Abstract
The purpose of this study was to investigate the relationship between individual learning styles and the use of computer simulation in the classroom. The variables examined for this relationship were: student learning styles, interest level and use of computer simulation, affinity towards and performance in classes with computer simulation, presence of individual learning styles, field of study, and frequency of computer simulation use. Two survey instruments, the Learning-Style Inventory II (Kolb 1985) and a demographic and computer simulation questionnaire were administered to 374 college undergraduates at a small private university in northern New York. Frequency, trend, z-score test of difference, and correlational analyses were accomplished to examine relationships between learning styles and the use of computer simulation. All four learning styles were still present when computer simulation was used in the classroom but, results did indicate that learning modes were tending to be more reflective and abstract. There was a strong correlation among affinity and interest level for all students. Previous exposure correlated strongly with the freshmen and sophomore students, suggesting previous exposure is offset as students continue their academic career. A strong correlation between interest and affinity level and a low correlation between interest level and performance were found in all classes. A negligible correlation was found among performance and learning style. The results suggest a relationship among learning style, learning modes, and computer simulation is found among interest level, performance, and affinity students have for computer simulation. Furthermore, results suggest individuals using computer simulation may not change their learning style but, their learning mode will move toward a more reflective and abstract mode. Because of this movement a re-examination of the norm value for the Learning-Style Inventory II is recommended. The results of this study and others like it begin an understanding of the relationship between learning styles and computer simulation assisting universities in the development of effective computer education programs for the future.