Development of Sustainable Humanistic Education Strategies in Higher Vocational Colleges
Bibliographic record
Abstract
The objectives of this research were: 1) to study the current status of the development of sustainable humanistic education in higher vocational colleges in Hunan Province, 2) to develop strategies for the sustainable development of humanistic education in higher vocational colleges in Hunan Province, and 3 to evaluate the effectiveness of the suitability and feasibility of the sustainable development strategy of humanistic education in higher vocational colleges in Hunan Province. This study took 3351 people from 6 vocational colleges in Hunan Province as the research subjects. According to the Krejcie and Morgan (1970) sampling table, the sample group is 338 teachers, 132 school administrators, and 196 corporate mentors. The research tools include 1) a questionnaire, 2) in-depth interview, 3) focus group, and 4) evaluation effectiveness. Data analysis uses percentage, mean, standard deviation and content analysis. The research results showed that 1) the current status of development of sustainable humanistic education in higher vocational colleges in Hunan Province is at a medium level, 2) the strategies for the sustainable development of humanistic education in higher vocational colleges in Hunan Province include: (1) improve talent training programs; (2) strengthen the construction of the teaching staff; (3) innovate teaching methods; (4) enrich course content; (5) organize social practice; (6) strengthen school-enterprise cooperation; (7) establish an evaluation system, and 3) the effectiveness of the suitability and feasibility of the sustainable development strategy of humanistic education in higher vocational colleges in Hunan Province are both at a high level.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".