Unveiling the Cognitive and Affective Mechanisms of Virtual Museum Learning: A Partial Least Squares Analysis

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Virtual museums, as important carriers of immersive learning environments, are changing traditional knowledge acquisition and cultural inheritance methods. However, existing research focuses on direct relationships between virtual museum design features and learning outcomes, lacking systematic revelation of cognitive and affective mechanism pathways in the learning process. Therefore, this study constructs a Cognitive-Affective Model of Virtual Museum Learning (CAMVML), aiming to reveal complex relationships among virtual museums’ technological features, learners’ cognitive and affective experiences, and learning outcomes. This study involved 254 seventh-grade students as participants, utilized structured questionnaires for data collection, and employed partial least squares structural equation modeling to empirically validate the proposed model. Results showed that the virtual museum’s interactivity and autonomy, learners’ germane cognitive load, flow experience, and situational interest significantly and positively predicted learning outcomes. Additionally, germane cognitive load and flow experience played important mediating roles between technical features and learning outcomes. Results verified multiple hypothesized paths in the proposed model and highlighted the necessity of synergy between cognitive and affective factors in virtual learning environments. This study provides a structured theoretical framework for understanding cognitive and affective mechanisms of virtual museum learning and provides empirical support for instructional design and practical application of immersive learning environments.