Title:
Evolution of the CTMM Model in the University Context Supported by AI [Download]Authors:
René Fabián Zúñiga Muñoz, Angela María Muñoz Muñoz, Marcos Román-González, Gregorio Robles
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Abstract:
This paper presents the evolution of the Computational Thinking Measuring Model (CTMM) within university contexts, integrating generative artificial intelligence tools as methodological support. It describes the gradual and reflective process of refining performance indicators, contextualizing them within engineering courses, and analyzing two new components: verification understood as the critical validation of responses provided by AI and ethics conceived as the reflection on the responsible use of these technologies in academic settings. The results demonstrate that the CTMM maintains its theoretical coherence and practical applicability, consolidating itself as a comprehensive instrument for evaluating computational thinking in higher education. The paper outlines the process of evolution and validation of the CTMM within university contexts, integrating generative artificial intelligence as a methodological tool to strengthen the assessment of computational thinking. The findings confirm the model’s relevance to engineering education and its capacity to promote reflective, ethical, and sustainable practices in the use of emerging technologies in educational environments.
DOI:
How to cite:
René Fabián Zúñiga Muñoz, Angela María Muñoz Muñoz, Marcos Román-González, Gregorio Robles, "Evolution of the CTMM Model in the University Context Supported by AI", IEEE-RITA, vol. 21, no. 1, pp. 82-90, Jan. 2026. doi: 10.1109/RITA.2026.3666426