JALT2014 Plenary Speaker article: An invitation to reflect on practice
Bibliographic record
Abstract
Reflective practice is now a common term in many teacher education and development programs worldwide. Although definitions of reflective practice may vary in different programs, it generally means teachers systematically collect information about their classroom happenings, and then analyze and evaluate this information and compare it to their underlying assumptions and beliefs so that they can make changes and improvements to their teaching. This paper outlines what reflective practice is, why it is important, and how teachers can reflect. 内省の実践（意識的に深く考え注意深く観察する）というのは世界中の多くの教員養成課程で使われている一般的な用語である。内省の実践の定義は、それぞれの教科課程で異なっているかもしれないが、一般的には、授業の向上と工夫のために、教師がクラス内の情報を体系的に集め、この情報を分析・評価し、自分達の教育の前提や信条と比較する、ということを意味している。本論では内省の実践とは何か、なぜそれが重要なのか、どのように教師は授業に反映できるかについて要点を述べる。
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".