Impact of an Embedded Expert Model on Course Transformation in Engineering

Molly McVey; Caroline R. Bennett; Andrea Follmer Greenhoot

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Conference: 2019 ASEE Annual Conference & Exposition
Location: Tampa, Florida
Publication Date: June 15, 2019
Start Date: June 15, 2019
End Date: June 19, 2019
Conference Session: Writers, Experts, and the Workforce in Civil Engineering
Tagged Division: Civil Engineering
Page Count: 16
DOI: 10.18260/1-2--32921
Permanent URL: https://peer.asee.org/32921
Download Count: 689

Paper Authors

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Molly McVey University of Kansas

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Dr. Molly A. McVey is a post-doctoral teaching fellow at the University of Kansas School of Engineering where she works with faculty to incorporate evidence-based and student-centered teaching methods, and to research the impacts of changes made to teaching on student learning and success. Dr. McVey earned her Ph.D in Mechanical Engineering from the University of Kansas.

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Caroline R. Bennett P.E. University of Kansas

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Caroline is the John E. & Winifred E. Sharp Associate Professor in the KU Civil, Environmental, and Architectural Engineering department, with a specialty in structural engineering and bridge structures. She works closely with KU Engineering’s post-doctoral Teaching Fellow and oversees the overall Engaged Learning Initiative in the School of Engineering. Caroline is responsible for overseeing KU Engineering’s active-learning classroom design and usage, prioritizing course assignments in the active-learning classrooms, helping faculty to advance their pedagogy by incorporating best practices, and advancing implementation of student-centered, active-learning approaches in the School of Engineering. Caroline is also active in contributing to university-level discussions in the area of course redesign, and has been closely involved with the KU Center for Teaching Excellence since 2006. She regularly teaches courses in bridge engineering, steel buildings, structural analysis, fatigue and fracture, elastic stability, and how to be an effective college teacher.

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Andrea Follmer Greenhoot University of Kansas

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Andrea Follmer Greenhoot is Professor of Psychology, Director of the Center for Teaching Excellence and Gautt Teaching Scholar at the University of Kansas. Her research in psychology is on cognitive development and memory. Her work with the Center for Teaching Excellence explores how we can transform learning experiences for university students that are grounded in cognitive and developmental science and mindful of the challenges they will face in the future.

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Abstract

The School of Engineering has prioritized course transformation through an “Engaged Learning Initiative,” and a partnership with a larger, multi-institutional NSF grant aimed at investigating an “embedded expert” model as a catalyst for change. This paper describes the implementation of the embedded expert model as implemented in this institution and the impact of this model on course transformation, faculty engagement with teaching excellence, and student success.

The embedded expert in this model is a “post-doctoral teaching fellow” with an educational background in Mechanical Engineering. The role, however, was to develop as an expert in and to support engineering education across the entire School of Engineering. The main roles of the post-doctoral teaching fellow position include: 1) consultation with faculty on course transformation, 2) development and management of the Undergraduate Teaching Fellows (UGTF) program, 3) analysis of student learning and publication of engineering education research, and 4) development of a community of practice around teaching excellence in the School. The embedded expert model has been in place since Fall 2014.

The embedded expert in Engineering was one of 11 of these positions across the University as part of the larger NSF project. The larger project supported the development of a University-wide community of practice around excellence in teaching, supported course transformation grants for faculty across the University, and developed a Teaching Scholarship community for the embedded experts and others in similar roles.

The impact of the embedded expert will be examined for the School of Engineering. The impact of the model will be described in terms of 1) course transformation activity, 2) development and impact of the UGTF program, 3) engineering education research involvement, and 4) school-wide measures of student success. Course transformation activity will be measured by the number of courses and instructors involved in course transformation each year of the embedded expert program, and by a description and count of the scope of transformations undertaken. Additionally, changes in teaching practices across the school, as evidenced by the COPUS (Course Observation Protocol for Undergraduate STEM), will be presented. The growth and training program developed for the UGTF program will be described, as well as survey data from students, those in UGTF roles, and faculty. Engineering Education research involvement will be described in terms of counts of activity and involvement in the community of practice around Engineering Education. School-wide indicators of student success will be examined in terms of DFW rates in particular courses. Finally, the authors will reflect on survey results from faculty who interacted with the embedded expert to understand what aspects of the embedded expert model were most critical to success.

Citation
Format

McVey, M., & Bennett, C. R., & Greenhoot, A. F. (2019, June), Impact of an Embedded Expert Model on Course Transformation in Engineering Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32921

TY - CPAPER
AB -
The School of Engineering has prioritized course transformation through an “Engaged Learning Initiative,” and a partnership with a larger, multi-institutional NSF grant aimed at investigating an “embedded expert” model as a catalyst for change. This paper describes the implementation of the embedded expert model as implemented in this institution and the impact of this model on course transformation, faculty engagement with teaching excellence, and student success.

The embedded expert in this model is a “post-doctoral teaching fellow” with an educational background in Mechanical Engineering. The role, however, was to develop as an expert in and to support engineering education across the entire School of Engineering. The main roles of the post-doctoral teaching fellow position include: 1) consultation with faculty on course transformation, 2) development and management of the Undergraduate Teaching Fellows (UGTF) program, 3) analysis of student learning and publication of engineering education research, and 4) development of a community of practice around teaching excellence in the School. The embedded expert model has been in place since Fall 2014.

The embedded expert in Engineering was one of 11 of these positions across the University as part of the larger NSF project. The larger project supported the development of a University-wide community of practice around excellence in teaching, supported course transformation grants for faculty across the University, and developed a Teaching Scholarship community for the embedded experts and others in similar roles.

The impact of the embedded expert will be examined for the School of Engineering. The impact of the model will be described in terms of 1) course transformation activity, 2) development and impact of the UGTF program, 3) engineering education research involvement, and 4) school-wide measures of student success. Course transformation activity will be measured by the number of courses and instructors involved in course transformation each year of the embedded expert program, and by a description and count of the scope of transformations undertaken. Additionally, changes in teaching practices across the school, as evidenced by the COPUS (Course Observation Protocol for Undergraduate STEM), will be presented. The growth and training program developed for the UGTF program will be described, as well as survey data from students, those in UGTF roles, and faculty. Engineering Education research involvement will be described in terms of counts of activity and involvement in the community of practice around Engineering Education. School-wide indicators of student success will be examined in terms of DFW rates in particular courses. Finally, the authors will reflect on survey results from faculty who interacted with the embedded expert to understand what aspects of the embedded expert model were most critical to success.

AU - Molly McVey
AU - Caroline R. Bennett P.E.
AU - Andrea Follmer Greenhoot
CY - Tampa, Florida
DA - 2019/06/15
PB - ASEE Conferences
TI - Impact of an Embedded Expert Model on Course Transformation in Engineering
UR - https://peer.asee.org/32921
DO - 10.18260/1-2--32921
ER -