Elementary School EFL Learners' Vocabulary Learning: The Effects of Post-Reading Activities
Bibliographic record
Abstract
Abstract: As language learning involves the acquisition of thousands of words, teachers and learners alike would like to know how vocabulary learning can be fostered, especially in EFL settings where learners frequently acquire impoverished lexicons, despite years of formal study. Research indicates that reading is important but not sufficient for second-language vocabulary learning, and that it should be supplemented by post-reading activities to enhance students' vocabulary knowledge. The present study investigates the effects of two types of post-reading activities: discrete written tasks on their own and a combination of written tasks along with interactive tasks on the vocabulary acquisition of young learners in an EFL setting. A total of 62 Grade 6 students in two classes in a public school in Turkey participated in the study. Data were collected by the Cambridge English Test (CYLET) and Vocabulary Knowledge Scale (VKS). Results showed that the experimental group students outperformed the control group students in acquisition of both selected and unselected vocabulary items. The use of interactive tasks as post-reading activities proved to be an effective way of enhancing the L2 vocabulary knowledge of young learners.
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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 | 0.002 |
| 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) | 0.002 | 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".