A Systematic Review on Learning, Teaching, and Assessing Computational Thinking Skills for Secondary Education

Leidy Carvajal-Ortiz; Deisy Chaves; María Trujillo

doi:10.3991/ijep.v16i2.55787

Authors

Leidy Carvajal-Ortiz Universidad del Valle, Cali, Colombia https://orcid.org/0000-0002-6231-4561
Deisy Chaves Universidad del Valle, Cali, Colombia https://orcid.org/0000-0002-7745-8111
María Trujillo Universidad del Valle, Cali, Colombia https://orcid.org/0000-0002-0169-1339

DOI:

https://doi.org/10.3991/ijep.v16i2.55787

Keywords:

Computational Thinking, systematic review, Teaching, Teachers, Learning

Abstract

Computational thinking (CT) has become a fundamental skill in the 21st century, especially within secondary education. However, integrating CT into teaching and learning requires the participation of teachers specialized in this area. This systematic review identifies and analyzes the most effective methods, strategies, and activities used to teach and assess secondary- level CT skills. To ensure broad and rigorous coverage of relevant research, a literature search was conducted in Scopus, Web of Science, and ScienceDirect databases, covering studies published between 2020 and 2024. The review synthesizes current educational practices, highlighting approaches such as Game-Based Learning, gamification, and assessment activities such as the Bebras Challenge. Findings reveal diverse pedagogical strategies and ongoing challenges, particularly regarding validating assessment instruments and teacher professional development. Besides, this review underscores the need for more robust, standardized assessment methods and further research to advance CT education. The insights provided are valuable for educators, policymakers, and researchers seeking to enhance CT education and its integration into engineering pedagogy.

Author Biographies

Leidy Carvajal-Ortiz, Universidad del Valle, Cali, Colombia

Leidy Carvajal is a Ph.D. candidate in Computer Science at Universidad del Valle, where she also serves as an adjunct professor. She holds a degree in Systems Engineering and a Master's degree with an emphasis in Systems Engineering and Computing from the same institution. Her doctoral research focuses on software development, computational thinking, and gamification in adults.

Deisy Chaves, Universidad del Valle, Cali, Colombia

Deisy Chaves is a Ph.D., professor, and researcher at Universidad del Valle. She holds degrees in Systems Engineering and a Master's in Systems Engineering and Computing from the same institution. In 2018, she successfully defended her doctoral thesis, earning a Ph.D. in Engineering from both the University of León, Spain, and Universidad del Valle, with cum laude distinction. Her research focuses on artificial intelligence, pattern recognition, and machine learning using digital images.

María Trujillo, Universidad del Valle, Cali, Colombia

María Trujillo is a Full Professor at Universidad del Valle. She holds a Ph.D. in Computer Vision from the University of London, United Kingdom, a Master's degree in Statistics from Colegio de Postgraduados, Mexico, and a Bachelor's degree in Statistics from Universidad del Valle.

She has participated in various research projects involving image-based data analysis. Her intellectual contributions and commitment to training human resources have earned her the distinction of Senior Researcher by Minciencias.