AI Chatbot Acceptance and Self-Disclosure among Guidance and Counseling Students: Testing the Technology Acceptance Model in Counselor Education
Abstract
Self-disclosure is a core competency in counseling, yet many students experience psychological barriers, such as fear of judgment and stigma, that inhibit openness. AI-powered counseling chatbots directly facilitate self-disclosure by providing a non-judgmental and anonymous environment that reduces these barriers. However, empirical evidence in counselor education remains limited. This study examines the role of Technology Acceptance Model (TAM) variables in predicting self-disclosure among 76 Guidance and Counseling students at Universitas PGRI Semarang using a cross-sectional design. Results showed moderate levels of perceived ease of use (M = 3.38), perceived usefulness (M = 3.46), attitude toward use (M = 3.18), and self-disclosure (M = 2.94). Correlation analysis revealed significant associations between perceived ease of use (r = 0.20, p = 0.043), perceived usefulness (r = 0.32, p = 0.002), attitude toward use (r = 0.39, p < 0.001), and self-disclosure. Regression results indicated that perceived usefulness (B = 0.29, p = 0.04) and attitude toward use (B = 0.31, p = 0.005) significantly predicted self-disclosure, explaining 35.8% of variance (R² = 0.36). These findings extend TAM by demonstrating that psychological acceptance and perceived value, rather than usability, are the primary drivers of self-disclosure in AI-mediated counseling.
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