A Teaching Assistant Training Protocol for Improving Feedback on Open-Ended Engineering Problems in Large Classes

Matthew A Verleger; Heidi A. Diefes-Dux

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Conference: 2013 ASEE Annual Conference & Exposition
Location: Atlanta, Georgia
Publication Date: June 23, 2013
Start Date: June 23, 2013
End Date: June 26, 2013
ISSN: 2153-5965
Conference Session: FPD 4: First-Year Engineering Courses, Part I: Multimedia, Large Classes, and TAs
Tagged Division: First-Year Programs
Page Count: 12
Page Numbers: 23.121.1 - 23.121.12
DOI: 10.18260/1-2--19135
Permanent URL: https://peer.asee.org/19135
Download Count: 467

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Paper Authors

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Matthew A Verleger Embry-Riddle Aeronautical Univ., Daytona Beach

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Matthew Verleger is Assistant Professor in Freshman Engineering at Embry-Riddle Aeronautical University. He has a BS in Computer Engineering, an MS in Agricultural & Biological Engineering, and a PhD in Engineering Education, all from Purdue University. Prior to joining the Embry-Riddle faculty, he spent two years as an Assistant Professor of Engineering Education at Utah State University. His research interests include Model-Eliciting Activities, online learning, and the development of software tools to facilitate student learning.

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Heidi A. Diefes-Dux Purdue University, West Lafayette orcid.org/0000-0003-3635-1825

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Heidi A. Diefes-Dux is an Associate Professor in the School of Engineering Education at Purdue University. She received her B.S. and M.S. in Food Science from Cornell University and her Ph.D. in Food Process Engineering from the Department of Agricultural and Biological Engineering at Purdue University. She is a member of Purdue’s Teaching Academy. Since 1999, she has been a faculty member within the First-Year Engineering Program at Purdue, the gateway for all first-year students entering the College of Engineering. She has coordinated and taught in a required first-year engineering course that engages students in open-ended problem solving and design. Her research focuses on the development, implementation, and assessment of model-eliciting activities with realistic engineering contexts. She is currently the Director of Teacher Professional Development for the Institute for P-12 Engineering Research and Learning (INSPIRE).

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Abstract

A Teaching Assistant Training Protocol for Improving Feedback on Open-Ended Engineering Problems in Large ClassesTeaching Assistants (TAs) are vital to teaching large classes. TAs often function as students’primary contact within a large course, and, in many cases, they evaluate the majority of studentwork on assignments. For TAs, evaluating students’ work on open-ended problems ischallenging because students produce a variety of solutions that the TA must interpret toaccurately apply a given rubric. Reliable evaluation of student work is desirable. This paperexplores a TA training protocol for identifying TAs who are in need of additional guidance onhow to evaluate students’ work on open-ended engineering problems in a large class.Model-Eliciting Activities (MEAs) are authentic, open-ended, client-driven, engineering-basedmathematical modeling problems. Teams of students develop a written document describingtheir generalizable procedure (mathematical model) for solving a given problem and similarproblems. MEAs have been conducted at a midwestern university since 2002 in the large first-year engineering courses. In Fall 2012, the enrollment was approximately 1700 students, thecourse was staffed by 9 Graduate TAs, 70 Undergraduate TAs, 11 faculty, and 3 staff. All TAs(both graduate and undergraduate) are the primary point-of-contact for students and evaluatealmost all class assignments, including MEA solutions. The use of undergraduate TAs,including sophomore juniors, and seniors, to evaluate student work on MEAs is relatively new.Ensuring that each of the approximately 80 TAs is adequately prepared to reliably evaluatestudent work is a significant challenge.TAs, currently, engage in approximately 5 hours of training per MEA taught in the two-semestersequence required first-year engineering courses. The focus of this training is on evaluating andproviding feedback on students work on the MEAs slated for implementation in a givensemester. After the face-to-face training, TAs practice evaluating prototypical student solutionsand compare their evaluations to those of an expert. Following each evaluation, the TAs areasked to critically reflect on how they can improve their subsequent evaluations. Uponcompletion of the training sequence, the TAs’ evaluations of the sample solutions are examinedby the course coordinator to identifying which TAs need additional help to better align theirevaluations and feedback to an expert’s. Identified TAs are then given additional guidance onhow to improve their evaluations.This paper will do the following: (1) explore the history and need for TA training, (2) describethe context in which training occurs, (3) describe the training process and protocol in detail, (4)examine, quantitatively and qualitatively, historical and current data to explore the effectivenessof the TA training protocol, and (5) identify future changes that should be made to improve howTAs are being trained. Such an overview and analysis will provide insights for others whostruggle to bring open-ended problem solving in to large courses because of the demands forreliable evaluation of student work.

Citation
Format

Verleger, M. A., & Diefes-Dux, H. A. (2013, June), A Teaching Assistant Training Protocol for Improving Feedback on Open-Ended Engineering Problems in Large Classes Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--19135

TY  - CPAPER
AB  -         A Teaching Assistant Training Protocol for Improving Feedback            on Open-Ended Engineering Problems in Large ClassesTeaching Assistants (TAs) are vital to teaching large classes. TAs often function as students’primary contact within a large course, and, in many cases, they evaluate the majority of studentwork on assignments. For TAs, evaluating students’ work on open-ended problems ischallenging because students produce a variety of solutions that the TA must interpret toaccurately apply a given rubric. Reliable evaluation of student work is desirable. This paperexplores a TA training protocol for identifying TAs who are in need of additional guidance onhow to evaluate students’ work on open-ended engineering problems in a large class.Model-Eliciting Activities (MEAs) are authentic, open-ended, client-driven, engineering-basedmathematical modeling problems. Teams of students develop a written document describingtheir generalizable procedure (mathematical model) for solving a given problem and similarproblems. MEAs have been conducted at a midwestern university since 2002 in the large first-year engineering courses. In Fall 2012, the enrollment was approximately 1700 students, thecourse was staffed by 9 Graduate TAs, 70 Undergraduate TAs, 11 faculty, and 3 staff. All TAs(both graduate and undergraduate) are the primary point-of-contact for students and evaluatealmost all class assignments, including MEA solutions. The use of undergraduate TAs,including sophomore juniors, and seniors, to evaluate student work on MEAs is relatively new.Ensuring that each of the approximately 80 TAs is adequately prepared to reliably evaluatestudent work is a significant challenge.TAs, currently, engage in approximately 5 hours of training per MEA taught in the two-semestersequence required first-year engineering courses. The focus of this training is on evaluating andproviding feedback on students work on the MEAs slated for implementation in a givensemester. After the face-to-face training, TAs practice evaluating prototypical student solutionsand compare their evaluations to those of an expert. Following each evaluation, the TAs areasked to critically reflect on how they can improve their subsequent evaluations. Uponcompletion of the training sequence, the TAs’ evaluations of the sample solutions are examinedby the course coordinator to identifying which TAs need additional help to better align theirevaluations and feedback to an expert’s. Identified TAs are then given additional guidance onhow to improve their evaluations.This paper will do the following: (1) explore the history and need for TA training, (2) describethe context in which training occurs, (3) describe the training process and protocol in detail, (4)examine, quantitatively and qualitatively, historical and current data to explore the effectivenessof the TA training protocol, and (5) identify future changes that should be made to improve howTAs are being trained. Such an overview and analysis will provide insights for others whostruggle to bring open-ended problem solving in to large courses because of the demands forreliable evaluation of student work.
AU  - Matthew A Verleger
AU  - Heidi A. Diefes-Dux
CY  - Atlanta, Georgia
DA  - 2013/06/23
PB  - ASEE Conferences
TI  - A Teaching Assistant Training Protocol for Improving Feedback on Open-Ended Engineering Problems in Large Classes
UR  - https://peer.asee.org/19135
DO  - 10.18260/1-2--19135
ER  -