Perception and assessment of an interactive AI assistant in a digital educational environment: a psychological and pedagogical analysis

Context and relevance. Traditional passive online learning formats in higher education often fail to sustain students' academic engagement. This raises the challenge of finding effective tools for personalizing education while minimizing cognitive and socio-psychological risks. Conversational AI assistants hold significant potential to address this issue; however, their impact on the subjective educational experience remains insufficiently explored. The rationale for this study stems from the need for a psychological and pedagogical analysis of how interactivity, personalization, and media-based stylization determine learners' engagement and satisfaction. Objective. The objective of this study is to provide a comprehensive evaluation of the impact of the AI lecturer DeepTalk on students’ academic engagement and their subjective perception of the educational course. Hypothesis. The use of an interactive AI assistant implementing principles of personalization and dialogue is expected to lead to higher levels of perceived engagement and overall course satisfaction compared to a traditional non-interactive online format. Methods and materials. A mixed-methods design was employed. Quantitative data were gathered through questionnaires, while qualitative data were derived from semi-structured interviews. The sample comprised 40 students (M = 20,9, SD = 2,43; 62,5% female) from Tomsk State University, who were assigned to either an experimental group (N = 20) learning with an AI lecturer or a control group (N = 20) following a conventional online format. Results. Subjective assessments revealed a largely positive perception of the AI-assisted course. The majority of the experimental group (85%) gave it high ratings, praising its novel format, logical structure, and practical utility. Interactivity, personalization, and gamification were identified as key drivers of this positive experience. However, significant barriers were also noted, primarily technical issues (e.g., AI response delays) and the assistant's limited anthropomorphic qualities, such as a monotonous voice. A key finding is that most participants believe AI cannot fully replace a human teacher in creative or discussion-heavy subjects. Additionally, 20% of respondents raised concerns about data privacy. Conclusions. These findings can inform the development of more effective and human-centered AI courses. While the results highlight AI's potential as a powerful supplementary tool, they also emphasize the critical need for robust technical implementation, user-controlled flexibility, and the irreplaceable role of the human educator in complex learning environments.

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