Data-Driven Analysis of Collaborative Problemsolving and Emotions in Knowledge Building Among Different Performance Groups

In response to the evolving demands of education, this study investigates the nuanced differences in collaborative problem-solving behaviors and epistemic emotions among varying performance groups within a knowledge building framework facilitated by a networked collaborative environment. Through rigorous content and comparative analysis of data collected from a knowledge forum, significant distinctions were identified. The results indicate that higher-performing groups not only contributed more notes but also engaged in deeper cognitive interactions and reflective explorations, thereby fostering mutual understanding and critical thinking. Moreover, these groups demonstrated a higher proportion of positive epistemic emotions, such as joy, compared to lower-performing groups, which were more prone to frustration and boredom. Uniquely, this study integrates quantitative content analysis and comparative evaluation to reveal the underlying dynamics of group collaboration, offering actionable insights for educational technology. The findings inform the design of adaptive learning environments by recommending targeted emotional support, incremental task design, and structured reflective sessions to balance collaborative moves and enhance knowledge integration. As such, the research provides a practical framework for developing technological solutions and pedagogical strategies aimed at improving team dynamics and educational outcomes in collaborative settings.