Feedback in Complex, Authentic, Industrially Situated Engineering Projects using Episodes as a Discourse Analysis Framework – Year 1

Milo Koretsky; Audrey Briggs Champagne; Debra Gilbuena

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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: NSF Grantees' Poster Session
Tagged Topic: NSF Grantees Poster Session
Page Count: 8
Page Numbers: 23.598.1 - 23.598.8
DOI: 10.18260/1-2--19612
Permanent URL: https://peer.asee.org/19612
Download Count: 530

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Paper Authors

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Milo Koretsky Oregon State University

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Dr. Milo Koretsky is a professor of Chemical Engineering at Oregon State University. He currently has research activity in areas related to thin film materials processing and engineering education. He is interested in integrating technology into effective educational practices and in promoting the use of higher level cognitive skills in engineering problem solving. Dr. Koretsky is a six-time Intel faculty fellow and has won awards for his work in engineering education at the university and national levels.

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Audrey Briggs Champagne

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Debra Gilbuena Oregon State University

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Debra Gilbuena is a Ph.D. candidate in the School of Chemical, Biological, and Environmental Engineering at Oregon State University. She currently has research focused on student learning in virtual laboratories. Debra has an M.BA, an M.S, and four years of industrial experience including a position in sensor development. Sensor development is also an area in which she holds a patent. Her dissertation is focused on the characterization and analysis of feedback in engineering education. She also has interests in the diffusion of effective educational interventions and practices.

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Abstract

Feedback in Complex, Authentic, Industrially Situated Engineering Projects using Episodes as a Discourse Analysis Framework – Year 1AbstractOver the last seven years, we have developed, implemented, and studied student learning incyber-enabled learning systems. Central to each of these learning systems is a virtual reactor thatenables a team of students to develop, test, and refine solutions as they are tasked withdeveloping an optimal “recipe” for one of two virtual reactors. The two virtual reactors include:the Virtual Chemical Vapor Deposition (CVD) Reactor, a simulation of an industrial-scalechemical vapor deposition (CVD) reactor, and the Virtual Bio Reactor, based on an industrialscale bioreactor process. These learning systems provide students a capstone experience in whichthey can apply experimental design in a context similar to that of a practicing engineer.Throughout students’ engagement with a learning system, student teams meet with an instructor,called the coach. The student-coach interactions are different from those in traditional classroomsettings. Students and a coach interact in semi-structured design meetings, called coachingsessions, which mirror the structure of industrial design reviews. Students take on the role ofprocess development engineers while the coach acts as mentor and manager. We have learnedthat feedback provided by the coach during these interactions is critical to the success of thelearning systems. For effective implementation of these learning systems at other institutions,there is a need to describe the characteristics of successful feedback and the effects of thatfeedback on student learning. This poster will present the initial findings of the investigation intothe nature of the feedback provided by the coach to the student teams and the relationship of thatfeedback to the strategies students apply as they engage in the task, the models they develop, andtheir knowledge integration of material from previous courses. Specifically, the researchquestions for this stage of the study are: 1. What are the different types of feedback coaches provide and what characteristics distinguish the different types of feedback? 2. What is the relationship between coach feedback and the development of the experimental models and strategies students apply as they work to complete the assigned task?Qualitative assessment data sources include recordings of introductory lectures, coachingsessions, and final oral reports; think-aloud sessions of student teams as they work on the task;student work products, including their design notebooks, written memoranda and reports, oralreports, records of experimentation from the database; and interviews of individual students. Weuse an episodes framework to examine the characteristics of feedback during the coachingsessions. Each episode is defined by the content that is addressed (e.g., reaction kinetics), calledthe episode theme. Each theme is composed of up to four stages: surveying, probing, guiding,and confirmation. A coaching session typically contains approximately 10-20 episodes. Inaddition, we use a method called Model Maps to represent student groups’ model developmentas they complete the task. Model Maps are used to identify teams’ models and strategies and areinterpreted in terms of the guidance the team received during the coaching sessions. Thedifferences noted before and after coaching sessions are interpreted with reference to theepisodes analysis.

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Koretsky, M., & Champagne, A. B., & Gilbuena, D. (2013, June), Feedback in Complex, Authentic, Industrially Situated Engineering Projects using Episodes as a Discourse Analysis Framework – Year 1 Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--19612

TY - CPAPER
AB - Feedback in Complex, Authentic, Industrially Situated Engineering Projects using Episodes as a Discourse Analysis Framework – Year 1AbstractOver the last seven years, we have developed, implemented, and studied student learning incyber-enabled learning systems. Central to each of these learning systems is a virtual reactor thatenables a team of students to develop, test, and refine solutions as they are tasked withdeveloping an optimal “recipe” for one of two virtual reactors. The two virtual reactors include:the Virtual Chemical Vapor Deposition (CVD) Reactor, a simulation of an industrial-scalechemical vapor deposition (CVD) reactor, and the Virtual Bio Reactor, based on an industrialscale bioreactor process. These learning systems provide students a capstone experience in whichthey can apply experimental design in a context similar to that of a practicing engineer.Throughout students’ engagement with a learning system, student teams meet with an instructor,called the coach. The student-coach interactions are different from those in traditional classroomsettings. Students and a coach interact in semi-structured design meetings, called coachingsessions, which mirror the structure of industrial design reviews. Students take on the role ofprocess development engineers while the coach acts as mentor and manager. We have learnedthat feedback provided by the coach during these interactions is critical to the success of thelearning systems. For effective implementation of these learning systems at other institutions,there is a need to describe the characteristics of successful feedback and the effects of thatfeedback on student learning. This poster will present the initial findings of the investigation intothe nature of the feedback provided by the coach to the student teams and the relationship of thatfeedback to the strategies students apply as they engage in the task, the models they develop, andtheir knowledge integration of material from previous courses. Specifically, the researchquestions for this stage of the study are: 1. What are the different types of feedback coaches provide and what characteristics distinguish the different types of feedback? 2. What is the relationship between coach feedback and the development of the experimental models and strategies students apply as they work to complete the assigned task?Qualitative assessment data sources include recordings of introductory lectures, coachingsessions, and final oral reports; think-aloud sessions of student teams as they work on the task;student work products, including their design notebooks, written memoranda and reports, oralreports, records of experimentation from the database; and interviews of individual students. Weuse an episodes framework to examine the characteristics of feedback during the coachingsessions. Each episode is defined by the content that is addressed (e.g., reaction kinetics), calledthe episode theme. Each theme is composed of up to four stages: surveying, probing, guiding,and confirmation. A coaching session typically contains approximately 10-20 episodes. Inaddition, we use a method called Model Maps to represent student groups’ model developmentas they complete the task. Model Maps are used to identify teams’ models and strategies and areinterpreted in terms of the guidance the team received during the coaching sessions. Thedifferences noted before and after coaching sessions are interpreted with reference to theepisodes analysis.
AU - Milo Koretsky
AU - Audrey Briggs Champagne
AU - Debra Gilbuena
CY - Atlanta, Georgia
DA - 2013/06/23
PB - ASEE Conferences
TI - Feedback in Complex, Authentic, Industrially Situated Engineering Projects using Episodes as a Discourse Analysis Framework – Year 1
UR - https://peer.asee.org/19612
DO - 10.18260/1-2--19612
ER -