Learners’ Incidental Vocabulary Acquisition: A Case on Narrative and Expository Texts
Bibliographic record
Abstract
This study was intended to determine whether or not the genre of a reading text affects the incidental vocabulary acquisition of L2 learners while reading. To this aim, 40 Iranian EFL students whose vocabulary knowledge was within a limited range (already determined by Nation’s Vocabulary Levels Test) were divided into two groups of 20 each for the reading sections. The Narrative Group comprised the participants who read the narratives, and the Expository Group were those who read the expository texts. Three types of vocabulary tests (i.e., Form recognition, Meaning translation and Multiple-choice items) were administered after the reading sessions to assess the incidental vocabulary gains of the participants. Overall, this study demonstrated the relative superiority of expository texts over narratives in terms of enhancing readers' incidental acquisition of unknown words. It is argued that depending on the genre of a text, readers will invest processing resources with different depths and varying degrees of cognitive elaboration for the task of comprehension.
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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 | 0.010 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| 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".