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Analyzing Student Team Dialogues To Guide The Design Of Active Learning Sessions

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Conference

2007 Annual Conference & Exposition

Location

Honolulu, Hawaii

Publication Date

June 24, 2007

Start Date

June 24, 2007

End Date

June 27, 2007

ISSN

2153-5965

Conference Session

Student Teams and Project-Based Learning

Tagged Division

Educational Research and Methods

Page Count

18

Page Numbers

12.243.1 - 12.243.18

Permanent URL

https://peer.asee.org/1905

Download Count

28

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Paper Authors

biography

Steven Zemke Gonzaga University

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Steven Zemke is an Assistant Professor of Mechanical Engineering at Gonzaga University. He teaches design classes at the sophomore, junior, and capstone level. His research pursuits are in the pedagogy of design. Steven received his Ph.D. in Mechanical Engineering with a dissertation on pedagogy from the University of Idaho in 2005. Prior to teaching, Steven was a design engineer and engineering manager for 25 years.

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biography

Diane Zemke Gonzaga University

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Diane Zemke is a Doctoral Student in the Leadership Studies Program at Gonzaga University. Her interests include pedagogy, paradigms of leadership, and Western spirituality. Diane holds a Masters degree in Religious Studies from Gonzaga University.

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Analyzing Student Team Dialogues to Guide the Design Of Active Learning Sessions

Abstract

Engineering faculty are increasingly using active learning methods to improve learning in their classes. Many methods and their uses are described in the literature. These methods range from impromptu techniques such as “think-pair-share” up to strategies for structuring the entire course. The strength of these methods relies on generating student interactions marked with deep cognitive reasoning. Presumably, the greater the depth of reasoning in interactions, the greater the potential for learning. We define deep interactions as conversations that show thoughtful use of schema to organize information and/or the organization of information to create schema. In contrast, shallow interactions deal primarily with exchange of information.

Active learning methods, when used properly, initiate deep student interactions. However, many teaching environments do not directly fit into the prescription of a well-researched method. Consequently, at times faculty must thoughtfully adapt these methods for their classes. However, in doing so there is no guarantee that deep interactions will ensue. Furthermore, faculty may also wish to diagnose whether their application of an active learning method is working as planned. One way to assess active learning is to assess the depth of the student interactions. These interactions may be assessed by recording, transcribing, and analyzing student dialogues. Our question is:

What important design features for active learning sessions can be identified by the use of brief analyses of student dialogue?

This case study examines the student dialogues in four sequential active learning sessions. In each session, a student team was recorded and their conversation transcribed. The transcription was reviewed and the observations were used to improve the design of the next session. After the conclusion of the sessions, the transcripts were examined for trends that emerged across multiple sessions. Three findings emerged:

1. Briefly coding transcripts by identify major themes and then coding along those themes surfaced substantial feedback to improve the design of the active sessions. The use of coding criteria, such as the three principles of learning, was used informally to interpret the content of the coding. The iterative use of transcript coding and session improvement created sessions with dialogues showing deeper interactions.

2. The student learning appeared to be tied to context. When the case supplied the context, the students used it to create schema. When the context was not supplied, the students created their own context to use. Consequently, cases that provide a rich context appear to better support the use of schemas related to the case.

3. The students seemed to intuitively identify the challenge in each session and apply their efforts to resolving it. This included challenges that were unintentionally introduced into the

Zemke, S., & Zemke, D. (2007, June), Analyzing Student Team Dialogues To Guide The Design Of Active Learning Sessions Paper presented at 2007 Annual Conference & Exposition, Honolulu, Hawaii. https://peer.asee.org/1905

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