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ERIC Number: EJ1126804
Record Type: Journal
Publication Date: 2016
Pages: 27
Abstractor: As Provided
ISSN: EISSN-1929-7750
Using Learning Analytics to Characterize Student Experimentation Strategies in Engineering Design
Vieira, Camilo; Goldstein, Molly Hathaway; Purzer, Senay; Magana, Alejandra J.
Journal of Learning Analytics, v3 n3 p291-317 2016
Engineering design is a complex process both for students to participate in and for instructors to assess. Informed designers use the key strategy of conducting experiments as they test ideas to inform next steps. Conversely, beginning designers experiment less, often with confounding variables. These behaviours are not easy to assess in educational settings because they occur throughout the design process. This paper reports on a two-fold study carried out to test the model for identifying student behaviours during design experimentation. The first phase uses the process data from 48 middle-school students designing an energy-plus house. The study utilized learner interaction data sets collected through automatic, unobtrusive logging of student actions in a CAD platform. The analysis of learner process data is compared to student performance on an open-ended post-test. The second phase correlates the number of experiments students conducted to the quality of student prototypes. The results suggest that the proposed model can be used to identify, characterize, and assess student strategies associated with conducting experiments. Implications of this work are relevant to engineering and design educators as well as researchers interested in the role of learning analytics in studying complex processes.
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Publication Type: Journal Articles; Reports - Research
Education Level: Middle Schools; Secondary Education; Junior High Schools
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: DUE1348547; DRL1503436