Learning Styles of Computer Science I Students

We conducted a study to investigate how learning styles related to the introductory Computer Science I course: the learning styles of the student population that took the course; course completion rates as they related to learning styles; relationship between the final grade in the course and learning styles; and the correlation between project and assignment completion rates and learning styles. We found that students in the course preferred active, sensing, visual and sequential learning styles. There was no significant difference in the course completion rates along any dimension that could not be explained based on prior preparation. Reflective and intuitive learners earned better grades in the course than active and sensing learners. While male students earned better grades than female students and traditionally represented students earned better grades than underrepresented students, these differences may be attributable to differences in prior preparation. In this context, SAT scores were found to be better predictors of student grades in Computer Science I than high school GPA. Programming projects in the course favored reflective students whereas online assignments favored sensing and sequential learners - unsurprising, since the design of these course instruments were congruent with the definition of these learning styles. It is hoped that this study provides insight into the types of course activities that might be incorporated into Computer Science I to accommodate the different learning styles of students.