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The Sequential Nature of Engineering Problem Solving

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Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

NSF Grantees: Student Learning 2

Tagged Topic

NSF Grantees Poster Session

Page Count

15

DOI

10.18260/1-2--35372

Permanent URL

https://peer.asee.org/35372

Download Count

83

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Paper Authors

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Carolyn Plumb Montana State University

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Carolyn Plumb is the recently retired Director of Educational Innovation and Strategic Projects in the College of Engineering at Montana State University (MSU). Plumb has been involved in engineering education and program evaluation for over 25 years, and she continues to work on externally funded projects relating to engineering education.

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Rose M. Marra University of Missouri - Columbia

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Professor Rose M. Marra is the Director of the School of Information Science and Learning Technology at the University of Missouri. She is PI of the NSF-funded Supporting Collaboration in Engineering Education, and has studied and published on engineering education, women and minorities in STEM, online learning and assessment. Marra holds a PhD. in Educational Leadership and Innovation and worked as a software engineer before entering academe.

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Douglas J. Hacker

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Dr. Hacker is a full professor in the Department of Educational Psychology and participates in both the Learning Sciences Program and the Reading and Literacy Program. Prior to receiving his Ph. D. in educational psychology from the University of Washington in 1994, Dr. Hacker worked as a high school science and math teacher and then as a school counselor. From 1994 to 1999, Dr. Hacker was an assistant/associate professor in the Department of Counseling, Educational Psychology and Research at The University of Memphis. During those years, he worked in the areas of reading and writing processes, metacognition, self-regulated learning, teacher education, and school and program evaluation. Dr. Hacker moved to the University of Utah in 1999 and has continued his research in the previous areas and has added to them research in the area of the detection of deception. Also at the University of Utah, he served as chair of the Teaching and Learning Department. His publications have appeared in the Journal of Educational Psychology, Contemporary Educational Psychology, Journal of Experimental Psychology: Applied, and Journal of Experimental Education. At both universities, Dr. Hacker has maintained a strong commitment to work in elementary and middle schools, working directly with teachers by providing professional development in reading and writing instruction. Since 1994, Dr. Hacker has been either the principal investigator or co-principal investigator on grants totaling $2,548,960. He has served as an editorial board member for the Journal of Educational Psychology, Metacognition and Learning, and Frontiers of Educational Psychology. He is a former Associate Editor for the Journal of Educational Psychology.

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Abstract

The Sequential Nature of Engineering Problem Solving Iron Range Engineering (IRE) is an innovative, problem-based-learning program in Virginia, Minnesota. Part of its innovation comes from the program’s strong emphasis on developing metacognitive skills necessary for students to become self-directed learners of the knowledge and skills required for professional engineers. In our NSF IUSE project, we have been investigating the cognitive processes involved in engineering problem solving, focusing specifically on the role of metacognition. Using verbal protocol analysis, we recorded students’ utterances as they solved two engineering design problems, a pre-problem at the beginning of their engineering program and a post-problem at the end. We identified categories of utterances, some metacognitive and some non-metacognitive, and measured the frequency of those utterance categories. However, because problem solving does not reside in a single utterance nor in the frequency of utterances but rather in the sequence of the utterance categories, we examined the sequences of students’ utterances as they solved the two problems. This poster will address the sequential nature of the cognitive processes revealed in students’ utterances as they solved engineering design problems and to identify the role that metacognition plays in that sequencing. We hypothesized that as students acquired greater engineering knowledge and were exposed to greater use of metacognitive thinking and strategies that focused on that knowledge across their education at IRE, the sequencing of their utterances would indicate the following differences from the pre- to the post-problem: 1) greater sustained use of engineering knowledge when solving the post-problem; 2) increased metacognitive monitoring occurring before and after the use of engineering knowledge on the post-problem; 3) greater elaboration of solutions on the post-problem; 4) increased metacognitive monitoring before and after providing solutions on the post-problem; 5) greater use of metacognitive knowledge of strategies on the post-problem. A lag-one sequential analysis (i.e., an utterance [lag 0] directly followed by another utterance [lag 1]) was conducted by producing three matrices for each of the 11 participants for the pre- and post-problems: a frequency matrix showing the frequency of lag-one transitions; a transitional matrix showing the probability of a particular category of utterance occurring given that a specific category of utterance had occurred; and a z-score matrix produced from each frequency matrix showing what sequence transitions significantly differed from chance. We averaged the z-score matrices across students’ pre- and post-problems and computed a χ2 statistic to analyze differences between the two. Our results are preliminary, but the χ2 was significant. We found support for hypotheses 1, 3, and 5, partial support for hypothesis 2, and no support for hypothesis 4. From pre- to post-problems, students increased their use of engineering knowledge, elaborated their solutions, made greater use of their metacognitive knowledge of strategies, and made greater use of metacognitive monitoring before but not after the use of their engineering knowledge. Metacognitive monitoring remained stable before a solution but decreased after a solution. The IRE program showed positive growth in both students’ engineering knowledge and in their metacognitive use of that knowledge.

Plumb, C., & Marra, R. M., & Hacker, D. J. (2020, June), The Sequential Nature of Engineering Problem Solving Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35372

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