earticle

영어

In the era of digital transformation, various attempts are constantly being made to foster software talent required to lead the future society. Accordingly, educational research is being conducted to develop computational thinking, a thinking process that uses the basic concepts of computers to solve problems. In particular, various assessment tools are being used to diagnose computational thinking. Typically, online judge systems that can solve programming problems and automatically evaluate programming code in an online environment are used, and self-report type assessment questions are used to diagnose computational thinking. However, existing online judge systems do not provide questions to diagnose computational thinking, and only present the correctness of the answer based on the execution result of the code. In addition, the self-assessment type of computational thinking assessment tool has the limitation that it is unreliable because they are subjective and lack objectivity. In this study, we develop a question instrument that can diagnose computational thinking through a different approach than the existing computational thinking assessment tools. We develop a problem context-driven item and then verify it through a data analytics-driven scheme using an online judge system. In particular, to diagnose computational thinking, we present problem situations and provide items for each specific element of computing thinking by categorizing each situation into abstraction, algorithm, and automation. In addition, based on the programming code written in the automation step, the answers in the abstraction and algorithm section are checked so that data analytics-driven question modification and verification can be made. This study provides a new direction for diagnosing computational thinking and aims to provide learners with more reliable diagnostic results.