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

\bibitem{asee_peer_23296}
  Min, K. J., \& Jackman, J., \& Chan, J. C. (2014, June), \emph{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

K. Jo Min, John Jackman, and Jason C.K. Chan.  "Visual Models for Abstract Concepts Towards Better Learning Outcomes and Self-Efficacy".  2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana, 2014, June.  ASEE Conferences, 2014.  https://peer.asee.org/23296 Internet.  24 Jun, 2024

\bibitem{asee_peer_23296}
  K. Jo Min, John Jackman, and Jason C.K. Chan.
  "Visual Models for Abstract Concepts Towards Better Learning Outcomes and Self-Efficacy".
  \emph{2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana, 2014, June}.
  ASEE Conferences, 2014.
  https://peer.asee.org/23296 Internet.  24 Jun, 2024

@INPROCEEDINGS{asee_peer_23296
author = "K. Jo Min, John Jackman, and Jason C.K. Chan"
title = "Visual Models for Abstract Concepts Towards Better Learning Outcomes and Self-Efficacy"
booktitle = "2014 ASEE Annual Conference \& Exposition"
year = "2014"
month = "June"
address = "Indianapolis, Indiana"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/23296}
number = {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  -