The Noticing Function of Classroom Pop Quizzes and Formative Tests in the Uptake of Lexical Items of EFL Intermediate Learners
Bibliographic record
Abstract
The main concern of the present research was to examine the effect of classroom testing in bringing up the noticing of learners using pop quizzes and formative tests. Following the noticing hypothesis by Schmidt (1990, 2001) and backwash effect of testing on teaching, we specifically tested whether noticing through testing might result in better uptake of lexical items by Iranian EFL learners. Following MacKey and Gass (2005), a comparison design study was conducted using three groups of learners with intermediate level of language proficiency. Based on the results of Oxford Placement Test, 77 female EFL students in Iran were selected and randomly assigned into three groups. The first group took pop quizzes, the second group took formative tests, and the third group was incidental learning. Since the data were not normally distributed, non-parametric tests were applied to test the hypotheses formulated for the purpose of the study. The results of the statistical tests revealed the probable positive effect of noticing function of testing on the acquisition of lexical items. The research results might be helpful for teachers to include cognitive tasks to bring up noticing and awareness of learners to facilitate input-to-intake process.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".