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Record W4409793720 · doi:10.61091/jcmcc127a-198

A Path Modeling Study on the Integration of Science and Technology and Education for Quality Improvement of Vocational Education

2025· article· en· W4409793720 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Combinatorial Mathematics and Combinatorial Computing · 2025
Typearticle
Languageen
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsVocational educationPath (computing)Quality (philosophy)Engineering managementMathematics educationEngineeringComputer scienceMedical educationSociologyPedagogyPsychologyMedicinePhysics

Abstract

fetched live from OpenAlex

The integration of science and education is conducive to promoting the integrated development of education, science and technology, and talents, and is a key path for the high-quality development of vocational education and serving the strategy of a strong education nation.This paper explains the necessity of integrating science and technology with education, and realizes the path design of vocational education quality improvement based on the new concept of science and education integration.Then, the quality of science and education integration in vocational education is evaluated using hierarchical analysis and fuzzy comprehensive evaluation.Then, a comparison test is designed and independent sample t-test is applied to verify the practicality of the path in this paper.In the criterion layer of the established evaluation index system, the weight of industry-university-research integration is the largest, which is 23.91%, indicating that industry-university-research integration is particularly important in the path of vocational education quality improvement.In the indicator layer, the research team building has the largest weight, 10.17%, which needs to be emphasized in the implementation of the integration of science and education in vocational education.The overall rating of the quality of science and education integration in H higher vocational colleges implementing the path of this paper is 84.638, which is between good and very good, and is at a high level.And the twosided Sig value of the T-test of the evaluation score of the quality of science and education integration in the higher vocational colleges and universities using this paper's pathway and those using the traditional education model is 0.000<0.05,which is a significant difference.It indicates the practicality of this paper's path for improving the quality of vocational education based on science and education integration.This paper provides a path paradigm for improving the quality of vocational education using science and education integration.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.356
Teacher spread0.324 · 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