mobile Learning in Medical Education: Quasi-Experimental Realist Evaluation of Usage, Context, and Examination Performance in a Curricular Setting.JMIR medical education · 2026Article
- Factors influencing residents' continued use intention of smart community platforms: an integrated theoretical perspective.BMC psychology · 2026Article
- Continuance intention to use mobile learning among college students: integrating quality factors and the expectation confirmation model.Scientific reports · 2026Article
- Article
- Relationship between school support and digital teaching adaptation among physical education teachers: the mediating roles of self-efficacy, digital teaching beliefs and teaching intention.Frontiers in psychology · 2026Article
- Psychological mechanisms underlying medical students' continued use of DeepSeek: an explanatory sequential mixed-methods study.Frontiers in psychology · 2026Article
- Modeling student satisfaction in online learning using random forest.Scientific reports · 2025Article
- Perceived ease of use, perceived enjoyment, and continuance intention as predictors of medical students' well-being in hybrid learning: an extended TAM approach.Frontiers in psychology · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: In response to the growing adoption of digital education technologies, this study explores the factors influencing the continuous use of innovative learning platforms among students in higher vocational education. Recognizing that technological performance and psychological experiences shape user engagement, this research extends the Technology Acceptance Model (TAM) by integrating constructs such as perceived trust, enjoyment, ideological alignment, and psychological states-including satisfaction, wellbeing, and anxiety. Methods: Data were collected from 782 higher vocational college students in China using an online questionnaire. Participants represented diverse academic fields (e.g., liberal arts, sciences, engineering, arts) and were balanced in terms of gender (44.28% male and 55.72% female). Structural Equation Modeling (SEM) was applied to assess direct and indirect relationships among key variables, including perceived usefulness, perceived ease of use, system quality, expectation confirmation, enjoyment, and psychological indicators such as anxiety and subjective wellbeing. The mediating role of psychological wellbeing was also tested to evaluate its influence on continued platform usage. Results: Perceived enjoyment emerged as the strongest predictor of continuance intention ( Discussion: These findings highlight the need for innovative learning platforms to address technological expectations and psychological resilience. While usability and usefulness remain essential, designers must foster emotional engagement and manage trust-based expectations. Platforms that overlook psychological dimensions risk diminishing user satisfaction and long-term retention. Conclusion: Sustaining engagement with innovative learning platforms in higher vocational education requires a holistic approach that balances functional usability with mental wellbeing. This study offers important theoretical and practical insights for educators, developers, and policymakers aiming to create emotionally supportive and pedagogically effective digital learning environments.
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Registered trials
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.