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Board 29: The Impact of Metacognitive Instruction on Students' Conceptions of Learning and their Self-monitoring Behaviors

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

14

Permanent URL

https://peer.asee.org/29999

Download Count

23

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Paper Authors

biography

Patrick J. Cunningham Rose-Hulman Institute of Technology

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Patrick Cunningham is an Associate Professor of Mechanical Engineering at Rose-Hulman Institute of Technology. During the 2013-14 academic year he spent a sabbatical in the Department of Engineering Education at Virginia Tech. Dr. Cunningham's educational research interests are student metacognition and self-regulation of learning and faculty development. His disciplinary training within Mechanical Engineering is in dynamic systems and control with applications to engine exhaust aftertreatment.

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Holly M. Matusovich Virginia Tech

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Dr. Matusovich is an Associate Professor in Virginia Tech’s Department of Engineering Education. She has her doctorate in Engineering Education and her strengths include qualitative and mixed methods research study design and implementation. She is/was PI/Co-PI on 10 funded research projects including a CAREER grant. She has won several Virginia Tech awards including a Dean’s Award for Outstanding New Faculty. Her research expertise includes using motivation and related frameworks to study student engagement in learning, recruitment and retention in engineering programs and careers, faculty teaching practices and intersections of motivation and learning strategies.

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Chris Venters East Carolina University

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Chris Venters is an Assistant Professor in the Department of Engineering at East Carolina University in Greenville, North Carolina, USA. He teaches introductory courses in engineering design and mechanics and upper-level courses in fluid mechanics. He earned his Ph.D. in Engineering Education from Virginia Tech in 2014, and his research primarily focuses on conceptual understanding in engineering mechanics courses. He received his M.S. in Aerospace Engineering from Virginia Tech and his B.S. in Aerospace Engineering from North Carolina State University.

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Sarah Anne Blackowski Virginia Tech

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Sarah is a PhD student in the Department of Engineering Education at Virginia Tech. She has a bachelor's degree in Aerospace Engineering from Embry-Riddle Aeronautical University and, during that time, spent a summer at Franklin W. Olin College of Engineering for an REU in engineering education. Sarah's research interests include: motivation, student and faculty metacognition, and engineering faculty self-regulated learning.

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Sreyoshi Bhaduri Virginia Tech

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Sreyoshi Bhaduri recently graduated with a Ph.D.in Engineering Education from Virginia Tech. She has an M.S. in Mechanical Engineering, and an M.A. in Data Analytics and Applied Statistics (DAAS) both from Virginia Tech. Sreyoshi's research interests include working on innovative research designs for analyzing varied datasets and presenting the results of these analyses to various stakeholders through meaningful and easily interpretable visualizations. Sreyoshi was recognized during her time at Virginia Tech as a Diversity Scholar, was a part of the Global Perspectives Program (GPP-2013), served as a Fellow of the Academy for Graduate Teaching Excellence (VT-GrATE), and was inducted into the prestigious Bouchet Graduate Honor Society.

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Abstract

Metacognition involves the knowledge and regulation of one’s thinking processes, and, therefore one’s learning. The quality of metacognitive knowledge and the accuracy of self-monitoring directly impacts metacognitive skill and the effectiveness and efficiency of learning. In particular, one’s approaches to learning are entangled with one’s views on the nature of knowledge and learning. Natural development of metacognitive knowledge and skills is inefficient and often leaves gaps and inaccuracies in the resulting mental models of learning processes. Further, self-monitoring is plagued by misattributions and inaccuracies related to poor evidence for these judgements. As part of our NSF IUSE grant we developed a set of modules to engage students in the intentional development of their metacognitive knowledge (e.g., improving mental models) and skills (e.g., making more accurate self-assessments) within the context of existing courses.

In this implementation we sought to understand how students’ conceptions of learning change with metacognitive instruction and how metacognitive instruction affects the alignment of students’ monitoring behaviors and their conceptions of learning. To accomplish this, we implemented metacognitive instruction within three different engineering courses corresponding to different years in school. We looked at the degree of match/mismatch between students’ conceptions of learning and their reports of how they monitor their level of understanding and their learning processes before and after the metacognition modules. We also investigated how these trends varied across year in school. We hypothesized that the effect of the metacognitive instruction modules on reported learning behaviors would depend on prior knowledge and experience with thinking about learning. Further, we hypothesized that the metacognitive instruction modules would increase the coherence between students’ conceptions of learning and students’ reported monitoring behaviors.

A series of six metacognitive instruction modules was implemented in three engineering courses; one at the Freshman level, one at the Sophomore level, and one at the Junior level. Each module consists of a video with reflection questions, an in-class activity, and a post-class assignment. The videos provided general information about metacognition, with examples from a STEM context. The in-class activity and post-class assignment were tailored to the specific class context and were designed to enhance self-awareness or practice metacognitive regulation. Pre- and post-surveys were conducted with Likert scale and free-response questions to capture students conceptions of learning and monitoring behaviors. An additional question captured students’ prior knowledge and experience with examining their learning processes. The data was de-identified and given tracking markers in order to match pre- and post-survey responses. We analyzed the data using and open-coding approach that was informed by what is already known from literature and metacognition frameworks. We focused on conceptions of learning and monitoring strategies.

Our study has implications for students and instructors. For students we make recommendations on approaches to learning that align better with their learning goals, which embody their conceptions of learning. For instructors we offer suggestions for supporting student learning and encouraging student engagement in metacognitive development.

Cunningham, P. J., & Matusovich, H. M., & Venters, C., & Blackowski, S. A., & Bhaduri, S. (2018, June), Board 29: The Impact of Metacognitive Instruction on Students' Conceptions of Learning and their Self-monitoring Behaviors Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/29999

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