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Engineering problems are ill-defined, require assumptions, and have multiple unique solutions. Although most industry engineers solve ill-defined problems in groups, students typically only practice this in engineering design courses. Our research aims to expand these experiences to engineering science courses. Currently, most engineering science courses assign 'classic' textbook problems, where they are given certain physical parameters of a system, and are told to calculate an unknown value. Ill-defined modeling problems provide students with more opportunities to utilize engineering judgment when compared to traditional textbook problems, and when these problems are solved in a group setting, it is both a better representation of how engineering is performed in the industry, and can help students better understand the class concepts. This paper examines groups of students solving an ill-defined modeling task that asks students to design a portable pool lift. When working in a group, students have the opportunity to help each other understand what was taught in class, along with the ability to push back on other students' ideas. This will prepare students for their future career, lead to knowledge creation and help solidify concepts taught in class. This full paper analyzes data (approximately 15.5 hours) that was collected in the form of recordings of zoom meetings of two groups that were tasked with solving an ill-defined modeling problem in a second year statics course. Using comparative coding, we categorized how students spent time when working in their group. Results show students alternate between negotiating tasks, comparing assumptions, and aiding each other in understanding course concepts. Implications of this work include forming a better understanding of how students make decisions, judgments and build knowledge when working together on an ill-defined modeling problem. Similarly, the results may assist professors in iterating on assignment design to further engage students in knowledge creating and engineering judgment practices. [ABSTRACT FROM AUTHOR]

Engineering problems are ill-defined, require assumptions, and have multiple unique solutions. Although most industry engineers solve ill-defined problems in groups, students typically only practice this in engineering design courses. Our research aims to expand these experiences to engineering science courses. Currently, most engineering science courses assign 'classic' textbook problems, where they are given certain physical parameters of a system, and are told to calculate an unknown value. Ill-defined modeling problems provide students with more opportunities to utilize engineering judgment when compared to traditional textbook problems, and when these problems are solved in a group setting, it is both a better representation of how engineering is performed in the industry, and can help students better understand the class concepts. This paper examines groups of students solving an ill-defined modeling task that asks students to design a portable pool lift. When working in a group, students have the opportunity to help each other understand what was taught in class, along with the ability to push back on other students' ideas. This will prepare students for their future career, lead to knowledge creation and help solidify concepts taught in class. This full paper analyzes data (approximately 15.5 hours) that was collected in the form of recordings of zoom meetings of two groups that were tasked with solving an ill-defined modeling problem in a second year statics course. Using comparative coding, we categorized how students spent time when working in their group. Results show students alternate between negotiating tasks, comparing assumptions, and aiding each other in understanding course concepts. Implications of this work include forming a better understanding of how students make decisions, judgments and build knowledge when working together on an ill-defined modeling problem. Similarly, the results may assist professors in iterating on assignment design to further engage students in knowledge creating and engineering judgment practices. [ABSTRACT FROM AUTHOR]

This research paper examines students' productive beginnings of engineering judgement while solving open-ended problems in a second-year dynamics course. Undergraduate students are typically assigned well-structured textbook problems for homework, in which the systems have already been simplified and there are few, if any, open-ended decisions to be made. Therefore, students have few opportunities in class to practice their engineering judgment until capstone design courses. We have developed a framework of the productive beginnings of engineering judgment with data from open-ended modeling problems in statics courses. In this paper we investigate how the framework transfers to open-ended modeling problems in dynamics courses. This analysis suggests our framework is transferable to dynamics courses, with all fourteen types of judgement found in the dynamics data set and no additional ways of engaging in judgement were found. [ABSTRACT FROM AUTHOR]