A method for assessing computational thinking in students using source code analysis

Steven Pacheco-Portuguez, Antonio Gonzalez-Torres, Lilliana Sancho-Chavarria, Ignacio Trejos-Zelaya, Jorge Monge-Fallas, Jose Navas-Su, Alberto J. Canas, Andres Rodriguez, Carol Angulo Chinchilla

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

1 Cita (Scopus)

Resumen

This paper summarizes research in progress, at a national scale, that analyzes large volumes of elementary school and high school projects to assess the development of skills, attitudes, and practices that students develop when solving problems via computer programming, grounded on their under-standing of fundamental concepts in computing. The approach is independent of programming languages and uses a generic abstract syntax tree and projects' metadata to calculate metrics, and establish relationships between measures, school regions, educational centers, and student groups. The research relates source code analysis using abstract syntax trees to some of the main computational thinking concepts. Preliminary results obtained using the proposed method are presented and discussed.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2022 International Conference on Advanced Learning Technologies, ICALT 2022
EditoresMaiga Chang, Nian-Shing Chen, Mihai Dascalu, Demetrios G Sampson, Ahmed Tlili, Stefan Trausan-Matu
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas144-146
Número de páginas3
ISBN (versión digital)9781665495196
DOI
EstadoPublicada - 2022
Evento22nd International Conference on Advanced Learning Technologies, ICALT 2022 - Bucharest, Rumanía
Duración: 1 jul 20224 jul 2022

Serie de la publicación

NombreProceedings - 2022 International Conference on Advanced Learning Technologies, ICALT 2022

Conferencia

Conferencia22nd International Conference on Advanced Learning Technologies, ICALT 2022
País/TerritorioRumanía
CiudadBucharest
Período1/07/224/07/22

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