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

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Visual Models for Abstract Concepts towards Better Learning Outcomes and Self-Efficacy.
Συγγραφείς: K. Jo Min, Jackman, John, Chan, Jason C. K.
Πηγή: Proceedings of the ASEE Annual Conference & Exposition; 2014, p1-13, 13p
Θεματικοί όροι: Self-efficacy, Engineering education, Mathematics problems & exercises, Engineering student research, Teaching aids, Education
Περίληψη: We constructed and analyzed an evidence-based practice case to see if visual models help students develop a better understanding of abstract concepts and enhance their self-efficacy when solving engineering problems. Abstract concepts without corresponding physical phenomena are often found in the domains of industrial engineering, engineering management, and systems engineering. In this study, we focus on inventory control of a supply chain, which is typically a junior level undergraduate production systems course in an industrial engineering program. Visual models of inventory behaviors were designed to complement the traditional approach of mathematical derivations and numerical computations. In this context, we use a randomized-controlled design research framework implementing the visual models in a quiz. Pre- and post-surveys on student self-efficacy were used to assess the effects of the visual models. Students' quiz outcomes and self-efficacy surveys are compared to those from a control group that did not use the visual models, and the results from both groups were statistically analyzed. This study is motivated by engineering students' inability to understand abstract concepts and the need for continuous improvement of student learning. The results show that, within the scope of the aforementioned experiment and collected data, the visual models do help students understand abstract concepts and improve their self-efficacy. This study can serve as a basis for further studies on the extent of visual models helping students develop a complete mental model and on whether better mental models actually lead to a better understanding of the domain knowledge and enhance students' self-efficacy. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of the ASEE Annual Conference & Exposition is the property of ASEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: We constructed and analyzed an evidence-based practice case to see if visual models help students develop a better understanding of abstract concepts and enhance their self-efficacy when solving engineering problems. Abstract concepts without corresponding physical phenomena are often found in the domains of industrial engineering, engineering management, and systems engineering. In this study, we focus on inventory control of a supply chain, which is typically a junior level undergraduate production systems course in an industrial engineering program. Visual models of inventory behaviors were designed to complement the traditional approach of mathematical derivations and numerical computations. In this context, we use a randomized-controlled design research framework implementing the visual models in a quiz. Pre- and post-surveys on student self-efficacy were used to assess the effects of the visual models. Students' quiz outcomes and self-efficacy surveys are compared to those from a control group that did not use the visual models, and the results from both groups were statistically analyzed. This study is motivated by engineering students' inability to understand abstract concepts and the need for continuous improvement of student learning. The results show that, within the scope of the aforementioned experiment and collected data, the visual models do help students understand abstract concepts and improve their self-efficacy. This study can serve as a basis for further studies on the extent of visual models helping students develop a complete mental model and on whether better mental models actually lead to a better understanding of the domain knowledge and enhance students' self-efficacy. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Proceedings of the ASEE Annual Conference & Exposition is the property of ASEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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              Text: 2014
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