Why Students Cannot Easily Integrate Component Skills: An Investigation of the Composition Effect in Programming

Abstract

Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills—a challenge called the composition effect. This effect was first studied in learning mathematics, and findings in that area have led to more effective instruction in mathematics. In the current work, we systematically investigate the nature of the composition effect in novice code tracing through a classroom study in a university-level introductory programming course. We designed a set of problems that require integrating component skills, along with matched problems that use the same component skills separately. The composition effect was defined as the performance difference between these two types of problems. We further singled out errors that were committed in integration problems but not in the matched problems and conducted qualitative coding to categorize these errors. Statistical analyses produced three main findings. First, we found a robust composition effect across problems and students, mostly with small or medium effect sizes. Second, we identified two potential sources of errors for this composition effect: conceptual misunderstandings of how to integrate component skills and process errors resulting from slips related to cognitive load challenges. In particular, additional conceptual knowledge often appears to be needed when component skills are integrated in specific ways. Moreover, the primary source appears to be misunderstandings of how skills integrate. Composition effects may not generalize across topics, which suggests that domain topics may serve as the conceptual basis for the composition effect. Third, we found stable individual differences in susceptibility to the composition effect in both overall and finer-grained levels. Our findings provide implications for building theories that may generally explain challenges in learning complex skills and may result in practical designs for skill integration enhanced curricula and instruction to foster student mastery in computing education.