| The purpose of this study was to determine the effect of learning style preference on course performance of non-traditional students enrolled in an undergraduate computer science program. Kolb's Learning-Style Inventory was used to assess students' learning style preferences in four learning style types: Converger, Diverger, Assimilator, and Accommodator. All computer science courses were classified according to content type: survey (concept generalizations), programming language (syntax and structure), advanced programming language (self-directed experimentation), and theory/analytical (abstract conceptualization). Instructor teaching style preference was determined using Lieberman's Teaching Style Self-Assessment.;The sample consisted of 16 different instructors, teaching a total of 25 sections of 13 different courses, and 213 enrollments. A three-way ANOVA was used to compare student course performance based on the four course groupings, the four learning style preferences, and the four teaching style orientations. The results indicated the difference in course grades was significant based on the course type, learning style preference, and teaching style preference for p-values of 0.110, 0.100, and 0.104, respectively. The course grade difference based on combined effects of the independent variables was significant for a p-value of 0.094. Although these levels of significance are problematic, the results support the need for computer science curriculum designers to consider a variety of learning activities in specific types of courses. |
