Use Of Myers Briggs Type Indicator In The University Of Tennessee Engage Freshman Engineering Program
Author(s) -
Tom Scott,
J. Elaine Seat,
J. Roger Parsons
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--10352
Subject(s) - graduation (instrument) , learning styles , curriculum , engineering education , style (visual arts) , subject (documents) , session (web analytics) , mathematics education , computer science , psychology , engineering , pedagogy , engineering management , world wide web , mechanical engineering , archaeology , history
The subject of student learning style has been a topic of interest in engineering education for some time. As engineering educators have struggled with how to increase retention, interest nontraditional students into the profession, and incorporate an exploding knowledge base into the curriculum, the systematic study of how students learn technical material has become increasingly important. It has become accepted that students have different learning styles and that alternate teaching styles and methods can assist the learning process. Many of the innovations in approach to engineering education and the decrease in emphasis on lecturing as the primary method of material delivery have resulted from knowledge and appreciation of student learning style. Of the many diagnostic tools available to measure learning style, The Myers-Briggs Type Indicator is probably the most commonly used. At the University of Tennessee, we have given the Myers-Briggs to engineering freshmen since 1990 and have a substantial database for engineering students that includes learning style information. In this paper we utilize this database to show the MBTI distribution for students at our university, compare this information to existing engineering student data available in the literature, explore graduation rates for different learning styles, and explore gender and minority differences in learning style and graduation rate. We also have given the MBTI to our engineering faculty and have data to demonstrate the teaching /learning style differences that a typical engineering student faces in his or her classes. We compare this information with MBTI data for educators from kindergarten through high school to show how this situation has changed for a typical student as they have progressed through their educational career. We also compare this information with existing data for engineers working in industry.
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