Dawning of hope: Practice of and reflections on indigenous teacher education in Taiwan
Bibliographic record
Abstract
Teachers more familiar with students’ culture tend to use culturally relevant teaching methods to smooth students’ learning. Most pre-service teachers in Taiwan lack sufficient training for multicultural competence to enable them to embrace indigenous students’ culture and appropriate teaching approaches. In 2013, the Education Act for Indigenous Peoples was revised thereby requiring teachers of indigenous education to comply with the act within five years. It created huge changes and modifications to indigenous teacher education and required teachers who work in indigenous areas to complete ethnic culture and multiculture courses. All levels of government have to institute the Acts requirements within five years. Given the significance of the crucial keys to success of teaching indigenous students, it is important to understand how the government values the development of teachers’ multiculture teaching abilities. Following an outline of the tribal critical race theory (TribalCrit), the status quo of indigenous peoples’ education and teacher training in Taiwan were identified in a discussion of social justice. To make indigenous teacher education more suitable to indigenous peoples’ needs and build up a good foundation for ethnic culture development, the experiences of qualified teachers of indigenous education in the US, Canada, and Australia will be mentioned as examples. The goal for this research is to provide some useful reflections on the subsequent implementation of such efforts, and to get some inspiration for Taiwan's aboriginal teacher education in fulfillment of the Education Act for Indigenous Peoples.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.027 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.011 |
| 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".