The Relationship Among Receptive and Expressive Vocabulary, Listening Comprehension, Pre-Reading Skills, Word Identification Skills, and Reading Comprehension by Children With Reading Disabilities
Bibliographic record
Abstract
PURPOSE: Some researchers (F. R. Vellutino, F. M. Scanlon, & M. S. Tanzman, 1994) have argued that the different domains comprising language (e.g., phonology, semantics, and grammar) may influence reading development in a differential manner and at different developmental periods. The purpose of this study was to examine proposed causal relationships among different linguistic subsystems and different measures of reading achievement in a group of children with reading disabilities. METHODS: Participants were 279 students in 2nd to 3rd grade who met research criteria for reading disability. Of those students, 108 were girls and 171 were boys. In terms of heritage, 135 were African and 144 were Caucasian. Measures assessing pre-reading skills, word identification, reading comprehension, and general oral language skills were administered. RESULTS: Structural equation modeling analyses indicated receptive and expressive vocabulary knowledge was independently related to pre-reading skills. Additionally, expressive vocabulary knowledge and listening comprehension skills were found to be independently related to word identification abilities. CONCLUSION: Results are consistent with previous research indicating that oral language skills are related to reading achievement (e.g., A. Olofsson & J. Niedersoe, 1999; H. S. Scarborough, 1990). Results from this study suggest that receptive and expressive vocabulary knowledge influence pre-reading skills in differential ways. Further, results suggest that expressive vocabulary knowledge and listening comprehension skills facilitate word identification skills.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".