Pattern recognition in programming to support the evaluation of Computational Thinking

Steven Pacheco-Portuguez, Antonio Gonzalez-Torres, Lilliana Sancho-Chavarria, Ignacio Trejos-Zelaya, Jorge Monge-Fallas

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Computational thinking is a high-level skill that involves both critical and creative thinking. This research proposes an advanced method for analyzing source code to assess computational thinking skills in elementary school students. We present a large-scale approach that examines source code from various programming exercises using a generalized abstract syntax tree, enabling language-independent analysis. Clustering techniques are applied to identify different levels of computational thinking development in areas such as parallelism, data representation, abstraction and decomposition, control flow, and programming structure. The results of the automated assessment provide insights into students' computational thinking abilities across diverse populations, highlighting opportunities for improving the educational framework.

Idioma originalInglés
Título de la publicación alojadaEDUNINE 2025 - 9th IEEE Engineering Education World Conference
Subtítulo de la publicación alojadaEducation in the Age of Generative AI: Embracing Digital Transformation - Proceedings
EditoresClaudio da Rocha Brito, Melany M. Ciampi
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9798331542788
DOI
EstadoPublicada - 2025
Evento9th IEEE Engineering Education World Conference, EDUNINE 2025 - Montevideo, Uruguay
Duración: 23 mar 202526 mar 2025

Serie de la publicación

NombreEDUNINE 2025 - 9th IEEE Engineering Education World Conference: Education in the Age of Generative AI: Embracing Digital Transformation - Proceedings

Conferencia

Conferencia9th IEEE Engineering Education World Conference, EDUNINE 2025
País/TerritorioUruguay
CiudadMontevideo
Período23/03/2526/03/25

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