The Establishment of Task-Based Teaching Design Courses for Developing Pedagogical Design Ability of Pre-service Teachers in Chinese Normal Universities
Bibliographic record
Abstract
This study presents the design process of a task-based teaching design course in Chinese universities. The aim is to enhance the teaching design capabilities of candidates in Chinese language and literature while addressing the shortcomings of current teaching design courses in these institutions. To achieve this, task-based teaching has been incorporated into the curriculum. Utilizing the task-based teaching framework, the course was created through discussions among a group of experts. Once the course design was finalized, it was implemented for a semester at a university in China. The primary goal of this course is to foster the teaching design skills of Chinese language and literature pre-service teachers. This study outlines the course structure, designs teaching units, and details teaching activities among other components. Additionally, it explores the factors that should be considered when developing a task-based teaching design course. The findings aim to provide guidance for universities looking to implement such a course and to improve the teaching design capabilities of pre-service teachers in Chinese language and literature.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".