Exploring Student Computational Practices in Solving Complex Engineering Design Problems

Abstract

Abstract Exploring Student Computational Practices in Solving Complex Engineering Design Problems This study explores students’ experiences of computational practices to informtheir problem-solving process to accomplish a design task. In this paper we definecomputational practices as a system of activities carried out to create symbolicrepresentations, simplifications of systems or artifacts that delete, maintain and distortaspects of a phenomenon in order to support scientific inquiry and design activity.Computational tools are becoming more useful pedagogical tools because of their abilityto create and display multiple representational forms, often interactively and as a functionof time. Specifically, representational artifacts such as graphs, visual models, andsimulations of physical or non-physical phenomena can serve as tools in guiding inquiryand constructing solutions in engineering design. However, there is a limited amount ofresearch that describes the computational practices of engineering students. In particular,there is a need to investigate the differences in the way engineering students’ practicesand the way they use computational tools for developing solutions to complex designproblems beyond the first year of engineering.The research question in this particular study is: What are computational practices ofupper level engineering students for solving complex design problems? And how arethese practices implemented as part of their design process and/or supporting student’sconceptual understanding of course material? Activity theory is used as the theoretical framework for this study. Learning anddesign activities always contain artifacts (i.e., models, data, equations, procedures) thathelp individuals accomplish the goals of a particular task. Lev Vygostky’s ActivityTheory is described as consisting of three elements; the subject, mediating tools and thetask objective or outcome. In this case study, our experiment was developed such thattwo groups of participants were required to employ different computational resources(e.g., one group used a simulation while the other used a written analytical solution). Thegroups, consisting of about 5 to 8 students, were self-assigned a design problem thatinvolved similar concepts but using different analytical tools. This division of the groupsallowed for us to describe student problem solving process as a function of thecomputation resources made available to them. The qualitative component of the studyincludes an in-depth task analysis of students’ solutions (analytical or computational) andthe artifacts they produced. Participants of this study were drawn from a population of 24first and second year graduate students from a materials science engineering course titledIntroduction to Rechargeable Batteries. The final draft of this paper will describe students’ use of representations (e.g.,graphical, iconic, algebraic) as cognitive tools for processing domain-relevant knowledgeand strategies for formulating solutions. In addition, the differences in students’ use ofrepresentations using hand-written and coded methods of computing will be highlightedand discussed. The results of this study will be beneficial in expanding the current workin the role of representations for conceptual change in engineering and will provideinsights into how students process knowledge when provided with simulation tools andcomputational methods for solving design problems.