Artificial intelligence (AI)-based learning assistants and chatbots are increasingly integrated into higher education. While these tools are often evaluated in terms of technical performance, their successful and ethical use also depends on psychological factors such as trust, perceived risk, technology anxiety, and students' general attitudes toward AI. This paper adopts a psychology-oriented perspective to examine how university students form trust in AI-based learning assistants. Drawing on recent literature in mental health, human-AI interaction, and trust in automation, we propose a conceptual framework that organizes psychological predictors of trust into four groups: cognitive appraisals, affective reactions, social-relational factors, and contextual moderators. A narrative review approach synthesizes empirical findings and derives research questions and hypotheses for future studies. The paper highlights that trust in AI is a psychological process shaped by individual differences and learning environments, with practical implications for instructors, administrators, and designers of educational AI systems.

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