A Scoping Review of Empirical Research on Recent Computational Thinking Assessments

Abstract

Computational thinking (CT) is regarded as an essential twenty-first century competency and it is already embedded in K-12 curricula across the globe. However, research on assessing CT has lagged, with few assessments being implemented and validated. Moreover, there is a lack of systematic grouping of CT assessments. This scoping review examines 39 empirical studies published within the last five years, coded by the specific competencies outlined in existing CT frameworks, to identify and classify the key features of existing CT assessments. Results show that most studies target K-12 settings, focus on interventions that promote CT concepts and practices, adopt a quasi-experimental design, use selected-response items as the dominant testing form, and mainly assess algorithmic thinking, abstraction, problem decomposition, logical thinking, and data. Finally, few CT assessments have been validated in educational settings. Implications include identifying gaps in the CT assessment literature, deepening our understanding of the nature of CT, focusing on the validation of CT assessments, and guiding researchers and practitioners in choosing developmentally appropriate CT assessments. Cognitive and educational implications for future research inquiry include the development of new assessment tools that comprehensively assess CT and its relation to learning.