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Chapter 23 - Preparing Engineering Educators for Engineering Education Research
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- By Maura Borrego, Virginia Tech, Ruth A. Streveler, Purdue University
- Edited by Aditya Johri, Virginia Polytechnic Institute and State University, Barbara M. Olds
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- Book:
- Cambridge Handbook of Engineering Education Research
- Published online:
- 05 February 2015
- Print publication:
- 10 February 2014, pp 457-474
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- Chapter
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Summary
Introduction
The engineering profession is facing un-precedented challenges arising from globalization, poor public image, and low interest among students. To solve problems in sustainability, climate change, civil infrastructure, energy, and public health, the enterprise of engineering education must attract and retain a diverse group of students while preparing them to solve complex problems (Borri & Maffioli, 2007; Duderstadt, 2008; King, 2008). Clearly, this challenge requires effort from a wide range of stakeholders in industry, government, and both the teaching and research missions of academia.
In this chapter, we focus on research as just one position on a spectrum of in-quiry activities that advances the collective goals of quality education of engineers. We seek not simply to distinguish engineering education research from other education-related activities, but to situate many teaching, assessment, evaluation, inquiry, and research activities with respect to each other and their complementary aims. We hope to convey to readers the benefits and limitations of each, as well as the necessity of efforts across the spectrum. Anyone with concern for the future of engineering education can contribute in a systematic way that will help to move collective efforts forward rather than continuously reinventing the wheel. We note that most of our experience, data, and theory are drawn from the U.S. context, so certain aspects (such as discussion of disciplines and departments of engineering education) may be less relevant to other countries. In addition, we limit our use of terms such as “scholarly” and “rigorous” that are popular in the U.S. context but may have less positive connotations elsewhere. Instead, we focus on quality inquiry through systematic, intentional, thoughtful efforts.
Chapter 5 - Conceptual Change and Misconceptions in Engineering Education
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- By Ruth A. Streveler, Purdue University, Shane Brown, Oregon State University, Geoffrey L. Herman, University of Illinois, Devlin Montfort, Oregon State University
- Edited by Aditya Johri, Virginia Polytechnic Institute and State University, Barbara M. Olds
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- Book:
- Cambridge Handbook of Engineering Education Research
- Published online:
- 05 February 2015
- Print publication:
- 10 February 2014, pp 83-102
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- Chapter
- Export citation
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Summary
Introduction
Recent research has shown that many students continue to understand phenomena in simplified or unproductive ways, even after those understandings are directly contradicted in educational settings (Hake, 1998; Miller et al., 2006). In the context of engineering education, many engineering graduates still do not understand the foundational concepts of solid and fluid mechanics, physics, thermodynamics, digital logic, or other fields. The study of conceptual change and misconceptions is one attempt to understand and address this issue.
Because this field of study is fractious and diverse, we briefly establish some shared vocabulary and understanding of the fundamental processes underlying conceptual change and misconceptions. The following section introduces three primary theories of conceptual change: curriculum, measurement, and theory-focused efforts in engineering education. The chapter concludes with a brief summary and discussion of future directions for research.
We must define conceptual understanding somewhat carefully for our terminology to be useful across the various theoretical frameworks discussed in this chapter. An individual’s conceptual understanding of a topic is the collection of his or her concepts, beliefs, andmental models, where the following definitions apply:
Concepts are pieces or clusters of knowledge, for example, “force,” “mass,” “causation,” and “acceleration.”
Beliefs Concepts are pieces or clusters of knowledge, for example, “force,” “mass,” “causation,” and “acceleration.”
Mental models are groups of meaningfully related beliefs and concepts that allow people to explain phenomena and make predictions; for example, an expert dynamics instructor would use her mental model of Newtonian physics to predict an object’s motion.