Visual Models for Abstract Concepts Towards Better Learning Outcomes and Self-Efficacy

K. Jo Min; John Jackman; Jason C.K. Chan

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Conference: 2014 ASEE Annual Conference & Exposition
Location: Indianapolis, Indiana
Publication Date: June 15, 2014
Start Date: June 15, 2014
End Date: June 18, 2014
ISSN: 2153-5965
Conference Session: Student Learning, Problem Solving, and Critical Thinking 1
Tagged Division: Educational Research and Methods
Page Count: 13
Page Numbers: 24.1363.1 - 24.1363.13
DOI: 10.18260/1-2--23296
Permanent URL: https://peer.asee.org/23296
Download Count: 513

Paper Authors

biography

K. Jo Min Iowa State University

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K. Jo Min is an associate professor and the director of undergraduate education in the department of industrial and
manufacturing systems engineering at Iowa State University. He teaches courses in sustainable production systems and
market-based allocation mechanisms. His education research interests include continuous improvement for objectives and
outcomes, teaching and learning of global enterprise perspectives, and international student-team management and
effectiveness. His research publications have appeared in the International Journal of Engineering Education, the Engineering
Economist, IEEE Transactions on Engineering Management, and others.

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biography

John Jackman Iowa State University

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John Jackman is an associate professor of industrial and manufacturing systems engineering at Iowa State University. His research interests include engineering problem solving, computer simulation, web-based immersive learning environments, and data acquisition and control.

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Jason C.K. Chan

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Abstract

Visual Models for Abstract Concepts towards Better Learning Outcomes and Self-EfficacyAbstract concepts without direct physical representations related to principles of engineeringeconomics and management are difficult for engineering students to conceptualize as evidencedby their inability to explain their solutions. We observe that efforts to improve the learningoutcomes of such students have included a substantial increase in the use of visual models forabstract concepts in textbooks, DVDs, and online resources. To our knowledge, however, therehas been little systematic research on whether and how visual models help engineering studentsbetter understand abstract concepts especially in the areas of industrial engineering, engineeringmanagement, and systems engineering.To address this issue from an engineering education research perspective, two essential questionsare (1) to what extent do visual models of such concepts help students develop a complete mentalmodel and (2) whether better mental models lead to better understanding of the domainknowledge and enhance students’ self-efficacy. Towards addressing these important questions, inthis paper, we construct and analyze an evidence-based practice case to see if visual models leadto better understanding of the concepts by students and enhance their self-efficacy.In this study, we focused on the inventory control aspects of a supply chain in a typical juniorlevel undergraduate production systems course in Industrial Engineering. Visual models ofinventory behaviors were designed to complement the traditional approach of mathematicalderivations and numerical computations. In this context, we used a randomized-controlled designresearch framework implementing the visual models in quizzes administered to a randomlyselected group of students. Pre- and post-surveys on student self-efficacy were used to assess theeffects of the visual models.Students’ quiz outcomes and self-efficacy surveys were compared to those from a control groupthat did not use the visual models, and the results from both groups were statistically analyzed.All participants in the study were undergraduate engineering students. Based on this analysis, weevaluated the impact of visual models designed to help students understand abstract concepts,and address if visual models lead to enhanced students’ self-efficacy.This study was motivated by engineering students’ challenges in understanding abstract conceptsand the need for continuous improvement. The results showed that, within the scope of theaforementioned experiment and collected data, the visual models do help students understandabstract concepts and improve their self-efficiency. In addition, this paper shows how the visualmodels can be integrated into a course and offers insights on implementation effectiveness andefficiency. As this project focuses on the abstract concepts in the economic aspects of supplychains that are commonly found in industrial engineering, systems engineering, and engineeringmanagement, the research findings can be easily extended to various areas of business,management, and economics as well. 1

Citation
Format

Min, K. J., & Jackman, J., & Chan, J. C. (2014, June), Visual Models for Abstract Concepts Towards Better Learning Outcomes and Self-Efficacy Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--23296

TY  - CPAPER
AB  -                       Visual Models for Abstract Concepts towards                      Better Learning Outcomes and Self-EfficacyAbstract concepts without direct physical representations related to principles of engineeringeconomics and management are difficult for engineering students to conceptualize as evidencedby their inability to explain their solutions. We observe that efforts to improve the learningoutcomes of such students have included a substantial increase in the use of visual models forabstract concepts in textbooks, DVDs, and online resources. To our knowledge, however, therehas been little systematic research on whether and how visual models help engineering studentsbetter understand abstract concepts especially in the areas of industrial engineering, engineeringmanagement, and systems engineering.To address this issue from an engineering education research perspective, two essential questionsare (1) to what extent do visual models of such concepts help students develop a complete mentalmodel and (2) whether better mental models lead to better understanding of the domainknowledge and enhance students’ self-efficacy. Towards addressing these important questions, inthis paper, we construct and analyze an evidence-based practice case to see if visual models leadto better understanding of the concepts by students and enhance their self-efficacy.In this study, we focused on the inventory control aspects of a supply chain in a typical juniorlevel undergraduate production systems course in Industrial Engineering. Visual models ofinventory behaviors were designed to complement the traditional approach of mathematicalderivations and numerical computations. In this context, we used a randomized-controlled designresearch framework implementing the visual models in quizzes administered to a randomlyselected group of students. Pre- and post-surveys on student self-efficacy were used to assess theeffects of the visual models.Students’ quiz outcomes and self-efficacy surveys were compared to those from a control groupthat did not use the visual models, and the results from both groups were statistically analyzed.All participants in the study were undergraduate engineering students. Based on this analysis, weevaluated the impact of visual models designed to help students understand abstract concepts,and address if visual models lead to enhanced students’ self-efficacy.This study was motivated by engineering students’ challenges in understanding abstract conceptsand the need for continuous improvement. The results showed that, within the scope of theaforementioned experiment and collected data, the visual models do help students understandabstract concepts and improve their self-efficiency. In addition, this paper shows how the visualmodels can be integrated into a course and offers insights on implementation effectiveness andefficiency. As this project focuses on the abstract concepts in the economic aspects of supplychains that are commonly found in industrial engineering, systems engineering, and engineeringmanagement, the research findings can be easily extended to various areas of business,management, and economics as well.                                                 1
AU  - K. Jo Min
AU  - John Jackman
AU  - Jason C.K. Chan
CY  - Indianapolis, Indiana
DA  - 2014/06/15
PB  - ASEE Conferences
TI  - Visual Models for Abstract Concepts Towards Better Learning Outcomes and Self-Efficacy
UR  - https://peer.asee.org/23296
DO  - 10.18260/1-2--23296
ER  -