Research on Deepening the Integration of Industry and Education to Empower Undergraduate Vocational Education in Business Administration
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.
Bibliographic record
Abstract
Deepening the integration of industry and education is a crucial path to promote vocational undergraduate education in Business Administration to meet the requirements of the digital economy era and empower the cultivation of high-quality technical and skilled management talents. Addressing the practical problems existing in the current training model, such as ambiguous goal orientation, disconnection between the curriculum system and industry, insufficient practical ability of teachers, and superficial school-enterprise cooperation, this paper constructs a "five-dimensional synergy" theoretical mechanism based on educational ecology and collaborative governance theory, with curriculum synergy, practice synergy, teacher synergy, innovation synergy, and evaluation synergy as the core. The research proposes that a systematic implementation path should be adopted, including jointly building a substantive modern industry college, constructing a close-knit community of interests, promoting the construction of a digital practical teaching system, and strengthening the "dual-qualified" teacher team, to reconstruct a talent training model that is competency-based and highlights the characteristics of digitalization and combat readiness. This will realize the organic connection of the education chain, talent chain, industrial chain, and innovation chain, and provide solid talent support for industrial transformation and upgrading.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it