A Model for EFL Materials Development within the Framework of Critical Pedagogy (CP)
Bibliographic record
Abstract
Critical pedagogy (CP) is implemented in ELT programs aiming to empower both teachers and learners to unmask underlying cultural values and ideologies of educational setting and society, and subsequently to make them agents of transformation in their society. However, despite the increase in the number of publications in the field of critical L2 pedagogy, remarkably little has been done on materials development in CP. Considering materials as the core resources in language-learning programs (Richards, 2010), the present paper attemptsed to offer a model for ELT materials development based on the major tenets of critical pedagogy. The principles of the model were organized according to the main factors involved in materials development, i.e. program, teacher, learner, content, and pedagogical factors. This model is sensitive to the particularities of the local context and to the learner’s problems and concerns. It offers ways to help the learners to improve their second language skills while developing a sense of critical consciousness of issues of social structures in the world around them. It could be helpful for local materials writers and language teachers in developing and critically evaluating ELT materials. Subsequently, the model might contribute to students to be more critical consumers of information.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".