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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.
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Traffic Signal Phasing Problem-Solving Rationales of Professional Engineers Developed from Eye-Tracking and Clinical Interviews
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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- Award ID(s):
- 1463769
- PAR ID:
- 10124328
- Date Published:
- Journal Name:
- Transportation Research Record: Journal of the Transportation Research Board
- Volume:
- 2673
- Issue:
- 4
- ISSN:
- 0361-1981
- Page Range / eLocation ID:
- 685 to 696
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1177/0361198119837506
