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Data-Driven Course Improvements: Using Artifact Analysis to Conquer ABET Criterion 4

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

First-Year Programs Division Technical Session 8: Ways to Measure "Things" About Your Course(s)

Tagged Division

First-Year Programs

Page Count

15

DOI

10.18260/p.26641

Permanent URL

https://peer.asee.org/26641

Download Count

183

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Paper Authors

biography

Tony Andrew Lowe Purdue University, West Lafayette

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Tony Lowe is a PhD candidate in Engineering Education at Purdue University. He has a BSEE from Rose-Hulman Institute of Technology and a MSIT from Capella. He currently teaches as an adjunct at CTU Online and has been an on-and-off corporate educator and full time software engineer for twenty years.

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biography

David A. Evenhouse Purdue University

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David Evenhouse is a Graduate Student and Research Assistant in the Purdue School of Engineering Education. He graduated from Calvin College in the Spring of 2015 with a B.S.E. concentrating in Mechanical Engineering. Experiences during his undergraduate years included a semester in Spain, taking classes at the Universidad de Oviedo and the Escuela Politécnica de Ingenieria de Gijón, as well as multiple internships in Manufacturing and Quality Engineering. His current work primarily investigates the effects of select emergent pedagogies upon student and instructor performance and experience at the collegiate level. Other interests include engineering ethics, engineering philosophy, and the intersecting concerns of engineering industry and higher academia.

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Dhinesh Balaji Radhakrishnan Purdue University

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Graduate Research Assistant at the School of Engineering Education, Purdue University

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Stephen R. Hoffmann Purdue University, West Lafayette

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Stephen R. Hoffmann is the Assistant Head of the School of Engineering Education at Purdue University, with responsibilities for the First-Year Engineering Program.

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Abstract

This evidence based practice describes a process to evaluate a course within the spirit of ABET Criteria 4, continuous improvement. Faculty and staff often are asked to collaborate on the design of core engineering classes and share teaching across many sections. Over time these courses evolve to accommodate new subject matter, pedagogical approaches, political and personal preferences among other criteria as dictated by a dynamic group of stakeholders. Many changes originate from a clear mandate, while others sneak in without a full analysis of the course. Repeated and often subtle changes may have a significant impact on the course, creating a narrative of the faculty’s intent as the course goals and methods are updated semester after semester.

This paper describes a process using engineering educational research methods to understand the nature and motivation of course changes. We define a six step process focused around using the artifact analysis methodology to provide instructional teams with data to better understand the construction of their course and how it has changed over time. A case study examining a large-format First Year Engineering course design is included describing the process in action. The case study includes methodological choices, analysis, and findings as a guide to practitioners seeking to follow our process for gathering data. The data can be used to inform future changes to the course design to ensure alignment of the course objectives, assessment, and pedagogy, while at the same time systematically meeting ABET Criteria 4.

Lowe, T. A., & Evenhouse, D. A., & Radhakrishnan, D. B., & Hoffmann, S. R. (2016, June), Data-Driven Course Improvements: Using Artifact Analysis to Conquer ABET Criterion 4 Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.26641

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