Date of Award

Summer 2014

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer and Information Technology

First Advisor

James L. Mohler

Committee Member 1

Brandeis H. Marshall

Committee Member 2

Alejandra Magana

Abstract

Based on Kolb Learning Style Inventory 4.0, the objectives of this research were to demonstrate the existence of hybrid learning styles and demonstrate the existence of dynamic learning styles between subject matters (mathematics and English). Understanding an individual's dynamic distribution of learning styles might be used to further improve the quality of instruction, learning, and educational materials. Optimizing the quality of instruction, learning, and educational materials is important because careers in science, technology, engineering, and mathematics (STEM) fields are increasingly needed. Personalized learning has been identified as an area that could improve the quality of STEM education. Exploiting individuals learning styles may improve personalized learning. In this research approach a learning style inventory was given to 185 students in the College of Technology. Algorithms were developed to analyze learning ability, learning style, degree of hybridity, and dynamics. Results suggested that 43% of the students had a hybrid learning style at a confidence level of at least 99.99%. And 37% of the students had a dynamic learning style at a confidence level of at least 95%.

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