The Exploration and Practice of Humanization-Based Teaching Mode: Taking the Humanistic Teaching of Political Economy for Example
Bibliographic record
Abstract
Humanization-based education is student-oriented that fits into the development of human nature, keeps shaping and perfecting humanity, and unlocks the best of the individuals’ potential. The concept of humanization-based education must be reflected by humanistic teaching. During exploring its way forward in practice, humanistic teaching follows the principles to regard people as the end not instrument, concern with individual differences, respect the students’ demands, make the very most of the students’ gifts, dovetail knowledge into the system of values, and cultivate people of all-round development and profuse humanity. This study takes the teaching of political economy for example to explore the humanization-based education, designs the questionnaire aimed at the students, analyses the investigation statistically, hereby gets relatively deep knowledge of the students’ learning demands and their own learning information, and finally come up with the key points and specific measures of the humanistic teaching mode.
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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 | 0.003 | 0.006 |
| 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 | 0.002 |
| 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".