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Situated cognition theory suggests that representations of concepts are products of the environment wherein we learn and apply concepts. This research builds on situated cognition by investigating how concepts are tangible to a professional engineering environment.

The tangibility of concepts in relation to social and material contexts was defined and explored in this study. Specifically, the conceptual representations of structural loads were examined within workplace and academic environments.

A researcher conducted ethnographic fieldwork at a private engineering firm and in undergraduate engineering courses. Data sources from this fieldwork included the ethnographer's participant‐observation field notes, formal and informal interviews, and artifact documentation.

Findings from this study described how academic representations of structural loads are more or less tangible to the social and material contexts of engineering practice. Representations documented in the workplace were found to be tangible to (1) real‐world conditions, (2) project/stakeholder constraints, and (3) engineering tools. Conversely, representations documented in the courses studied exhibited various degrees of tangibility to none, some, or all of these three traits.

These findings explicitly identify the ways in which representations of structural loads differ across academic and workplace environments and how these differences may contribute to the education–practice gap. Specific suggestions for making academic representations more tangible to workplace environments are provided based on findings from in the workplace, previous engineering education literature, and best practices observed in the courses studied. Future research considerations and the value of ethnographic methodology to situated cognition theory are also discussed.

 

Problem solvers vary their approaches to solving problems depending on the context of the problem, the requirements of the solution, and the ways in which the problems and material to solve the problem are represented, or representations. Representations take many forms (i.e. tables, graphs, figures, images, formulas, visualizations, and other similar contexts) and are used to communicate information to a problem solver. Engagement with certain representations varies between problem solvers and can influence design and solution quality. A problem solver’s evaluation of representations and the reasons for using a representation can be considered factors in problem-solving heuristics. These factors describe unique problem-solving behaviors that can help understand problem solvers. These behaviors may lead to important relationships between a problem solver’s decisions and their ability to solve a problem and overall quality of the solution. Therefore, we pose the following research question: How do factors of problem-solving heuristics describe the unique behaviors of engineering students as they solve multiple problems? To answer this question, we interviewed 16 undergraduate engineering students studying civil engineering. The interviews consisted of a problem-solving portion that was followed immediately by a semi-structured retrospective interview with probing questions created based on the real time monitoring of the problem-solving interview using eye tracking techniques. The problem-solving portion consisted of solving three problems related to the concept of headloss in fluid flow through pipes. Each of the three problems included the same four representations that were used by the students as approaches to solving the problem. The representations are common ways to present the concept of headloss in pipe flow and included two formulas, a set of tables, and a graph. This paper presents a set of common reasons for why decisions were made during the problem-solving process that help to understand more about the problem-solving behavior of engineering students. 

This paper presents the preliminary findings of a larger study on the problem-solving rationale associated with the use of multiple contextual representations. Four engineering practitioners solved a problem associated with headloss in pipe flow while their visual attention was tracked using eye tracking technology. Semi-structured interviews were conducted following the problem-solving interview and the rationale associated with their decisions to use a particular contextual representation emerged. The results of this study show how the rationale can influence the problem-solving process of the four engineering practitioners. Engineering practitioners used various contextual representations and provided multiple rationale for their decisions. Eye tracking techniques and semi-structured interviews created a robust picture of the problem-solving process that supplements previous problem-solving research.