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ADAT: A Tool for Assessing Computational Thinking Skills in Adults

10.24050/reia.v23i46.1968
Published 2026-09-17
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Abstract

Computational thinking (CT) is widely recognized as a crucial skill for adults in the digital era. However, fostering CT in this population faces challenges due to the lack of practical assessment tools and learning methods tailored to their specific needs and motivations. This paper introduces and validates ADAT, a diagnostic tool designed to evaluate adults’ CT skills, focusing on abstraction, decomposition, and algorithmic thinking. ADAT was developed by integrating elements from the Callysto Computational Thinking Test (CCTt) and the Marcos Román test. The tool was validated with two distinct groups: students from the Multimedia and Vision laboratory at the School of Systems and Computer Engineering (EISC) of Universidad del Valle, and secondary school teachers. Descriptive statistical analyses and the Wilcoxon test were employed to analyze the data. Additionally, student results were benchmarked against the 2022 Bebras questionnaire, an international initiative assessing CT skills in children and youth through problem-solving challenges. Findings indicate a high degree of congruence between ADAT and Bebras results, supporting its consistency as an assessment tool for CT skills in adults. Moreover, observed differences in skill levels between teachers and students underscore ADAT’s diagnostic value. Overall, ADAT constitutes a valid tool for assessing CT skills in adults. To the best of our knowledge, it represents the first multi-skill CT test adapted for adults in Latin America, addresses a critical gap in population-specific assessment, and informs the design of targeted teaching and learning interventions.

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