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Assessing Mechanistic Reasoning: Leveraging Systems Thinking

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2018 ASEE Mid-Atlantic Section Spring Conference


Washington, District of Columbia

Publication Date

April 6, 2018

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April 6, 2018

End Date

April 7, 2018

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Paul Jason Weinberg Oakland University

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Dr. Paul J. Weinberg is an Assistant Professor of Mathematics and Science Education at Oakland University (Rochester, MI), where he teaches methods courses for pre- and in-service secondary mathematics teachers. In addition, he teaches mathematics content courses, in the Department of Mathematics and Statistics, for elementary education majors. Dr. Weinberg’s research focuses on students’ reasoning within STEM disciplines, in the context of schooling; this focus has principally been in the field of engineering. He is interested in ways of characterizing and developing disciplinary practices (e.g., mechanistic reasoning) in K-12 classrooms in order to promote and support disciplined inquiry. He has published his research in the Journal of Pre-College Engineering Education Research (J-PEER), Cognition and Instruction, and ZDM: The International Journal on Mathematics Education. In addition, Dr. Weinberg has coauthored a book, The First-Year Urban High School Teacher, focusing on the challenges of supporting teaching and learning in the nation’s highest poverty schools and districts. He has recently begun a research study that will supports mechanistic reasoning through mathematical description in a 3rd grade after-school engineering program. Dr. Weinberg received a doctorate, with a focus on Mathematics and Science Education, from Peabody’s College of Education and Human Development at Vanderbilt University in 2012.

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Reasoning about mechanism is central to disciplined inquiry in science and engineering and should thus be one of the foundations of a STEM (Science Technology Engineering and Mathematics) education. In addition, mechanistic reasoning is one of the core competencies listed in the Next Generation Science Standards (NGSS) Engineering Concepts and Practices (NGSS Lead States, 2013). Mechanistic explanations focus on the processes that underlie cause-effect relationships and take into account how the activities of system components affect one another.

While some assessment work has been accomplished in engineering education, to date mechanistic reasoning is an area where limited assessment development has been accomplished for pre-college populations. The data in this study come from the calibration of the Assessment of Mechanistic Reasoning Project (AMRP) (Weinberg, 2012), designed to diagnose individuals' mechanistic reasoning about systems of levers. This assessment presents a domain-specific characterization of mechanistic reasoning and illuminates what is easy and difficult about this form of reasoning. The study participants included elementary, middle, and high school students as well as college undergraduates and adults without higher education. Within this calibration study, item analyses, reliability, and validity measures were conducted using Item Response Theory (IRT) modeling; the AMRP assessment was found to have high reliability and validity. In addition, this study shows that machine characteristics such as number of levers, lever type, and arrangement of levers can affect the difficulty of mechanistic reasoning.

Weinberg, P. J. (2018, April), Assessing Mechanistic Reasoning: Leveraging Systems Thinking Paper presented at 2018 ASEE Mid-Atlantic Section Spring Conference, Washington, District of Columbia. 10.18260/1-2--29457

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