Evanston, IL
June 27 – 29, 2016
Conference Website
This biennial conference series provides an international forum for the presentation and discussion of state-of-the-art and cutting-edge design research with a focus on artificial intelligence, cognitive science and computational theories in design. The conference proceedings will form a continuing archive of design computing and cognition research. The conference will be preceded by a series of state-of-the-art half-day workshops on specialist topics in design computing and cognition.
Wednesday, June 29
Experiences with Large Learner Data for Understanding How People Design: Insights and Lessons Learned
Robin Adams (Purdue University), Molly Goldstein (Purdue University), Charles Xie (The Concord Consortium)
4:00–6:00 PM, Louis Room, Norris Center
The context of this paper is a “large learner data” project that seeks to respond to existing challenges by introducing educational data mining and learning analytics into K-12 engineering design research. To probe deeply into student learning, we are developing and refining computational techniques to analyze large process analytics datasets generated through a CAD-based software, Energy3D, that logs design process data as students complete an assigned design challenge, such as a net-zero energy efficient building. We are combining these process analytics with demographic data and pre/post-tests of science and design knowledge. In this paper, we revisit three illustrative research cases to reflect on our experiences and lessons learned with navigating big data, generating useful data visualizations, and integrating process analytics with traditional performance assessment methods to relate design actions to knowledge and learning outcomes.