An Action Research on Infusing Moral and Political Education into College English Teaching from the Perspective of New Liberal Arts
Bibliographic record
Abstract
Under the background of new liberal arts, the era of "great foreign languages" requires college English teaching in local applied colleges and universities to break through the barriers of result-centred traditional teaching and bravely shoulder the important task of "moral and political education". In order to guide teachers to carry out this key task effectively, the present study preliminarily builds a teaching model in which four links of curriculum moral and political goals, teaching content, implementation steps and curriculum evaluation are interrelated. After a semester of teaching practice, the students participants are not satisfied with such an English teaching model integrated with moral and political education. The teacher participants do not understand the connotation of curriculum moral and political education, how to integrate moral and political goals with knowledge and ability goals, on how much degree to integrate moral and political education with college English teaching, and what is the standard to evaluate such a comprehensive course. Most of them hope to be guided by experts and learn from the demo courses. Therefore, this study further accurately sets teaching goals, determines systematic teaching content, highlights the gradual teaching process, and integrates teaching evaluation methods to reconstruct a dynamic and systematic teaching model of moral and political education into the course of college English, in order to provide teachers with standards and norms of moral and political education in the course of college English, and help teachers design excellent courses of moral and political education in the course of college English, so as to provide a guarantee for local colleges and universities to train applied and qualified talents.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".