An SFL-oriented Framework for the Teaching of Reading in EFL Context
Bibliographic record
Abstract
This study aimed to introduce a systematic framework for the interactive instruction of reading based on Systemic Functional Linguistics (SFL). To do so, 60 undergraduate TEFL students taking an advanced reading course were assigned to two equal groups. Both groups were pre-tested for their comparability, and then the experimental group was treated with SFL-oriented knowledge for 13 two-hour sessions with the control group just receiving the traditional grammar-oriented method of teaching reading. Following the treatment, a post-test was administered to both groups the results of which indicated that there was a significant difference at p < .05 in the performance of the two groups on reading comprehension. Detailed analyses revealed that the treated group had a better performance on understanding the lower-level intra-sentential relationships and higher-level contextual components involved in reading comprehension. It was concluded that the SFL-based teaching of reading comprehension had a great effect on the reading comprehension of Iranian TEFL students.
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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 | 0.001 | 0.060 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".