Impact of the Conversational Educational Design Kit on Student Performance in Higher Education: A Prototype - DATA availability .xlsx

Learning in higher education requires strategies that structure balanced and effective experiences. In this context, the Conversational Educational Design Kit emerges as a tool that combines a conversational learning framework and a set of educational design principles, facilitating teacher planning without requiring specialized pedagogical training. However, its impact on student performance has not been widely evaluated. To address this gap, the authors developed the Conversational Learning Metrics (CLM), a tool based on Learning Analytics that quantifies the relationship between the five types of learning proposed in the Kit and their influence on academic performance.The study implemented the Kit and CLM in a university course, analyzing the interaction between the types of learning through regression and correlation models. The results show that practice and inquiry are the most significant predictors of production, highlighting the importance of actively applying knowledge and encouraging autonomous exploration. Additionally, interdependencies between acquisition and discussion, as well as between inquiry and discussion, were evident, suggesting that strengthening one type of learning positively impacts others.These findings validate the Kit and CLM as effective tools for improving teaching in higher education. However, it is recommended to expand their application in different contexts and evaluate their impact on variables such as motivation and self-efficacy, reinforcing the importance of integrated pedagogical models to optimize university teaching.The dataset collects the student performance within the CLM. Data is obtained from the institutional LMS.