Research on the Deep Integration of Moral Education Elements in College Students’ Career Planning Education for Intelligent Teaching and Learning
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
This paper aims to enhance the moral and vocational qualities of college students by integrating moral education elements into career planning education. The BOPPPS teaching model is constructed, comprising six modules: introduction, objectives, pre-test, participatory learning, post-test, and summary, to effectively stimulate students’ interest and initiative. Moral education elements are integrated into career planning education through an intelligent teaching platform, incorporation into teaching processes, and the use of the second classroom to promote in-class and out-of-class linkages. Additionally, a fuzzy classroom teaching evaluation system is developed to assess the effectiveness of career planning education. The results indicate high reliability and validity of the evaluation system, with an alpha coefficient exceeding 0.8, a KMO value of 0.938, and a Bartlett’s test P-value of 0.000. Students’ positive classroom mood improved significantly from 35.79% to 68.42%, alongside an enhanced evaluation of classroom learning. The findings demonstrate the practical value of this approach in advancing education reform.
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 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 | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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