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The integration of artificial intelligence (AI) into learning management systems (LMSs) calls for studies focusing on the drivers of student engagement. This exploratory study aims to investigate the Blackboard AI Conversation tool's potential impact on postgraduate student engagement, using the AI device usage acceptance (AIDUA) model. A qualitative design was employed, combining focus group interviews with master's and PhD students and a functional analysis of 360 turns to document actual usage patterns. Qualitative findings from the focus groups were examined using Braun and Clarke's (six stages) thematic analysis. The results indicated that perceptions of anthropomorphism and hedonic motivation appeared to enhance students' initial appraisals, potentially transforming AI into perceived human-likeness assistant and encouraging active dialogue. However, cognitive fatigue was observed, seemingly due to AI's verbosity and persistent conversation loops. These observed patterns, stemming from an intentionally open-ended design , suggest that instructional designers should consider structured closure mechanisms to manage conversation loops and prevent user burnout. Future research should investigate the longitudinal stability of these emotional and cognitive responses. This research offers preliminary qualitative insights into the implementation of AI-enhanced digital classrooms in higher education contexts .
Fawzia Omer Alubthane (Fri,) studied this question.