ArticleScientific reports2026
Artificial intelligence integrated WeChat social media adoption for collaborative learning engagement among university students.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Abstract
Artificial intelligence (AI) has transformed social media into a powerful tool for educational learning engagements. WeChat, a Chinese social media platform, is extensively used by students for academic learning, collaboration, and information acquisition. However, research on the adoption of AI-integrated social media for learning engagement remains limited, especially in the Chinese context. Based on the traditional Technology Acceptance Model (TAM), this study proposes an AI-Integrated Social Media Adoption (AISMA) model for learning engagement by integrating the core TAM constructs-perceived usefulness (PU) and perceived ease of use (PEOU), with the external factors of collaborative learning, social support, resource sharing, and facilitating conditions to investigate their influence on students' intention to adopt AI-integrated WeChat for learning engagement. Data from Chinese university students were analyzed using structural equation modeling (SEM) via Smart-PLS 4. The results confirm that collaborative learning, social support, and resource sharing are significant direct drivers of AI-integrated social media adoption. Furthermore, facilitating conditions significantly influence both PU and PEOU and also directly drive adoption intention. A key finding from the moderating analysis is that PEOU significantly amplifies the effects of all three external factors (collaborative learning, social support, and resource sharing) on adoption intention. While PU significantly strengthens the relationship for social support and resource sharing, it does not moderate the link between collaborative learning and adoption intention. The study concludes by discussing the theoretical contributions and practical implications for educators and platform developers.
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