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Characterization of Problem Types in Engineering Textbooks

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Conference

2022 ASEE Annual Conference & Exposition

Location

Minneapolis, MN

Publication Date

August 23, 2022

Start Date

June 26, 2022

End Date

June 29, 2022

Conference Session

ERM: Problem Solving and Conceptual Understanding

Page Count

8

DOI

10.18260/1-2--40557

Permanent URL

https://peer.asee.org/40557

Download Count

336

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Paper Authors

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David Therriault University of Florida

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David J. Therriault is an Associate Professor of Educational Psychology in the College of Education at the University of Florida. where he has been a faculty member since 2004. From 2014–2017, he held the UF Research Foundation Professorship. From 2015-2018 he held the B. O. Smith Research Professorship. He currently holds the University of Florida Research Foundation Professorship (2019-2022). His research interests lie in the area of cognitive psychology. Consequently, the bulk of his work is experimental, conducted in a laboratory setting. In all of his research, the goal is two-fold: (1) exploring fundamental cognitive processes related to learning to add to our theoretical understanding, and (2), where appropriate, applying this knowledge to improve education. An assumption underlying his research approach is that current educational issues provide investigators with some of the most compelling research topics and that rigorous empirical work aids us in making the education process more successful. He has collaborated actively with researchers in STEM disciplines outside of psychology (engineering and chemistry). Dr. Therriault currently serves as a Board Member on UF’s IRB.

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Elliot Douglas University of Florida

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Dr. Elliot P. Douglas is Professor of Environmental Engineering Sciences and Engineering Education, and Distinguished Teaching Scholar at the University of Florida. His research interests are in engineering problem solving, diversity and inclusion, and social justice for engineering ethics. Dr. Douglas has served as Associate Editor and Deputy Editor of the Journal of Engineering Education, Chair of the Educational Research & Methods Division of ASEE, and Program Director for Engineering Education at the US National Science Foundation. He received S.B. degrees from MIT in 1988 and a Ph.D. from the University of Massachusetts – Amherst in 1993.

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Emily Buten

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Emily is a recent graduate from the University of Dayton where she studied mechanical engineering. As an undergraduate researcher, she worked with the University of Florida to determine ambiguity and problem types in engineering textbook problems.

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Elizabeth Bates Michigan Technological University

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Elizabeth is a senior mechanical engineering student at Michigan Technological University. In the summer of 2021 she worked as an undergraduate researcher categorizing problem types as part of a project to identify the level of ambiguity present in engineering text book problems.

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Jeremy Waisome University of Florida

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Dr. Jeremy A. Magruder Waisome earned her bachelor's and master's of science degrees and Ph.D. in civil engineering from UF. During her studies, she became passionate about issues of equity, access, and inclusion in engineering and computing and worked to develop programs and activities that supported diverse students in these disciplines. Today, Dr. Waisome is an incoming Assistant Professor in the Department of Engineering Education where she conducts research on broadening participation in science, technology, engineering, mathematics, and computing (STEM+C). She is particularly interested in understanding how formalized mentoring programs impact student trajectories and self-efficacy. In her teaching, she utilizes the learner-centered approach to instruction.

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Marah Berry University of Florida

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Abstract

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

Beer, F., Johnston, E., & Mazurek, D. (2019). Vector mechanics for engineers: Statics New York: McGraw-Hill Education. Hibbeler, R. C. (2016). Engineering mechanics: Statics. New York: Pearson. Johnstone, A. H. (2001). Can problem solving be taught. University Chemistry Education, 5(2), 69-73. Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65-94. Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63-85. Lee, C. S., McNeill, N. J., Douglas, E. P, Koro-Ljungberg, M. E., & Therriault, D. J. (2013). Indispensable Resource? A Phenomenological Study of Textbook Use in Engineering Problem Solving. Journal of Engineering Education 102(2), 269-288. Shin, N., Jonassen, D. H., & McGee, S. (2003). Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching, 40(1), 6-33. Voss, J. (2006). Toulmin's model and the solving of ill-structured problems. In D. Hitchcock & B. Verheij (Eds.), Arguing on the Toulmin model: New essays in argument analysis and evaluation (pp. 303-311). New York: Springer.

Therriault, D., & Douglas, E., & Buten, E., & Bates, E., & Waisome, J., & Berry, M. (2022, August), Characterization of Problem Types in Engineering Textbooks Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--40557

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