The Effect of Dynamic versus Static Assessment on Syntactic Development of Iranian College Preparatory EFL Learners
Bibliographic record
Abstract
This study investigated the effect of dynamic assessment on learners’ syntactic knowledge. The main concern of this study was significant difference between dynamic and static assessment and the possible role of these two forms of assessment on the syntactic development of Iranian EFL college preparatory learners. To fulfill the purpose of the study, NELSON was administered to 70 pre university male learners. Those learners with scores one standard deviation above and below the mean were selected for the purpose of the study. There were 60 students who were then divided into experimental and control groups. Next, the pre-test (a teacher-made, multiple-choice test) was administered to 20 subjects of parallel group. Then, twelve multiple-choice grammar tests were administered to the subjects of the experimental group. The students received mediation in dynamic assessment model which involved some strategies like looking for clues, eliminating the answers that do not fit and comparison strategies. The mediation process was designed to enable teachers to mediate each of the items in an interactive way. The mediation was divided into two stages: a) manipulation of grammatical and structural point through the strategies mentioned above and b) information paper which was given to the students at the end of each session to work on them at home. The control group received deductive grammatical rules during twelve sessions. Finally, the pre-test was re-administered as the post-test and t-test was applied. The results showed that at 0.05 level of significance the mean of experimental group was more than the mean of control group for different scores and consequently the null-hypothesis was rejected. The study proved that dynamic assessment outperformed in improving syntactic knowledge of the learners.
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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 | 0.002 | 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 | 0.000 | 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".