Ill-structured problems, problems that do not have simple structures and one finite correct solution, are the most common form of problems that engineers meet in everyday situations. However, because ill-structured problems and well-structured problems differ in many aspects, the curriculum of engineering education mostly focuses on well-structured problems, leading to the possibility that students might not apply the knowledge they have learned from school to the workplace after they graduate. Problem-based learning using ill-structured problems is more effective in teaching students to approach a solution for a task in a more expert-like way, by, for example, using analogical reasoning. In this study, novice participants who are majoring in Engineering and expert participants who are in the Civil or Mechanical Engineering fields are asked to solve ill-structured problems. The focus of analysis will be on the different types of analogies they use. Self-Efficacy will also be measured using a survey to observe if different levels of self-efficacy affect problem solving differently in the two groups, and if there is any relationship between types of analogies that each groups use and self-efficacy. The findings of this study would help to improve the curriculum of engineering education especially enhancing students’ cognitive strategy for engineering designs. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/28119 |
| Date | 20 January 2015 |
| Creators | Heo, Damji |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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