Columbus, Ohio
June 24, 2017
June 24, 2017
June 28, 2017
Student
2
10.18260/1-2--27694
https://peer.asee.org/27694
553
Molly Goldstein is a Ph.D. candidate in the School of Engineering Education at Purdue University, West Lafayette with a research focus on characterizing behaviors in student designers. She previously worked as an environmental engineer specializing in air quality influencing her focus in engineering design with environmental concerns. She earned her B.S. in General Engineering (Systems Engineering & Design) and M.S. in Systems and Entrepreneurial Engineering from the University of Illinois in Urbana-Champaign.
Although design and decision-making are intertwined for practicing engineers, students from elementary school through college and graduate schools are not taught to think through uncertain situations (Howard, 2007) in which information is limited or outcomes are not guaranteed. Trade-offs are a complex element of decision, as the decision-making weighs possible outcomes against their respective costs (Otto &Antonsson, 1991). Although much is understood about how professional designers’ behaviors as compared to novice designers and students (Atmen et al., 2007; Crismond & Adams, 2012; Cross, 2003), there is little research regarding making trade-off decisions from middle school and high school to college. Understanding how students characterize their design tradeoffs would allow educators a better glimpse into students’ system design thinking. Without such knowledge at the K-16 level, we cannot create suitable design activities for students to improve on their decision-making skills, inhibiting their effectiveness as future engineers. In order to characterize trade-off behaviors in student designers, I will study the student design profiles and design artifacts in conjunction with student conceptions of design (i.e. what they do and what they think). In order to review student design profiles I propose using learning analytics (e.g., logs of student design files). Traditional tests and student design reflections will be utilized to better understand student design thinking. Learning analytics, traditional test and reflections will be used to group students based on the patterns they exhibit related to trade-off decisions. My rationale is that identifying these patterns will help K-16 educators (1) understand variations in student trade-off behaviors (2) incorporate appropriate design activities into their curricula. A pilot study with high school students (Purzer, Goldstein, Adams, Xie, & Nourian, 2015; Goldstein et al., 2015) showed that there are variations in how students demonstrate balancing benefits and tradeoffs in making design decisions. A second pilot investigated the connection between student reflection and informed design through quantitative analysis (Goldstein et al., 2015b), laying the groundwork for understanding student design decision-making rationale through reflections. A third pilot study (Goldstein et al., 2015c) demonstrated how micro-level process data (e.g., student clickstream data) can be used to validate outsider observations of student design. I propose one specific aim – to unpack and elaborate on how student designers characterize trade-off decisions in design through the following research questions: Research Question 1: What is the relationship between design artifact trade-off value and profiles of design behaviors that differentiate design students? Research Question 2: What do student reflections tell us about how student characterize their design decisions? What relationship exists between the degree of trade-off in the reflections and final artifact trade-off value? Research Question 3: How do students prioritize making trade-offs as contributing to a quality design solution? What relationship exists between their prioritization and final artifact trade-off value?
Goldstein, M. H. (2017, June), Board # 113 : EEGRC Poster: Characterizing Trade-off Decisions in Student Designers Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--27694
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