A Path Modeling Study on the Integration of Science and Technology and Education for Quality Improvement of Vocational Education
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".