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Students bring different levels of interest to learning experiences, which impacts how they engage with learning materials. This study aims to understand the relationship between student's interest levels and their scientific observation behaviors within a Minecraft-based learning system. Motivated by the growing interest in integrating human-AI collaboration within educational research, we combine the capabilities of Large Language Models (LLMs) with the expertise of human researchers to capture the emerging themes within students’ observations. Using epistemic network analysis, we then visualized and compared the observational patterns of students with high and low situational interest. Our findings indicate that students with higher situational interest tend to make observations across a broader range of topics, with a particular emphasis on scientific content. These results highlight the potential for developing timely interventions to support students with low situational interest. 

As digital games and simulations continue to see use in both formal and informal learning contexts, it becomes increasingly important to understand the goals, motivations, and interests of the learners using them. Recently, there has been increased interest in identifying the different engagement profiles of learners playing games, descriptions of groups of learners’ tendencies and preferences when playing digital games. These engagement profiles represent a powerful tool for designers looking to create personalized and adaptive learning environments. In this work, we explore two aspects of these engagement profiles. First, we explore the different profiles of engagement in a large sample of elementary and middle school learners playing the history game Jo Wilder and the Capitol Case (2019) in a variety of contexts, using the data from a self-report survey. Second, we explore the effect that minor game dialogue changes had on learners’ perceptions of different game elements, such as character likeability and humor, as well as personal preferences, such as enjoyment of history. These findings highlight opportunities for personalized and adaptive game design that leverage players’ goals and motivations.