A Knowledge Space Theory Graph for File Organisation Mastery: From Desktop to Project-Grade Practitioner

The Document Engineering textbook series, aimed at Vietnamese learners aged 14 and up, opens with a volume on file systems whose pedagogical surface is unusually wide: the 14+ audience arrives with mature but unreflective filename and folder intuition, derived almost entirely from a Desktopdump pattern carried over from primary-school computer use. Linear curriculum design fails on this surface because individual learners enter at heterogeneous knowledge states. This paper applies Knowledge Space Theory (KST), introduced by Doignon and Falmagne in 1985 and operationalised at scale by the ALEKS system since the mid-1990s, to model file-organisation mastery as a directed prerequisite graph rather than as a linear sequence. The graph contains 36 atomic skill nodes organised in six strata: S0 Desktop-only baseline (4 nodes), S1 singlefolder organisation (5 nodes), S2 hierarchical folders plus adhoc naming (6 nodes), S3 naming convention plus folder-perproject plus dated archives (7 nodes), S4 project workflows with drafts/final/archive sub-directories plus README plus version markers (8 nodes), S5 cross-project library with templates, shared assets, and backup discipline (6 nodes). Each node carries an id, short label, prerequisite-id list, evidence-of-skill check, and characteristic misconception. The graph satisfies the KST union-closure property and admits a well-graded learningspace refinement on the Cosyn-Uzun 2009 axiomatisation. The contribution to the textbook series is a chapter-sequencing rule and an exercise-difficulty progression rule. The scope is explicitly 14+ school-project, capstone, and science-fair context; researchgrade workflow is out of scope. No cohort study is conducted; the audit loop is the quality bar per program scope.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-12
DOI
https://doi.org/10.5281/zenodo.20131572
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

A Knowledge Space Theory Graph for File Organisation Mastery: From Desktop to Project-Grade Practitioner

That Le
Zenodo (CERN European Organization for Nuclear Research)
Intelligent Tutoring Systems and Adaptive Learning
preprint

A Knowledge Space Theory Graph for File Organisation Mastery: From Desktop to Project-Grade Practitioner

That Le
preprint en

Abstract

The Document Engineering textbook series, aimed at Vietnamese learners aged 14 and up, opens with a volume on file systems whose pedagogical surface is unusually wide: the 14+ audience arrives with mature but unreflective filename and folder intuition, derived almost entirely from a Desktopdump pattern carried over from primary-school computer use. Linear curriculum design fails on this surface because individual learners enter at heterogeneous knowledge states. This paper applies Knowledge Space Theory (KST), introduced by Doignon and Falmagne in 1985 and operationalised at scale by the ALEKS system since the mid-1990s, to model file-organisation mastery as a directed prerequisite graph rather than as a linear sequence. The graph contains 36 atomic skill nodes organised in six strata: S0 Desktop-only baseline (4 nodes), S1 singlefolder organisation (5 nodes), S2 hierarchical folders plus adhoc naming (6 nodes), S3 naming convention plus folder-perproject plus dated archives (7 nodes), S4 project workflows with drafts/final/archive sub-directories plus README plus version markers (8 nodes), S5 cross-project library with templates, shared assets, and backup discipline (6 nodes). Each node carries an id, short label, prerequisite-id list, evidence-of-skill check, and characteristic misconception. The graph satisfies the KST union-closure property and admits a well-graded learningspace refinement on the Cosyn-Uzun 2009 axiomatisation. The contribution to the textbook series is a chapter-sequencing rule and an exercise-difficulty progression rule. The scope is explicitly 14+ school-project, capstone, and science-fair context; researchgrade workflow is out of scope. No cohort study is conducted; the audit loop is the quality bar per program scope.

Zenodo (CERN European Organization for Nuclear Research)
ElSohly Laboratories (United States) (US)
Quality Education
Intelligent Tutoring Systems and Adaptive Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.