Ideological and Political Casting Soul, Student Center, Number of Wisdom to Empower, One Lesson More Integration—Typical Case of "Classroom Revolution" in Primary Accounting Practice
Bibliographic record
Abstract
This case integrates ideological and political elements to develop the ideological and political teaching design of "12234" course. It adheres to the concept of OBE and focuses on the student-centered problem list course content. It builds the teaching model of "MOOC+SPOC+ Flipped classroom" based on the joint course group. It creates the course assessment method of "task-driven, simulation, one-lesson integration". Form a new classroom revolution model of "ideological and political red + accounting color + wisdom features + results bright color". The results of this case are as follows: first, school-enterprise cooperation, task-driven, achieving the trinity teaching goal. Second, the integration of ideology and politics, the combination of German and technical training, to promote the all-round development of students. Third, internal and external circulation, teachers and students empowerment, curriculum reconstruction to improve teaching quality. Fourth, one lesson more integration, teaching and learning, improves the quality of employment and enterprise satisfaction. Fifth, multi-participation, whole-process assessment, to create a comprehensive teaching evaluation system.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".