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Board 139: Investing in Instructors: Creating Intelligent Feedback Loops in Large Foundational Courses for Undergraduate Engineering

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

7

Permanent URL

https://peer.asee.org/29937

Download Count

20

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Paper Authors

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Jacob R. Grohs Virginia Tech

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Jacob Grohs is an Assistant Professor in Engineering Education at Virginia Tech with Affiliate Faculty status in Biomedical Engineering and Mechanics and the Learning Sciences and Technologies at Virginia Tech. He holds degrees in Engineering Mechanics (BS, MS) and in Educational Psychology (MAEd, PhD).

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David B. Knight Virginia Tech Orcid 16x16 orcid.org/0000-0003-4576-2490

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David Knight is Assistant Professor and Assistant Department Head for Graduate Programs in the Department of Engineering Education at Virginia Tech. He is also Director of International Engagement in Engineering Education and affiliate faculty with the Higher Education Program at Virginia Tech. His research tends to be at the macro-scale, focused on a systems-level perspective of how engineering education can become more effective, efficient, and inclusive.

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Michelle Soledad Virginia Tech Orcid 16x16 orcid.org/0000-0002-2491-6684

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Michelle Soledad is a PhD candidate in the Department of Engineering Education at Virginia Tech. Her research interests include faculty development and data-informed reflective practice. Ms. Soledad has degrees in Electrical Engineering (BS, ME) from the Ateneo de Davao University (ADDU) in Davao City, Philippines, where she continues to be a faculty member of the Electrical Engineering Department. She also served as Department Chair and was a member of the University Research Council before pursuing doctoral studies. Prior to joining ADDU in 2008, Ms. Soledad was a Senior Team Lead for Accenture, where she worked on and managed systems maintenance and enhancement projects.

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Scott W Case Virginia Tech

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Scott W. Case is the Reynolds Metals Professor of Engineering Mechanics at Virginia Tech. He has previously served as associate department head of Engineering Science and Mechanics and as Interim Associate Dean for Academic Affairs within the College of Engineering.

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Homero Gregorio Murzi Virginia Tech Orcid 16x16 orcid.org/https://0000-0003-3849-2947

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Homero Murzi is an Associate Professor of Practice in the Department of Engineering Education at Virginia Tech. He holds degrees in Industrial Engineering (BS, MS), Master of Business Administration (MBA) and in Engineering Education (PhD). His research focuses on contemporary and inclusive pedagogical practices, environmental, ethics and humanitarian engineering, and non-traditional knowledge transfer. Homero has been recognized as a Fulbright scholar and was inducted in the Bouchet Honor Society.

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Natasha Smith Virginia Tech

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Natasha is the Director of Enrollment Management for the College of Engineering as well as an undergraduate academic and career advisor for General Engineering students. These dual roles allow Natasha the unique opportunity to understand and articulate viewpoints of both administration and students.

Natasha strives to implement innovative and systematic technological advances to academic advising and enrollment management.

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Abstract

The drive to encourage young people to pursue degrees and careers in engineering has led to an increase in student populations in engineering programs. For some institutions, such as large public research institutions, this has led to large class sizes for courses that are commonly taken across multiple programs. While this decision is reasonable from an operational and resource management perspective, research on large classes have shown that students suffer decreased engagement, motivation and achievement. Instructors, on the other hand, report having difficulty establishing rapport with their students and a growing inability to monitor students’ learning gains and provide quality individualized feedback. To address these issues, our project draws from Lattuca and Stark’s Academic Plan model, which incorporates a thorough consideration of factors influencing curricular activities that can be applied at the course, program, and institutional levels, and assumes that instructors are key actors in curriculum development and revision. We aim to revitalize feedback loops to help instructors and departments continuously improve. Recognizing that we must understand both individual and systems level perspectives, we prioritize regular engagement between faculty and institutional support structures to collaboratively identify problems and systematically establish continuous improvement. In the first phase of this NSF IUSE Institutional Transformation project, we focus on specifically prompting and studying the experiences of 8 instructors of foundational engineering courses usually taught in large class sizes across 4 different departments at a large public research institution. We collected qualitative data (semi-structured interviews, reflective journals, course-related documents) and quantitative data (student surveys and institution-provided transcript data) to answer research questions (e.g., what data do faculty teaching large foundational undergraduate engineering courses identify as being useful so that they may enhance students’ experiences and outcomes within the classes that they teach and across students’ multiple large classes?) at the intersection of learning analytics and faculty change. The data was used as a baseline to further refine data collection protocols, identify data that faculty consider meaningful and useful for managing large foundational engineering courses, and consider ways of productively leveraging institutional data to improve the learning experience in these courses. Data collection for the first phase is ongoing and will continue through the Spring 2018 semester. Findings for this paper will include high-level insights from Fall interviews with instructors as well as data visualizations created from the population-level data characterizing student performance in the foundational courses within the context of pre-college characteristics (e.g., SAT scores) and/or other academic outcomes (e.g., major switching within or out of engineer, degree attainment).

Grohs, J. R., & Knight, D. B., & Soledad, M., & Case, S. W., & Murzi, H. G., & Smith, N. (2018, June), Board 139: Investing in Instructors: Creating Intelligent Feedback Loops in Large Foundational Courses for Undergraduate Engineering Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/29937

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