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Improving Computational Thinking Through Teacher Development (#2444)

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Date of Conference

July 15-17, 2026

Published In

"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"

Location of Conference

Santiago (Chile)

Authors

Sánchez Gómez, Juan Sebastián

Valdez Cervantes, Libis

Abstract

This paper examines how targeted institutional interventions can strengthen Computational Thinking (CT) in public schools by simultaneously improving teacher professional development and tertiary education provision. Situated at the Cartagena Node of Telematics and Teleinformatics within Colombia’s national Nodos de Pensamiento Computacional strategy, the study employs a design-based implementation approach combining mentoring cycles, protected professional learning time, micro-credential pathways, and a structured calendar of career guidance activities co-developed with nearby technical institutes and universities. Evidence from implementation artifacts, teacher reflections, and student surveys indicates increased teacher engagement, clearer curricular alignment of CT across subjects, and higher student awareness of postsecondary options in computing and related fields. The intervention also introduced managerial routines, peer observation, lesson study, and lightweight indicators for practice and tertiary awareness, supporting continuous improvement. While the short time horizon limited detection of downstream learning and enrollment outcomes, the results demonstrate early cultural and structural shifts consistent with scalable adoption under typical public-school constraints. The contribution is twofold: (i) a replicable model that links practice-embedded teacher learning to classroom CT enactment; and (ii) an operationalization of tertiary projection as a routine, data-tracked school function. The approach advances SDG 4 and SDG 9, aligning CT education with entrepreneurship, employability, and regional innovation pathways, and outlines priorities for longitudinal evaluation and scale-out.

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