Portada 24566

DOI:

https://doi.org/10.14483/22487638.24566

Publicado:

30-09-2026

Número:

Vol. 30 Núm. 89 (2026): Julio - Septiembre

Sección:

Investigación

Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept

Integración del tiempo de reacción serial visual y árboles de decisión binaria para la evaluación del aprendizaje implícito: una prueba de concepto metodológica

Autores/as

Palabras clave:

implicit learning, unconscious learning, binary trees, Visual Serial Reaction Time (VSRT), Java (en).

Palabras clave:

aprendizaje implícito, aprendizaje inconsciente, arboles binarios, tiempo de reacción visual serial (VSRT), Java (es).

Resumen (en)

Context: This investigation assessed whether repeated exposure to visual-spatial patterns and guided micro-interactions could lead high school and first-year engineering students to internalize formal rules. By combining implicit learning tools (e.g., VSRT) with explicit tools, such as a binary tree calculator.
Objective: This study aims to determine whether stable patterns and low-friction actions increase implicit learning, structured reasoning, and algebraic manipulation compared with historical baseline performance.
Methodology: A concurrent mixed-methods design was used to recruit 40 participants from a purposive historical sample of 153 students. Quantitative (VSRT accuracy, interaction statistics) and qualitative (28 interviews until theoretical saturation) analyses were performed using thematic analysis and decision trees.
Results: The participants achieved an accuracy of 84% in recognizing VSRT patterns, exceeding the previous average of 70% and showing clear improvement. Repetition and familiarity with tasks were found to be important factors that influenced progress.
Conclusions: Implicit VSRT training combined with explicit visualization is an efficient method for teaching hierarchical content. Such dual approaches enhance academic performance as well as structural understanding and can be evidenced by repetition and familiarity as pivotal techniques. This study provides a strong model for STEM education interventions that link implicit and explicit cognitive systems.

Resumen (es)

Contexto: Esta investigación evaluó si la exposición repetida a patrones visuoespaciales y micro interacciones guiadas podría llevar a estudiantes de secundaria y de primer año de ingeniería a internalizar reglas formales. Para ello, se combinaron herramientas de aprendizaje implícito (por ejemplo, Visual Serial Reaction Time – VSRT) e instrumentos explícitos (como una calculadora de árboles binarios).
Objetivo: Identificar si patrones estables y acciones de baja fricción permiten un aumento en el aprendizaje implícito, el razonamiento estructurado y la manipulación algebraica en comparación con un desempeño histórico de referencia.
Metodología: Mediante un diseño mixto concurrente, se evaluó a 40 participantes de una muestra intencional de un grupo histórico de 153 estudiantes. Se analizaron datos cuantitativos (precisión en VSRT, estadísticas de interacción) y cualitativos (28 entrevistas hasta saturación teórica) a través del análisis temático y árboles de decisión.
Resultados: Los estudiantes lograron un reconocimiento de patrones con un 84 % de aciertos, superando el promedio histórico del 70 %, lo que representa una mejora notable. Se encontró que la repetición y la familiaridad con las tareas fueron factores determinantes para este progreso.
Conclusiones: El entrenamiento implícito mediante VSRT combinado con visualización explícita representa un método de enseñanza eficiente para contenidos jerárquicos. Tales enfoques duales mejoran el rendimiento académico y el entendimiento estructural, evidenciado por la repetición y familiaridad como técnicas clave. Este estudio ofrece un modelo sólido para intervenciones educativas en STEM que vinculan los sistemas cognitivos implícitos y explícitos.

Biografía del autor/a

Iván Fernando Leal Ramírez, Universidad Pedagógica y Tecnológica de Colombia

Ingeniero de Sistemas y Computación. Universidad Pedagógica y Tecnológica de Colombia, Tunja, Colombia

Henry Montaña Quintero, Universidad Distrital Francisco José de Caldas

Ingeniero Electrónico. Universidad Distrital Francisco José de Caldas, Bogotá, D.C.

Eduardo Avendaño Fernández, Universidad Pedagógica y Tecnológica de Colombia

Ingeniero Electrónico. Universidad Pedagógica y Tecnológica de Colombia. Sogamoso, Colombia

Referencias

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Cómo citar

APA

Leal Ramírez, I. F., Montaña Quintero, H., y Avendaño Fernández, E. (2026). Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept. Tecnura, 30(89), 89–106. https://doi.org/10.14483/22487638.24566

ACM

[1]
Leal Ramírez, I.F. et al. 2026. Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept. Tecnura. 30, 89 (sep. 2026), 89–106. DOI:https://doi.org/10.14483/22487638.24566.

ACS

(1)
Leal Ramírez, I. F.; Montaña Quintero, H.; Avendaño Fernández, E. Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept. Tecnura 2026, 30, 89-106.

ABNT

LEAL RAMÍREZ, Iván Fernando; MONTAÑA QUINTERO, Henry; AVENDAÑO FERNÁNDEZ, Eduardo. Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept. Tecnura, [S. l.], v. 30, n. 89, p. 89–106, 2026. DOI: 10.14483/22487638.24566. Disponível em: https://revistas.udistrital.edu.co/index.php/Tecnura/article/view/24566. Acesso em: 2 oct. 2026.

Chicago

Leal Ramírez, Iván Fernando, Henry Montaña Quintero, y Eduardo Avendaño Fernández. 2026. «Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept». Tecnura 30 (89):89-106. https://doi.org/10.14483/22487638.24566.

Harvard

Leal Ramírez, I. F., Montaña Quintero, H. y Avendaño Fernández, E. (2026) «Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept», Tecnura, 30(89), pp. 89–106. doi: 10.14483/22487638.24566.

IEEE

[1]
I. F. Leal Ramírez, H. Montaña Quintero, y E. Avendaño Fernández, «Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept», Tecnura, vol. 30, n.º 89, pp. 89–106, sep. 2026.

MLA

Leal Ramírez, Iván Fernando, et al. «Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept». Tecnura, vol. 30, n.º 89, septiembre de 2026, pp. 89-106, doi:10.14483/22487638.24566.

Turabian

Leal Ramírez, Iván Fernando, Henry Montaña Quintero, y Eduardo Avendaño Fernández. «Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept». Tecnura 30, no. 89 (septiembre 30, 2026): 89–106. Accedido octubre 2, 2026. https://revistas.udistrital.edu.co/index.php/Tecnura/article/view/24566.

Vancouver

1.
Leal Ramírez IF, Montaña Quintero H, Avendaño Fernández E. Integrating Visual Serial Reaction Time and Binary Decision Trees for the Evaluation of Implicit Learning: A Methodological Proof of Concept. Tecnura [Internet]. 30 de septiembre de 2026 [citado 2 de octubre de 2026];30(89):89-106. Disponible en: https://revistas.udistrital.edu.co/index.php/Tecnura/article/view/24566

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