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◆ Acta Psychologica2025-12-19· Structural equation modeling

Students' attitudes toward AI teaching assistants in education: Considering the role of characteristics and perceptions in Ha'il Saudi Arabia

Saqib Muneer, Ghulam Dastgeer, Muhammad Imran Qureshi, Awwad Saad Alshammari

原始摘要(英文原文)· Original abstract
This study investigates the impact of human-like features and student perceptions on the intention to adopt Artificial Intelligence (AI)-based teaching assistants (AITAs) in higher education. Grounded in the Technology Acceptance Model, the study explores the roles of anthropomorphism, social language use, engagement quality, perceived usefulness, and ease of communication in shaping students' attitudes toward AITAs and their subsequent intention to adopt these technologies. Data were collected from 385 students in Ha'il Province, Saudi Arabia, using a structured questionnaire. The data were analyzed through Partial Least Squares Structural Equation Modeling to assess both direct and mediating effects. The findings reveal that all proposed factors have a positive influence on students' attitudes, which, in turn, significantly predict their intention to adopt AITAs. Furthermore, students' attitudes mediate the relationships between human-like features and adoption intentions. This research offers both theoretical insights and practical implications for integrating AITAs in educational contexts, highlighting the importance of designing AI systems that facilitate human-like interactions and promote positive student perceptions.
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Students' attitudes toward AI teaching assistants in education: Considering the role of characteristics and perceptions in Ha'il Saudi Arabia — 科研速览 Science Skim