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  1. Abstract— Engineers are frequently confronted with complex, unique, and challenging problems. Many of our most pressing engineering problems contain ambiguous elements, and a core activity of engineering is being able to solve these complex problems effectively. While engineering problems are often described as ambiguous, ambiguity has not been clearly defined in the literature in the context of engineering problem solving. This work-in-progress paper describes our initial results to understand how ambiguity is experienced during engineering problem solving. We interviewed both engineering students and engineering professionals about ambiguous problems they have encountered. We found that both groups identified technical ambiguity as the core element of engineering problem solving. They also described differences between classroom and workplace problems, with students describing classroom problems as “purposefully” ambiguous. Students had strong negative emotional reactions to ambiguity, in contrast to professionals who seemed to accept ambiguity as a common element in engineering problem. Our initial findings suggest that changes to engineering education practice that allow students to become comfortable with ambiguity would better prepare them for the ambiguous problems they will face in the workplace. Keywords—problem solving, ambiguity, qualitative 
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  2. This work in progress research paper considers the question, what kind of problems do engineering students commonly solve during their education? Engineering problems have been generally classified as ill-structured/open-ended or well-structured/closed-ended. Various authors have identified the characteristics of ill-structured problems or presented typologies of problems. Simple definitions state that well-structured problems are simple, concrete, and have a single solution, while ill-structured problems are complex, abstract, and have multiple possible solutions (Jonassen, 1997, 2000). More detailed classifications have been provided by Shin, Jonassen, and McGee (2003), Voss (2006), and Johnstone (2001). It is commonly understood that classroom problems are well-structured while workplace problems are ill-structured, but we cannot find any empirical data to confirm or deny this proposition. Engineers commonly encounter ill-structured problems such as design problems in the field therefore problem-solving skills are invaluable and should be taught in engineering courses. This research specifically looks at the types of problems present in the two most commonly used statics textbooks (Hibbeler, 2016; Beer, et al., 2019). All end-of-chapter problems in these textbooks were classified using Jonassen’s (2000) well-known typology of problem types. Out of 3,387 problems between both books, 99% fell into the algorithmic category and the remaining fell into the logic category. These preliminary results provide an understanding of the types of problems engineering students most commonly encounter in their classes. Prior research has documented that textbook example problems exert a strong influence on students' problem-solving strategies (Lee et al., 2013). If instructors only assign textbook problems, students in statics courses do not see any ill-structured problems at that stage in their education. We argue that even in foundational courses such as statics, students should be exposed to ill-structured problems. By providing opportunities for students to solve more ill-structured problems, students can become more familiar with them and become better prepared for the workforce. Moving forward, textbooks from several other courses will be analyzed to determine the difference between a fundamental engineering course such as statics and upper-level courses. This research will allow us to determine how the problem types differ between entry level and advanced classes and reveal if engineering textbooks primarily contain well-structured problems. Keywords: problem solving, textbooks, ill-structured problems 
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  3. null (Ed.)
    Abstract— In this Work in Progress Research paper, we present preliminary results on the analysis of the problems present in a common engineering textbook. In order to transition students from novice to expert problem solving, they must have practice solving problems that are typical of engineering practice, i.e. illstructured and complex. While it is generally believed that classroom problems are for the most part closed-ended and not complex, there is no work in the literature to confirm this belief. In order to address this gap, we analyzed the types of problems present in a commonly used statics textbook, using Jonassen’s well-known typology. Our findings show that almost all of the problems are algorithmic, with a few rule-based and story problems. There were no problems with higher levels of illstructuredness, such as decision-making, diagnosis-solution, or design problems. Some educators may believe that because statics is an introductory level class, it is appropriate to only present wellstructured problems. We argue that it is both possible and necessary to include ill-structured problems in classes at all levels. Doing so could potentially support students’ critical transition from novice to expert problem solvers. Keywords—problem-solving, statics, ambiguity 
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  4. This work in progress paper poses the research question: what are the qualitatively different ways that novice and expert engineers experience ambiguity? Engineers are frequently confronted with complex, unique, and challenging problems. Many of our most pressing engineering problems contain ambiguous elements, and a core activity of engineering is solving these complex problems effectively. We present a pilot study consisting of four in-depth interviews with senior civil engineering students. The data collection is ongoing; therefore, our results are not complete. Some preliminary categories of ambiguity have been identified. Once the data set is complete, we will analyze it using phenomenography in order to better understand the variations in these individuals’ experiences of ambiguity in engineering problem solving. 
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