Improving reading fluency and comprehension in adult ESL learners using bottom-up and top-down vocabulary training
Why this work is in the frame
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Bibliographic record
Abstract
The current research examines the effect of two methods of vocabulary training on reading fluency and comprehension of adult English as second language (ESL) tertiary-bound students. The methods used were isolated vocabulary training (bottom-up reading) and vocabulary training in context (top-down reading). The current exploratory and quasi-experimental study examines the effectiveness of these methods in two intact classes using pre- and posttest measures of students’ reading fluency and comprehension. The results show that bottom-up training had a negative impact on fluency and comprehension. In contrast, top-down training positively affected fluency but had no impact on comprehension. Further, the results do suggest that fast-paced reading may potentially lead to improved comprehension. These findings have implications for the type of language instruction used in classrooms and, therefore, for teachers of adult ESL learners.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 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 it