Analytical Methods and Tools for Evaluating the Development of Computational Thinking Abilities

Abstract

Computational thinking has gained an important place in modern education, enabling individuals to approach problem-solving in a logical and structured manner. This cross-curricular competence is important and applicable in any field of science, not just for computer science professionals. By fostering problem-solving, critical thinking, and creativity, among other skills, computational thinking is crucial in today's education. In the digital age, computational thinking is not just a technical skill, or one related to programming and robotics, but a way of thinking that can transform, or at least provide a different perspective, the way we approach everyday challenges and opportunities in our daily lives. To assess this new competency, analytical tools and methods that are not too general are needed. To achieve this, that is, to assess computational thinking, the process is currently complex and requires a combination of qualitative and quantitative methods. In this way, analytical rubrics, portfolio analysis, and standardized tests are essential tools that help provide a comprehensive and accurate assessment of students' skills related to this competence. In our project, we also work on assessing computational thinking using Bebras-type tasks and applying data analysis. Data analysis facilitates the continuous improvement of teaching and assessment methods. By monitoring and analyzing data over time, educators can identify the most effective strategies and make adjustments to improve learning outcomes. In this paper, we introduce COMATH, an assessment tool grounded in research, which has undergone two phases of piloting across six counties. This process involved collaboration with subject-matter experts and the participation of over 4500 students and 100 teachers. We employ tasks designed to evaluate computational thinking and share some of the findings we have gathered to date.