Modeling Metacognitive and Cognitive Processes in Data Science Problem Solving (Student Abstract).

Data Science (DS) is an interdisciplinary topic that is applicable to many domains. In this preliminary investigation, we use caselet , a mini-version of a case study, as a learning tool to allow learners to practice data science problem solving (DSPS). Using a dataset collected from a real-world classroom, we performed correlation analysis to reveal the structure of metacognitive and cognitive processes. We also explored the similarity of different DS knowledge components based on students' performance. In addition, we built predictive models to characterize the relationship between metacognition, cognition and learning gain.