A dual path cognitive model of academic well-being: the mediation of creative problem-solving ability and generative AI use self-efficacy

调解 对偶(语法数字) 生成语法 生成模型 心理学 认知 认知心理学 路径(计算) 认知科学 计算机科学 认知模型 因果模型 人工智能 路径分析(统计学) 人机交互 体验式学习 教育技术 空间能力 自主学习 数学教育 教学设计 社会心理学
作者
Princy Pappachan,Yu‐chu Yeh,Chua Ming Wei Gabriel
出处
期刊:Interactive Learning Environments [Taylor & Francis]
卷期号:: 1-18
标识
DOI:10.1080/10494820.2026.2732234
摘要

As generative artificial intelligence (GAI) becomes increasingly integrated into higher education and reshapes students’ learning experiences, important questions arise regarding how GAI-related competencies and higher-order thinking skills contribute to Academic well-being (AWB). Guided by the conceptual perspective of distributed cognition theory, this study proposed and tested a dual-path cognitive model of AWB. To support this investigation, we also developed the Inventory of GAI Use Self-Efficacy. For model testing, data were collected from 490 college students. The results supported the proposed dual-path model. Specifically, critical thinking dispositions and creativity competence were associated with AWB through creative problem-solving ability, whereas creativity competence and GAI use attitudes were related to AWB through GAI use self-efficacy. These findings suggest that AWB in the GAI era is associated with the synergistic integration of internal cognitive resources and AI-assisted external cognitive resources. The study contributes to the AWB theory and practice by: (a) evaluating a dual-path cognitive model that integrates higher-order thinking and GAI-related competencies; (b) identifying the possible intermediary roles of creative problem-solving ability and GAI use self-efficacy; and (c) providing a valid measure of GAI use self-efficacy for future research and educational applications in AI-enhanced learning contexts.
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