"My Personal Teaching Principle is ‘Safe, Fun, and Clear’": Reflections of a TESOL Teacher
Bibliographic record
Abstract
Reflection and reflective practice have now become common terms used in teacher education and development programs worldwide. Reflective practice generally means that teachers subject their own beliefs and practices of teaching and learning English to speakers of other languages to a critical examination. The increase in popularity of reflective practice in the field of TESOL has also brought about an array of different definitions and approaches most of which however originate from the general education literature. Thus, Farrell (2015; 2019b) developed a holistic framework for TESOL teachers to reflect, that includes reflections on five different stages, the TESOL teachers’ philosophy, principles, theory, practice, and beyond practice. This paper outlines a case study of the reflections of a TESOL teacher through the lens of this framework for reflecting on practice. Overall, the results revealed that many of Lisa’s reflections in all five stages of the framework appear to be connected through two common themes: Teaching to students’ needs and goals and student engagement and rapport building.
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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 | 0.003 |
| 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 | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".