June 24, 2017
June 24, 2017
June 28, 2017
NSF Grantees Poster Session
Through a five-year collaborative project, Purdue University and the Concord Consortium are applying a data-intensive approach to study one of the most fundamental research topics in learning sciences and engineering education: “How do secondary students learn and apply science concepts in engineering design processes?” We have collected data from over 1,000 middle and high school students in Indiana and Massachusetts through automatic, unobtrusive logging of student design processes enabled by a unique CAD tool that supports the design of energy-efficient buildings using earth science, physical science, and engineering science concepts and principles of design. Data collected includes fine-grained information of student design actions, experimentation behaviors, electronic student reflection notes, and virtual design artifacts. These process data are used to reconstruct the entire learning trajectory of each individual student. Our research evaluates how these learning analytics applied to these process data can be the computational counterparts of traditional performance assessment methods. Combining these process data with pre/post-tests and demographic data, we have investigated the common patterns of student design behavior and associated learning outcomes. We have focused on how students deepen their understanding of science concepts involved in engineering design projects and how often and deeply students use scientific experimentation to make a design choice.
Purzer, S., & Adams, R., & Goldstein, M. H. (2017, June), Board # 43 : Large-scale Research on Engineering Design in Secondary Classrooms: Big Learner Data Using Energy3D Computer-Aided Design Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. https://peer.asee.org/27854
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