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Special Session: Model Eliciting Activities: A Construct For Better Understanding Student Knowledge And Skills

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Conference

2010 Annual Conference & Exposition

Location

Louisville, Kentucky

Publication Date

June 20, 2010

Start Date

June 20, 2010

End Date

June 23, 2010

ISSN

2153-5965

Conference Session

Special Session: Next Generation Problem-Solving

Tagged Division

Educational Research and Methods

Page Count

14

Page Numbers

15.1085.1 - 15.1085.14

Permanent URL

https://peer.asee.org/16662

Download Count

32

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Paper Authors

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Tamara Moore University of Minnesota Orcid 16x16 orcid.org/0000-0002-7956-4479

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Tamara J. Moore is an Assistant Professor of Mathematics/Engineering Education and co-director of the STEM Education Center at the University of Minnesota. Dr. Moore is a former high school mathematics teacher and her research interests are centered on the integration of STEM concepts through contextual problem solving in the mathematics and engineering classroom. She has been developing curricular tools and researching professional development and student learning in this area. Before coming to the University of Minnesota, Dr. Moore received her Ph.D. from the School of Engineering Education at Purdue University.

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Brian Self California Polytechnic State University

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Brian Self is a Professor in the Mechanical Engineering Department at California Polytechnic State University in San Luis Obispo. Prior to joining the faculty at Cal Poly in 2006, he taught for seven years at the United States Air Force Academy and worked for four years in the Air Force Research Laboratories. Research interests include active learning and engineering education, spatial disorientation, rehabilitation engineering, sports biomechanics, and aerospace physiology. He worked on a team that developed the Dynamics Concept Inventory and is currently collaborating on a grant to develop and assess Model Eliciting Activities in engineering. Brian is the 2008-2010 ASEE Zone IV Chair and serves as Cal Poly’s ASEE Campus Representative.

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Margret Hjalmarson George Mason University

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Margret A. Hjalmarson is an Assistant Professor in the Graduate School of Education at George Mason University. She received her B.A. in mathematics at Mount Holyoke College, and her Masters mathematics and Ph. D. in mathematics education at Purdue University. She currently coordinates the Mathematics Education Leadership program for K-8 mathematics specialists and Ph.D students in mathematics education. She works with engineers to study the learning of mathematics in engineering education contexts. She also works in mathematics teacher professional development and design research related to students’ learning of mathematics.

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Judith Zawojewski Illinois Institute of Technology

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Judith S. Zawojewski is an Associate Professor in the Department of Mathematics and Science Education at Illinois Institute of Technology in Chicago, IL. She received her B.S. in mathematics and education at Northwestern University, and her Masters and Ph. D. degrees in mathematics education at National-Louis University and Northwestern University respectively. She works with teachers of mathematics and engineering educators who are interested in improving the learning and teaching of mathematics in their educational environment. In particular, she is studies the role of modeling and problem solving in developing mathematical capabilities.

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Barbara Olds Colorado School of Mines

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Ronald Miller Colorado School of Mines

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Ronald L. Miller is professor of chemical engineering and Director of the Center for Engineering Education at the Colorado School of Mines where he has taught chemical engineering and interdisciplinary courses and conducted engineering education research for the past 24 years. Dr. Miller has received three university-wide teaching awards and has held a Jenni teaching fellowship at CSM. He has received grant awards for education research from the National Science Foundation, the U.S. Department of Education FIPSE program, the National Endowment for the Humanities, and the Colorado Commission on Higher Education and has published widely in the engineering education literature.

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Heidi Diefes-Dux Purdue University

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Richard Lesh Indiana University

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Richard Lesh, Professor of Learning Science and Director of Center for Research on Learning and Technology at Indiana University, is the creator of Model-Eliciting Activities and a leading researcher in the area of implementing models and modeling inn STEM curriculum – particularly in mathematics, research methodologies, and complex assessment systems.

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Model-Eliciting Activities: A Construct For Better Understanding Student Knowledge and Skills

Introduction

The ABET criteria for engineering programs include that students should have “an ability to apply mathematics, science and engineering”, “an ability to design a system, component, or process to meet desired needs”, “an ability to identify, formulate and solve engineering problems”, and “an ability to communicate effectively”, and “a knowledge of contemporary issues”1. One manner of integrating teamwork and engineering contexts in undergraduate engineering is through the educational construct of Model-Eliciting Activities (MEAs). MEAs are a class of interdisciplinary problems designed to simulate authentic, client-driven situations in classroom settings. MEAs allow teachers and researchers to observe student development of conceptual models by requiring students to make their models explicit through design-test-revise cycles. The solution of an MEA requires the use of one or more mathematical or engineering concepts that are unspecified by the problem - students must make new sense of their existing knowledge and understandings to formulate a generalizable mathematical model that can be used by the client to solve the given and similar problems. An MEA creates an environment in which skills beyond mathematical abilities are valued because the focus is not on the use of prescribed equations and algorithms but on the use of a broader spectrum of skills required for effective engineering problem solving. Carefully constructed MEAs can begin to prepare students to communicate and work effectively in teams; to adopt and adapt conceptual tools; to construct, describe, and explain complex systems; and to cope with complex systems. MEAs provide a learning environment that is tailored to a more diverse population than typical engineering course experiences as they allow students with different backgrounds and values to emerge as talented, and that adapting these types of activities to engineering courses has the potential to go beyond “filling the gaps” to “opening doors” to women and underrepresented populations in engineering. Further, MEAs provide evidence of student development in regards to ABET standards. MEAs are particularly useful for implementation in engineering training as they promote creative problem solving, application of interdisciplinary knowledge, and teamwork.

This paper will present four cases of research on student learning through MEAs developed and assessed through an NSF-funded grant, Collaborative Research: Improving Engineering Students’Learning Strategies Through Models and Modeling. We have added a secondary title, Modeling: Elicitation, Development, Integration, and Assessment (MEDIA) Project, to more easily describe the work that we are doing. The MEDIA Project is a large-scale, four-year collaborative research project between seven major universities: University of Pittsburgh, University of Minnesota, US Air Force Academy, Colorado School of Mines, Purdue University, Pepperdine University, and California Polytechnic State University, through which we are working to develop, assess, and evaluate MEAs in undergraduate engineering courses, especially focusing on second and third year courses.

Moore, T., & Self, B., & Hjalmarson, M., & Zawojewski, J., & Olds, B., & Miller, R., & Diefes-Dux, H., & Lesh, R. (2010, June), Special Session: Model Eliciting Activities: A Construct For Better Understanding Student Knowledge And Skills Paper presented at 2010 Annual Conference & Exposition, Louisville, Kentucky. https://peer.asee.org/16662

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