Teaching Algorithm Selection: A Spine-Cluster Curriculum Architecture for Vietnamese Olympiad Informatics Training

Students on the specialized informatics track (Vietnamese: chuyên Tin) in Vietnam can memorize and reproduce classical algorithms but frequently fail to recognize which algorithm should be applied to a novel problem. The gap between declarative algorithmic knowledge and the ability for contextual deployment has been widely documented in cognitive science (Chi, Feltovich, & Glaser, 1981; Davies, 1990) but has not been addressed by any existing competitive-programming training curriculum. This paper proposes the Spine-Cluster architecture: a linear spine describing the development of cognitive skills combined with clusters of problem variants for each algorithmic concept. The architecture shifts the axis of organization from algorithmic content to algorithm-selection skill (in Davies's terminology), integrating interleaving, scaffolding fading, and mastery tracking. We describe the system design, an AI-mediated tutor built on Gemini, a simulation experiment executed to validate the correctness of the dispatch policy, and a validation plan targeting specialised-informatics students.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-12
DOI
https://doi.org/10.5281/zenodo.20131501
Primary Topic
Teaching and Learning Programming
Type
preprint
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preprint

Teaching Algorithm Selection: A Spine-Cluster Curriculum Architecture for Vietnamese Olympiad Informatics Training

That Le
Zenodo (CERN European Organization for Nuclear Research)
Teaching and Learning Programming
preprint

Teaching Algorithm Selection: A Spine-Cluster Curriculum Architecture for Vietnamese Olympiad Informatics Training

That Le
preprint en

Abstract

Students on the specialized informatics track (Vietnamese: chuyên Tin) in Vietnam can memorize and reproduce classical algorithms but frequently fail to recognize which algorithm should be applied to a novel problem. The gap between declarative algorithmic knowledge and the ability for contextual deployment has been widely documented in cognitive science (Chi, Feltovich, & Glaser, 1981; Davies, 1990) but has not been addressed by any existing competitive-programming training curriculum. This paper proposes the Spine-Cluster architecture: a linear spine describing the development of cognitive skills combined with clusters of problem variants for each algorithmic concept. The architecture shifts the axis of organization from algorithmic content to algorithm-selection skill (in Davies's terminology), integrating interleaving, scaffolding fading, and mastery tracking. We describe the system design, an AI-mediated tutor built on Gemini, a simulation experiment executed to validate the correctness of the dispatch policy, and a validation plan targeting specialised-informatics students.

Zenodo (CERN European Organization for Nuclear Research)
ElSohly Laboratories (United States) (US)
Quality Education
Teaching and Learning Programming
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