In Search of the Knowledge Base of Language Teaching: Explanations by Experienced Teachers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper examines aspects of the knowledge base that experienced English as a second language (ESL) teachers draw on in their teaching, primarily in giving explanations of grammar and other language points. The paper focuses on three categories of teacher knowledge: content knowledge, pedagogical content knowledge, and knowledge of learners (Shulman, 1987). Observations of and interviews with four experienced ESL grammar teachers about their classroom explanations are analyzed using this framework. The results indicate that these three categories of knowledge are intertwined in complex ways as they are played out in the classroom and in teacher thinking. This knowledge base and the actions it leads to are further seen to be fundamentally process-oriented. It is argued that the knowledge base itself should be integrated into language teacher education programs and that its complex and process-oriented nature needs to be taken into account in language teacher education curriculum design.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it