Assessing idea fluency through the student design process

Engineering design is a complex activity for students to undertake and for instructors to assess. This research uses large learner data sets collected through automatic, unobtrusive logging of student actions in a CAD platform to address this difficulty in observing design behavior. We used a computer-aided design software that captured student design activities to investigate patterns of student design behaviors that are associated with idea fluency. We show how micro-level process data can be used to validate observations made from viewing the student design process through design replays. Students who engaged in high idea fluency showed evidence of fluency in both process data and design replays. Similar patterns were observed for low idea fluency students. There is great potential to investigate student design learning through system-collected data. Yet, how to justify the inferences made about students based on their process data is largely unexplored. Our results demonstrate how traditional forms of assessment data can be used to validate inferences made by process data. Implications of this work would be highly relevant to engineering educators as well as researchers who are interested in understanding the relationship between learner analytics and student learning.