Learning style and factors contributing to success in an introductory computer science course

Abstract

An introductory course in computer science (CS1) is required of virtually all engineering majors at the University of Minnesota Duluth. From 2001-present an extensive battery of visualization software was developed for this course. Students consistently ranked the visualization software as more important to their learning than any other element of the course. However, these rankings were not highly correlated with actual outcomes. This study of learning style determined that reflective and verbal learners outperformed active and visual ones. Student opinions of the value of programming projects and lectures rank highest and seem to cut across learning style preference. Background familiarity with computers and software was not a strong correlate, although involvement in computer and video gaming was found to be negatively correlated with course success.

Using Learning Styles and Preferences to Incorporate Emerging E-Learning Tools in Teaching

“…For example, Chamillard and Karolick report that the reflective and verbal learners performed better than others [16]. Similar findings are reported by [17] and [18].…”

The Significance of Learning Style with Respect to Achievement in First Year Programming Students

“…They concluded that whilst learning style was not significant, it was noticeable that there was a preponderance of Convergers who had selected the programming course, an area which warrants further study. Similarly, Gomes and Mendes [12] found little or no correlation between the achievement and learning style of first year programming students, however Allert [13] reported a difference. Goold and Rimmer [14] maintain that students with a high relative abstraction score tend to do well in computing, a position that is supported by the results of this study.…”

Understanding Learning Styles, Attitudes and Intentions in Using e-Learning System: Evidence from Brunei

“…Another model is the Myers and Briggs Type Indicator (MBTI) (Myers, 1962) that was based on personality types. However, Allert (2004) stated that there were two dominant learning style assessment tools used in science and engineering education. For Kolb's KLSI and Felder-Silverman's (LSI), both these models measured four different dimensions of an individual's learning style.…”