Direct Phonemic Awareness Instruction as a Means of Improving Academic Text Comprehension for Adult Language Learners
Bibliographic record
Abstract
At an international branch campus of a Canadian university located in Qatar, difficulty comprehending academic English text has been an institutionally acknowledged barrier to student success. A team of teacher-researchers in the English for Academic Purposes program conducted a quasi-experimental investigation into the efficacy of phonemic awareness instruction as a means of addressing this competency gap. This project was conducted in an attempt to achieve better alignment between teaching strategies, classroom activities, and student learning outcomes. Sixty-seven students, enrolled in three program level s, were given one hour per week of standardised direct phonemic awareness instruction over a 10-week period. Two tests were used to measure pre-/post-instruction differences: a missing vowel identification test and a C-test. Learners in the treatment group improved significantly more in both measures than those in the control group. The results suggest that direct phonemic awareness instruction can promote the development of both vowel recognition and ability to comprehend academic English text among tertiary-level EAP learners in a predominantly native Arabic language environment.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".