Computers and Education Open (Dec 2021)
Instructional interventions for computational thinking: Examining the link between computational thinking and academic performance
Abstract
Teaching computational thinking (CT) has become a priority for educators and policymakers tasked with educating and training students for future jobs which are predicted to be increasingly automated. Recent research on effective instructional interventions for developing computational thinking skills, including algorithmic and critical thinking, problem-solving, creativity, and cooperativity, suggests that teaching and learning CT can improve student academic performance. In fact, the extant literature is quite sanguine about the topic of CT. However, few studies have attempted to establish a relationship between CT skills and academic performance.In the present cross-sectional study, we employ path analysis to model the structural relationship between self-reported CT skills and academic performance of a sample of 81 computer science undergraduates enrolled at a Southwestern American university. We found few direct relationships between CT skills and academic performance. We only find a significant positive relationship between creativity and academic performance and a significant negative relationship between cooperativity and academic performance. Our findings are surprising considering the abundant research promoting computational thinking as a key component of 21st century skills. The findings call for further in-depth analysis of computational thinking and the influence on students’ learning and learning outcomes. We discuss our results with respect to recent educational mandates for including CT and instructional alignment in school curricula. Our findings contribute to the existing discussion by helping to clarify the relationship between CT skills and academic performance in higher education.
