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Investigating Teacher’s Technological Pedagogical Content Knowledge in a CAD-enabled Learning Environment

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Pre-college: Blending Computers, Computational Thinking, and Engineering Education

Tagged Division

Pre-College Engineering Education Division

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Paper Authors


Chandan Dasgupta Department of Computer and Information Technology, Purdue University, West Lafayette

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Dr. Dasgupta is a Postdoctoral research fellow at Purdue University. He has a PhD in Learning Sciences from the University of Illinois at Chicago (UIC) and MS in Human-Computer Interaction from Georgia Tech. His dissertation work focused on scaffolding students' productive disciplinary engagement in engineering design activities using suboptimal models. His research interests include the use of counterexamples as primary generators for supporting productive disciplinary engagement, integration of design thinking and scientific inquiry into K-12 education, and designing learning environments that help students generate and use design heuristics and make effective tradeoff decisions.

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Alejandra J. Magana Purdue University, West Lafayette Orcid 16x16

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Alejandra Magana is an Associate Professor in the Department of Computer and Information Technology and an affiliated faculty at the School of Engineering Education at Purdue University. She holds a B.E. in Information Systems, a M.S. in Technology, both from Tec de Monterrey; and a M.S. in Educational Technology and a Ph.D. in Engineering Education from Purdue University. Her research is focused on identifying how model-based cognition in STEM can be better supported by means of expert technological and computing tools such as cyber-physical systems,visualizations and modeling and simulation tools.

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Jie Chao The Concord Consortium

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Jie Chao is a learning scientist with extensive research experience in technology-enhanced learning environments and STEM education. She completed her doctoral and postdoctoral training in Instructional Technology and STEM Education at the University of Virginia. Her past research experiences ranged from fine-grained qualitative mental process analysis to large-scale quantitative and longitudinal investigations. She is currently focusing on learning analytics research in open-ended domains such as engineering design and authentic scientific inquiry. With insights in learning sciences and a strong, computationally oriented mindset, she hopes to utilize learning analytics to investigate important questions with unprecedented granularity and generate actionable knowledge for the design of technology and curriculum.

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There has been an increased emphasis on the integration of engineering design with science learning across all grades in the school curriculum. A critical aspect of this integration process is understanding teacher preparedness and their knowledge about the technology, content, and pedagogy relevant for the effective implementation of such integrated curriculum. Prior research suggests that teachers may not be prepared to integrate technologies and other scaffolds that are crucial for students’ productive engagement with engineering design. Teaching technology skills isolated from the classroom context in which they need to be implemented does not help. Thus, the need of the hour is classroom environments that provide teachers opportunities for engaging deeply and meaningfully with the technology and scaffolding the implementation of technology to support science and engineering learning. We present findings from a study that investigates teachers’ technological pedagogical content knowledge in the context of a project-based unit using a CAD tool. We discuss ways in which teachers’ orchestrated their classroom instruction and interactions with the students.

Dasgupta, C., & Magana, A. J., & Chao, J. (2017, June), Investigating Teacher’s Technological Pedagogical Content Knowledge in a CAD-enabled Learning Environment Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28586

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