Student-Tool Interactions from a Conceptually Challenging Adaptive Learning Module for Materials Science

Nutnicha Nigon; Julie Tucker; Milo Koretsky

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: Materials Division (MATS) Technical Session 2
Tagged Division: Materials Division (MATS)
Page Count: 24
DOI: 10.18260/1-2--48024
Permanent URL: https://peer.asee.org/48024
Download Count: 122

Paper Authors

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Nutnicha Nigon Oregon State University

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Nutnicha (Kate) Nigon recently graduated with a Ph.D. in Materials Science in the School of Mechanical, Industrial and Manufacturing Engineering and a minor in Education at Oregon State University, USA. She received B.Eng. and M.Eng. in Metallurgical and Materials Engineering from Chulalongkorn University, Thailand.

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Julie Tucker Oregon State University

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Dr. Tucker earned her Ph.D. in Nuclear Engineering at the University of Wisconsin – Madison. After graduation, she spent five years as a Principal Scientist at Knolls Atomic Power Laboratory in Schenectady, NY researching welding and the thermal stability of structural alloys. In 2013, she joined the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University and was recently promoted to Full Professor. Dr. Tucker served as the Materials Science Interdisciplinary Graduate Program Director for five years and recently became the Director for the Design for Social Impact Program. Her research focuses on degradation of materials in extreme environments using both modeling and experimental approaches to gain fundamental understanding of materials performance.

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Milo Koretsky Tufts University

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Milo Koretsky is the McDonnell Family Bridge Professor in the Department of Chemical and Biological Engineering and in the Department of Education at Tufts University. He is co-Director of the Institute for Research on Learning and Instruction (IRLI). He received his B.S. and M.S. degrees from UC San Diego and his Ph.D. from UC Berkeley, all in chemical engineering.

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Abstract

The use of computers as automated adaptive instructional tools to support students in STEM education continues to grow. However, these tools often focus on development of declarative knowledge and procedural skills; it is uncommon and challenging to develop adaptive learning tools that specifically focus on developing conceptual understanding. In part, this difficulty stems from limited understanding of how students’ conceptual knowledge emerges through interaction with these adaptive tools. In a previous study, we have explained the components and how we quantitatively tested the adaptive logic of a newly developed Crystallography Adaptive Learning Module (CALM) in materials science. In the current study, we use a knowledge-in-pieces framework that views learning as the activation and coordination of resources. We seek to identify and explicate student-tool interactions that may lead to or hinder the activation of conceptual resources leading to canonical understanding. Utilizing a qualitative think-aloud design, four students completed the CALM while being recorded and prompted to explain their thinking. Sessions lasted two to three hours per participant. Audio recordings of students thinking aloud were supplemented by video recordings of their screens as they completed the module. We also collected and analyzed the notes they wrote as they completed the CALM. Comparing across the four cases, the activation and coordination of resources was more idiosyncratic than we previously envisioned. For example, part of the CALM contains three two-part multiple-choice questions used for formative assessment with the initial question asking a conceptually challenging question and the follow-up question having the students select a response that aligns with their reasoning. We constructed the possible choices for reasons in the second question based on our analysis of students’ free responses in previous terms. While students found the follow-up choices provided on some questions align with their initial reasoning when they selected the answer from the first approach, on most questions they re-thought their choice based on the reasons provided. There were also instances where students responded based on how they interpreted the tool’s response should be. For example, the summative assessment was designed to be adaptive with students who answered a question correctly receiving a more difficult question and those who did not answer correctly receiving a less difficult question. However, sometimes, when correct, a student interpreted a similar question as an indication they were incorrect the first time. We also describe differences in the ways students negotiated uncertainty and how they engaged in the more extensive instructional tools. This paper contributes both to how students conceptually engage with complex materials science content and how student-technology interactions can support or hinder learning.

Citation
Format

Nigon, N., & Tucker, J., & Koretsky, M. (2024, June), Student-Tool Interactions from a Conceptually Challenging Adaptive Learning Module for Materials Science Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--48024

TY - CPAPER
AB - The use of computers as automated adaptive instructional tools to support students in STEM education continues to grow. However, these tools often focus on development of declarative knowledge and procedural skills; it is uncommon and challenging to develop adaptive learning tools that specifically focus on developing conceptual understanding. In part, this difficulty stems from limited understanding of how students’ conceptual knowledge emerges through interaction with these adaptive tools. In a previous study, we have explained the components and how we quantitatively tested the adaptive logic of a newly developed Crystallography Adaptive Learning Module (CALM) in materials science. In the current study, we use a knowledge-in-pieces framework that views learning as the activation and coordination of resources. We seek to identify and explicate student-tool interactions that may lead to or hinder the activation of conceptual resources leading to canonical understanding. Utilizing a qualitative think-aloud design, four students completed the CALM while being recorded and prompted to explain their thinking. Sessions lasted two to three hours per participant. Audio recordings of students thinking aloud were supplemented by video recordings of their screens as they completed the module. We also collected and analyzed the notes they wrote as they completed the CALM. Comparing across the four cases, the activation and coordination of resources was more idiosyncratic than we previously envisioned. For example, part of the CALM contains three two-part multiple-choice questions used for formative assessment with the initial question asking a conceptually challenging question and the follow-up question having the students select a response that aligns with their reasoning. We constructed the possible choices for reasons in the second question based on our analysis of students’ free responses in previous terms. While students found the follow-up choices provided on some questions align with their initial reasoning when they selected the answer from the first approach, on most questions they re-thought their choice based on the reasons provided. There were also instances where students responded based on how they interpreted the tool’s response should be. For example, the summative assessment was designed to be adaptive with students who answered a question correctly receiving a more difficult question and those who did not answer correctly receiving a less difficult question. However, sometimes, when correct, a student interpreted a similar question as an indication they were incorrect the first time. We also describe differences in the ways students negotiated uncertainty and how they engaged in the more extensive instructional tools. This paper contributes both to how students conceptually engage with complex materials science content and how student-technology interactions can support or hinder learning.
AU - Nutnicha Nigon
AU - Julie Tucker
AU - Milo Koretsky
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - Student-Tool Interactions from a Conceptually Challenging Adaptive Learning Module for Materials Science
UR - https://peer.asee.org/48024
DO - 10.18260/1-2--48024
ER -