Proceedings of the Annual Meeting of the Cognitive Science Society

With the ever-increasing need for teaching computational thinking (CT) to learners of the digital age, teacher educatorsneed to better guide teachers to embed CT activities across subjects and contexts while discovering the positive effectsof computer programming in K-12 education. However, computational thinking assessment (CTA) have yet to be fullyunderstood in the literature. To address this challenge, this paper used text mining with the aim of reviewing CTA in theliterature for both pre-service and in-service educators. By analyzing 267 papers, we identified 14 clusters of CTA topicsby exploring the application of computational techniques including rudimentary vector space models and unsupervisedmachine learning algorithms. We also performed a network analysis for further interpretation of our unsupervised machinelearning results. This visualization of the network allows us to select main themes and perform an exploratory factoranalysis. Implications for educational design and future research are discussed.