Exploring Agency in Capstone Design Problem Framing

• Published in: Studies in engineering education (Blacksburg, Va.) Vol. 2; no. 2; p. 96
• Main Authors: Svihla, Vanessa, Peele-Eady, Tryphenia, Gallup, Amber
• Format: Journal Article
• Language: English
• Published: VT Publishing 21.12.2021
• Subjects: agency; capstone design; design learning; opportunity structure
• ISSN: 2690-5450; 2690-5450
• DOI: 10.21061/see.69

Background: Because of prior experience solving well-structured problems that have single, correct answers, students often struggle to direct their own design work and may not understand the need to frame ill-structured design problems. Purpose: Framing agency—defined as making decisions that are consequential to framing design problems and learning through this process—sheds light on students’ treatment of design problems; by framing, we mean the various actions designers take to understand, define, and bound the problem. Using the construct framing agency, we sought to characterize design team discourse to detect whether students treated design problems as ill- or well-structured and examine the consequences of this treatment. Method: Data were collected through extended participant observation of a capstone design course in a biomedical engineering program at a large research university. Data included audio and video records of design team meetings over the course of framing and solving industry-sponsored problems. For this paper, we analyzed three cases using sociolinguistic content analysis to characterize framing agency and compared the cases to illuminate the nuances of framing agency. Results: All teams faced impasses; one team navigated the impasse by framing the problem, whereas the others treated the problem as given. We identified markers of agency in students’ discourse, including tentative language, personal pronouns, and sharing ownership. Conclusions: Framing agency clarifies the kinds of learning experiences students need in order to overcome past experiences dominated by solving archetypical well-structured problems with predetermined solutions.