Dictogloss as a Technique to Raise EFL College Students’ Knowledge of Grammar, Writing and the Comprehension of Meaning
Bibliographic record
Abstract
Dictogloss is a classroom activity where all the four skills work together. The present study is an experimental one where a group of twelve students was taught by the researchers. The researchers train students to use dictogloss technique for twelve lectures. In each lecture, they used a new authentic text with a new focus on a specific role of grammar. The study aims at; finding out the impact of using dictogloss technique on Iraqi EFL college students’ knowledge of grammar, determining the impact of using dictogloss technique on Iraqi EFL college students’ improvement of writing, determining if there is any impact of using dictogloss technique on EFL college student’s comprehension of meaning and determining students’ attitudes toward using dictogloss in English language teaching. Four measurement tools were used in this study; an achievement test, a reflection sheet used at the end of each lecture, a questionnaire, and in addition to the teacher’s daily observation. Final results of the study clarify that there is a positive impact of dictogloss technique on the three variables in addition to the positive attitudes of students towards using dictogloss in English language teaching. So, the hypotheses of the study are rejected.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".