Purzer, S., & Adams, R., & Goldstein, M. H., & Douglas, K. A. (2015, June), Large-scale Research on Engineering Design in Secondary Classrooms: Big Learner Data Using Energy3D Computer-Aided Design  Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24391

\bibitem{asee_peer_24391}
  Purzer, S., \& Adams, R., \& Goldstein, M. H., \& Douglas, K. A. (2015, June), \emph{Large-scale Research on Engineering Design in Secondary Classrooms: Big Learner Data Using Energy3D Computer-Aided Design}
  Paper presented at 2015 ASEE Annual Conference \& Exposition, Seattle, Washington.
  10.18260/p.24391

Senay Purzer, Robin Adams, Molly H Goldstein, and K. Anna Douglas.  "Large-scale Research on Engineering Design in Secondary Classrooms: Big Learner Data Using Energy3D Computer-Aided Design".  2015 ASEE Annual Conference & Exposition, Seattle, Washington, 2015, June.  ASEE Conferences, 2015.  https://peer.asee.org/24391 Internet.  03 Jul, 2024

\bibitem{asee_peer_24391}
  Senay Purzer, Robin Adams, Molly H Goldstein, and K. Anna Douglas.
  "Large-scale Research on Engineering Design in Secondary Classrooms: Big Learner Data Using Energy3D Computer-Aided Design".
  \emph{2015 ASEE Annual Conference \& Exposition, Seattle, Washington, 2015, June}.
  ASEE Conferences, 2015.
  https://peer.asee.org/24391 Internet.  03 Jul, 2024

@INPROCEEDINGS{asee_peer_24391
author = "Senay Purzer, Robin Adams, Molly H Goldstein, and K. Anna Douglas"
title = "Large-scale Research on Engineering Design in Secondary Classrooms: Big Learner Data Using Energy3D Computer-Aided Design"
booktitle = "2015 ASEE Annual Conference \& Exposition"
year = "2015"
month = "June"
address = "Seattle, Washington"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/24391}
number = {10.18260/p.24391}
}

TY  - CPAPER
AB  -  Large-scale Research on Engineering Design in Secondary Classrooms: Big          Learner Data Using Energy3D Computer-Aided Design        Through a five-year collaborative project, the Concord Consortium and PurdueUniversity are applying a data-intensive approach to study one of the most fundamental researchtopics in learning sciences: “How do secondary students learn and apply science concepts inengineering design processes?” We have collected more 2GB of structured data from secondaryschool students in Indiana and Massachusetts through automatic, unobtrusive logging of studentdesign processes enabled by a unique CAD tool that supports the design of energy-efficientbuildings using Earth science and physical science concepts. Data includes fine-grainedinformation of student actions, experimentation results, electronic notes, and design artifacts.These process data are used to reconstruct the entire learning trajectory of each individualstudent with high resolution. Our research evaluates how these learning analytics applied to theseprocess data can be the computational counterparts of traditional performance assessmentmethods. Combining these process data with pre/post-tests and demographic data, we haveinvestigated the common patterns of student design behaviors and how they are associated withlearning outcomes with a specific focus on how students deepen their understanding of scienceconcepts involved in engineering design projects and how often and deeply students usescientific experimentation to make a design choice. So far we completed two small-scale studiesin Massachusetts and one study in Indiana using classroom observations and expert evaluations.We are collecting data with student interviews to validate metrics. Some key findings are…evidence that suggests that for science learning to occur, design projects used in classroomsshould (1) allow and emphasize trade-off analysis and include time and resources forexperimenting and data gathering; (2) provide instructional scaffolding and formative feedbackto guide student design.
AU  - Senay Purzer
AU  - Robin Adams
AU  - Molly H Goldstein
AU  - K. Anna Douglas
CY  - Seattle, Washington
DA  - 2015/06/14
PB  - ASEE Conferences
TI  - Large-scale Research on Engineering Design in Secondary Classrooms: Big Learner Data Using Energy3D Computer-Aided Design
UR  - https://peer.asee.org/24391
DO  - 10.18260/p.24391
ER  -