A Competency-Based Conceptual Framework and Assessment Method for Computational Thinking: Application to the Abstraction Competency

Computational Thinking (CT) has emerged as a key competency in K–12 education; however, its assessment remains fragmented due to the lack of shared conceptualizations and coherent evaluation frameworks. This study proposes a conceptual framework and an assessment method for CT competencies, and illustrates its application with sixth-grade students in lower secondary education in Colombia. The framework is articulated through competencies, learning outcomes, assessment criteria, and achievement indicators. Methodologically, a conceptual framework for CT was first formulated, organized into three competencies: Abstraction, Decomposition, and Algorithmic Thinking. Subsequently, a rubric-based assessment method was designed to assign achievement levels according to defined thresholds. The method was empirically applied to the Abstraction competency using the Tower of Hanoi problem. Evidence was collected through Moodle questionnaires aligned with each learning outcome and was analyzed at two moments: pre-test and post-test. The results show that the method enables performance to be classified in a structured, traceable, and interpretable manner, preserving the internal differentiation of the Abstraction competency and making visible redistributions, stability, or absence of change in achievement levels. It is concluded that the conceptual framework and the assessment method provide a useful methodological basis for competency-based assessment of CT in educational contexts. However, further studies are required to examine its performance in other samples, grade levels, and CT competencies.