Who is Likely to Acquire Programming Skills?

Abstract

The purpose of this study was to investigate the relationship between programming skill acquisition and various measures of individual differences, including: 1) prior knowledge and general cognitive skills (e.g., word knowledge, information processing speed); 2) problem solving abilities (e.g., ability to decompose a problem into its constituent parts); and 3) learning style measures (e.g., asking for hints versus solving problems on one's own). Subjects (N = 260) received extensive Pascal programming instruction from an intelligent tutoring system. Following instruction, an online battery of criterion tests was administered measuring programming knowledge and skills acquired from the tutor. Results showed that a large amount (68%) of the outcome variance could be predicted by a working-memory factor, specific word problem solving abilities (i.e., problem identification and sequencing of elements) and some learning style measures (i.e., asking for hints and running programs). Implications of the findings for the development of a theoretical framework on which to base programming instruction are discussed.