A Comparison of Output Interventions and Un-enhanced Reading Conditions on Vocabulary Acquisition and Text Comprehension
Bibliographic record
Abstract
This investigation assessed whether L2 readers' sensitivity towards a new lexical form is heightened if they are repeatedly pushed to produce output and are immediately provided with relevant input in input-output cycles. In addition, the study sought to assess how these interventions influence text comprehension. Fourth-semester learners read three texts, with four target words each, under the following conditions: (a) cued-output task, (b) self-selected output task, and (c) un-enhanced (control) reading. Results showed that four input-output cycles did not contribute to retain more or more robust form-meaning connections (FMCs) than the normal reading condition. In all three conditions, FMCs varied in strength and completeness, requiring different cues for retrieval. The two input-output tasks affected text comprehension differently. The self-selected output task resulted in text comprehension similar to the un-enhanced reading; the cued-output task seemed to interfere with text 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".