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Record W4391225739 · doi:10.3991/ijet.v19i02.47219

10.3991/ijet.v19i02.47219

2000· article· en· W4391225739 on OpenAlexvenueno aff
Wenbo Jiang, Yuan Zhang

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumThe InternetDisciplineComputer scienceEngineering managementMathematics educationMultimediaSociologyEngineeringWorld Wide WebPsychologyPedagogySocial science

Abstract

fetched live from OpenAlex

In the face of accelerating globalisation and digitalisation, Internet technology profoundly influences various sectors, notably education. Environmental design, a vital discipline centred around human-space interaction, is increasingly recognised. This study delves into the nexus between the integration of Internet technology and environmental design education, focusing on the formulation of a cross-disciplinary curriculum framework and the evaluation of its teaching effects. Existing research methodologies present limitations, predominantly favouring short-term evaluative measures while overlooking students’ extended learning trajectories and in-depth experiences. This study addresses this gap, introducing curriculum system construction based on knowledge graph techniques, complemented by a teaching effect evaluation harnessing time series analysis. This offers not merely an academic reference but also paves a novel direction and practical strategies for educational practitioners.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.134
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.8660.814

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.208
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

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