Technical Papers
Oct 19, 2018

Assessing Engineering Students’ Ethics Learning: Model of Domain Learning Framework

Publication: Journal of Professional Issues in Engineering Education and Practice
Volume 145, Issue 1

Abstract

The aim of this work was to examine the use of the Model of Domain Learning (MDL) framework to determine the level of students’ ethics learning during their progress in the engineering curriculum, considering three constructs through which learning is gained: knowledge, strategic processing, and interest. The MDL has been validated and used in different fields to predict the stages of student development and its relation to important constructs contributing to learning. This study was conducted to demonstrate that the MDL framework is effective in assessing ethics learning in engineering education. For this purpose, a questionnaire was developed based on the MDL framework and administered to 940 students from freshmen to seniors. The questionnaire consisted of 31 items divided into three sets of questions: (1) demographics, (2) multiple choices to measure knowledge and strategic processing, and (3) Likert scale to measure students’ interest level in ethics. The results revealed that there is a progressive increment in knowledge and strategic processing as students advance in their studies, while the level of interest remains statistically the same, and a significant correlation between knowledge and strategic processing in the development of ethical awareness and reasoning in engineering students. Consequently, the assessment instrument based on the MDL framework can be used to effectively measure the ethics learning in engineering education in a progressive form, taking into consideration the components and stages of learning.

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Acknowledgments

This work was supported by the National Science Foundation under Grant No. DUE 1141001.

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Go to Journal of Professional Issues in Engineering Education and Practice
Journal of Professional Issues in Engineering Education and Practice
Volume 145Issue 1January 2019

History

Received: Feb 16, 2018
Accepted: Jun 13, 2018
Published online: Oct 19, 2018
Published in print: Jan 1, 2019
Discussion open until: Mar 19, 2019

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Authors

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Ivan Esparragoza [email protected]
Professor, Division of Engineering, Math and Information Science and Technology, Penn State Brandywine, Media, PA 19063 (corresponding author). Email: [email protected]
Abdullah Konak
Professor, Information Science and Technology, Division of Engineering, Business and Computing, Penn State Berks, Reading, PA 19610.
Sadan Kulturel-Konak
Professor, Management Information Systems, Division of Engineering, Business and Computing, Penn State Berks, Reading, PA 19610.
Gul Kremer
Professor, Dept. of Industrial Engineering, Iowa State Univ., Ames, IA 50011.
Kristen Lee
Assistant Director, Center for Institutional Planning and Effectiveness, Univ. of San Francisco, San Francisco, CA 94117.

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