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The Effects of Verbal Interactions on Individual and Team Performance in Engineering Design

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016





Conference Session

Student Teams, Groups, and Collaborations

Tagged Division

Educational Research and Methods

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Paper Authors


Muhsin Menekse Purdue University, West Lafayette

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Muhsin Menekse is an assistant professor at the School of Engineering Education at Purdue University, with a joint appointment at the Department of Curriculum & Instruction. Dr. Menekse’s primary research investigates how classroom activities affect conceptual understanding in engineering and science for all students. His second research focus is on verbal interactions that can enhance productive discussions in collaborative learning settings. And his third research focus is on metacognition and its implications for learning. Much of this research focuses on learning processes in classroom settings. Dr. Menekse is the recipient of the 2014 William Elgin Wickenden Award by the American Society for Engineering Education.

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Senay Purzer Purdue University, West Lafayette Orcid 16x16

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Ṣenay Purzer is an Associate Professor in the School of Engineering Education. Her research examines how engineering students approach innovation. She also studies informed design practices among college and pre-college students . She serves on the editorial boards of Science Education and the Journal of Pre-College Engineering Education (JPEER).

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The Effects of Verbal Interactions on Individual and Team Performance in Engineering Design

Solving real-world problems requires interpreting data and making decisions effectively. Problem solving and decision-making process become more complex when decisions are made in small group settings. Group interactions and discourse processes can facilitate learning with reflection and co-construction of knowledge (e.g., Chi & Menekse, 2015; Purzer, 2011). However, these verbal interactions may also prevent successful collaboration and lead to unproductive results (e.g., Kuhn, 2015).

In this study, the fundamental goal was to explore how verbal interactions influence discourse patterns, and relate to individual and team performance in the context of an introductory engineering design course. Engineering Design courses address the open ended and ill-structured nature of design in project based context by introducing the idea of integration of the disciplines, people, and resources within engineering and beyond that are necessary to achieve optimal design solutions for products, systems, processes, and services. 

73 students in 19 teams, each composed of three or four engineering students, were presented with a design challenge, and three possible design options. The task asked student teams to decide on the best system to reduce the energy consumption and cost of a town library (adding solar panels, installing a green roof, or making no changes to existing design) and make a recommendation to the client. As a team, students were responsible to describe their problem scoping, specify a plan and/or process, explain the formulae for total system cost, construct a graphical representation of 10-year cost for all current and new systems, and finalize the decisions and justifications in 60 minutes. Students were video-recorded during the design task. They also produced brief reports indicating calculations, data for each design option, and their decision with a rationale.

We coded students verbal interactions based on episodes of group conceptual knowledge elaboration. Students’ verbal data, segmented by the topic discussed, were coded as question, conflict, or reasoning episodes. Two coders independently watched and listened teams’ discussions and coded for episodes and subcategories of each episode. The coders identified: (1) an opening utterance as a specific episodic category based on the definitions presented below, (2) other members’ reactions to the opening utterance (generally an answer, co-construction, or elaboration), and (3) the end of an episode (generally when the specific topic or problem is concluded or agreed upon).

Our analysis showed that the linear combination of three types of episodes was significantly related to the individual performance F(3, 69) = 3.57, p < .05, r2 = .14, with a sample multiple correlation coefficient of .37. In addition, among three types of verbal moves, the question episodes were the significant predictor of students’ performance, beyond other two types of episodes. Also, “asking questions” was slightly a better predictor than “answering questions” for student performance. On the other hand, results for team level performance were mixed: First, the reasoning episodes was negatively correlated r(17) = -.42 p < .05 . Second, the question episodes was positively correlated r(17) = .35 p = .07, but this correlation was not significant at .05 alpha level. And third, there was no meaningful relation between the conflict episodes and team performance. We are currently conducting multilevel analysis by employing two-level hierarchical linear models (HLM) - individual variables as level 1 & team variables as level 2. For the fully unconditional model, interclass correlation coefficient is .12, which indicates 12% of the variance is at group level, and the remaining 88% is at individual level. As the next step, we will explore to what degree HLM analysis change our current findings.

Menekse, M., & Purzer, S. (2016, June), The Effects of Verbal Interactions on Individual and Team Performance in Engineering Design Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.26149

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