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1. Factors Contributing to the Problem-Solving Heuristics of Civil Engineering Students

   Geston, Sean L. ; Brown, Shane ; Barner, Matthew S. ; Abadi, Masoud G. ; Hurwitz, David S. ( January 2019 , ASEE annual conference & exposition)

   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. 

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2. Traffic Signal Phasing Problem-Solving Rationales of Professional Engineers Developed from Eye-Tracking and Clinical Interviews

   https://doi.org/10.1177/0361198119837506  

   Ghodrat Abadi, Masoud ; Gestson, Sean L. ; Brown, Shane ; Hurwitz, David S. ( March 2019 , Transportation Research Record: Journal of the Transportation Research Board)

   There is a lack of knowledge on the way transportation engineering practitioners engage with various Contextual Representations (CRs) to solve traffic engineering design problems. CRs such as equations, graphs, and tables could be perceived differently, even if they represent the same concept. The present study recognized left-turn treatment at signalized intersections as a prominent concept in traffic engineering practice and identified three associated CRs (a text-book equation, a graphical representation, and a stepwise flowchart) to design a phasing plan. Two data collection mechanisms were concurrently employed: 1) eye-tracking to analyze visual attention and document problem-solving approaches and 2) reflective clinical interviews to analyze ways of thinking and document problem-solving rationales. The problem-solving experiment was completed by twenty-four transportation engineering practitioners. Transportation engineering practitioners not only demonstrated preferences for different CRs, they also demonstrated different reasoning as to the selection of the same CR. Results of Multivariate Analysis of Variance showed that there was a statistically significant difference in visual attention based on CR. Additionally, in-vivo coding of participants’ interviews identified seven distinct rationales for CR selection. Findings from this study could be employed to modify transportation engineering curricula with optimized visual CRs.

    

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3. Problem Solving Personas of Civil Engineering Practitioners Using Eye Tracking Techniques

   Gestson, Sean L. ; Barner, Mathew S. ; Abadi, Masoud G. ; Hurwitz, David S. ; Brown, Shane ( January 2019 , International journal of engineering education)

   Engineering practitioners solve problems in various ways; it is plausible that they often rely on graphs, figures, formulas and other representations to reach a solution. How and why engineering practitioners use representations to solve problems can characterize certain problem-solving behaviors, which can be used to determine particular types of problem solvers. The purpose of this research was to determine the relationship between time spent referring to various representations and the justifications for the decisions made during the problem-solving process of engineering practitioners. A persona-based approach was used to characterize the problem-solving behavior of 16 engineering practitioners. Utilizing eye tracking and retrospective interview techniques, the problem-solving process of engineering practitioners was explored. Three unique problem-solver personas were developed that describe the behaviors of engineering practitioners; a committed problem solver, an evaluative problem, and an indecisive problem solver. The three personas suggest that there are different types of engineering practitioner problem solvers. This study contributes to engineering education research by expanding on problem-solving research to look for reasons why decisions are made during the problem-solving process. Understanding more about how the differences between problem solvers affect the way they approach a problem and engage with the material presents a more holistic view of the problem-solving process of engineering practitioners. 

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4. The Affordance of Computer-Supportive Collaborative Learning in a Dynamics Course

   Lee, Y. ( July 2021 , Zone 1 Conference of the American Society for Engineering Education)

   null (Ed.)

   Over the past two decades, educators have used computer-supported collaborative learning (CSCL) to integrate technology with pedagogy to improve student engagement and learning outcomes. Researchers have also explored the diverse affordances of CSCL, its contributions to engineering instruction, and its effectiveness in K-12 STEM education. However, the question of how students use CSCL resources in undergraduate engineering classrooms remains largely unexplored. This study examines the affordances of a CSCL environment utilized in a sophomore dynamics course with particular attention given to the undergraduate engineering students’ use of various CSCL resources. The resources include a course lecturebook, instructor office hours, a teaching assistant help room, online discussion board, peer collaboration, and demonstration videos. This qualitative study uses semi-structured interview data collected from nine mechanical engineering students (four women and five men) who were enrolled in a dynamics course at a large public research university in Eastern Canada. The interviews focused on the individual student’s perceptions of the school, faculty, students, engineering courses, and implemented CSCL learning environment. The thematic analysis was conducted to analyze the transcribed interviews using a qualitative data analysis software (Nvivo). The analysis followed a six step process: (1) reading interview transcripts multiple times and preliminary in vivo codes; (2) conducting open coding by coding interesting or salient features of the data; (3) collecting codes and searching for themes; (4) reviewing themes and creating a thematic map; (5) finalizing themes and their definitions; and (6) compiling findings. This study found that the students’ use of CSCL resources varied depending on the students’ personal preferences, as well as their perceptions of the given resource’s value and its potential to enhance their learning. For example, the dynamics lecturebook, which had been redesigned to encourage problem solving and note-taking, fostered student collaborative problem solving with their peers. In contrast, the professor’s example video solutions had much more of an influence on students’ independent problem-solving processes. The least frequently used resource was the course’s online discussion forum, which could be used as a means of communication. The findings reveal how computer-supported collaborative learning (CSCL) environments enable engineering students to engage in multiple learning opportunities with diverse and flexible resources to both address and to clarify their personal learning needs. This study strongly recommends engineering instructors adapt a CSCL environment for implementation in their own unique classroom context. 

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5. Divergent thinking in engineering: Diverse exploration is key to successful project outcomes

   Murphy, L. ( July 2022 , 2022 ASEE Annual Conference & Exposition)

   Engineers have the power to drive innovation and rethink the way the world is designed. However, a key practice often absent from engineering education is facilitating innovation and considering diverse perspectives through divergent thinking. We define divergence in engineering practices as exploring multiple alternatives in any stage of engineering processes. Currently, engineering education and research focuses on divergence primarily in the generation and development of design solutions, supported by idea generation methods such as Brainstorming and Design Heuristics. But in practice, there are many other opportunities throughout an engineering project where engineers may find it useful to explore multiple alternatives. When does divergent thinking take place during engineering problem solving as it is currently practiced? We conducted 90-minute semi-structured interviews with mechanical engineering practitioners working in varied setting to elicit their experiences with divergent thinking taking place in their engineering projects. The initial results document divergent thinking in six different areas of engineering design processes: 1) problem understanding, 2) problem-solving methods and strategies, 3) research and information gathering, 4) stakeholder identification, 5) considering potential solutions, and 6) anticipating implications of decisions. These findings suggest engineers find divergent thinking useful in multiple areas of engineering practice, and we suggest goals for developing divergent thinking skills in engineering education. 

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