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Using Systemic Functional Linguistics to Analyze Engineering Speak in an Introductory Materials Science and Engineering Course

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Conference

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

Innovations in Materials Education

Tagged Division

Materials

Page Count

14

Page Numbers

25.1444.1 - 25.1444.14

Permanent URL

https://peer.asee.org/22201

Download Count

17

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Paper Authors

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Jacquelyn E. Kelly Arizona State University

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Stephen J. Krause Arizona State University

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Stephen J. Krause is a professor in the School of Materials in the Fulton School of Engineering at Arizona State University. He teaches in the areas of bridging engineering and education, capstone design, and introductory materials engineering. His research interests are evaluating conceptual knowledge, misconceptions and their repair, and conceptual change. He has co-developed a Materials Concept Inventory for assessing conceptual knowledge of students in introductory materials engineering classes. He is currently conducting research on misconceptions and development of strategies and tools to promote conceptual change in materials courses.

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Dale R. Baker Arizona State University

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Dale Baker is a Fellow of the American Educational Research Association and a Fellow of the American Association for the Advancement of Science. She is on the Advisory Board of JEE and is a Former Editor of the Journal of Research in Science Teaching. Her work focuses on equity issues in STEM, teacher professional development in STEM, and engineering education more generally.

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Abstract

Using Systemic Functional Linguistics to Analyze Engineering Speak in an Introductory Materials Science & Engineering CourseStudents can use technical language consistent with science and engineering norms yet may notknow the meaning of these words. This phenomenon has been examined in science classroomsby many researchers. However, little work has been done in the context of engineering whichrequires students to not only be able use engineering terms and understand natural scienceconcepts, but to also be able to clearly articulate and understand these concepts with respect toengineering applications. In order to understand and interpret student academic language, a lensto analyze and quantify it is required. This paper will answer the research question, “How canstudent proficiency of engineering academic language be assessed?” To answer this question, afunctional view of linguistics will be used as a theoretical framework for interpreting engineeringacademic language. While traditional views of language focus primarily on grammar, whichworks with the structure of sentences, a functional view of linguistics examines the relationshipsbetween these structural components of language and their contexts and meanings. Thistheoretical lens is particularly relevant to engineering language, as understanding its use in thecontext of engineering design is of utmost importance. Systemic functional linguistics (SFL)will be used as a theoretical framework for analyzing engineering speak in an introductorymaterials science and engineering course. A written engineering design task, asked students touse as much engineering knowledge and vocabulary as possible to discuss the design of abicycle. This task was administered four times over the course of the semester. An SFLframework was used to analyze students' engineering speak as it evolved throughout the course.Preliminary results suggest that student language use can be monitored successfully over thecourse of a semester, allowing instructors to make instructional decisions to enhance andmaximize student learning. Challenges, affordances, and results of interpreting engineeringspeak through an SFL lens will be described and discussed in the full paper. 

Kelly, J. E., & Krause, S. J., & Baker, D. R. (2012, June), Using Systemic Functional Linguistics to Analyze Engineering Speak in an Introductory Materials Science and Engineering Course Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. https://peer.asee.org/22201

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