Phonological Awareness Instruction: Opinions and Practices of Educators and Speech-Language Pathologists in West Virginia
Bibliographic record
Abstract
PHONOLOGICAL AWARENESS INSTRUCTION: OPINIONS AND PRACTICES OF EDUCATORS AND SPEECH-LANGUAGE PATHOLOGISTS IN WEST VIRGINIA By Melinda J. Daniel Research has shown phonological awareness to be a strong predictor of literacy. To support literacy development, a phonological awareness project was piloted in several West Virginia schools in 2001. This study compared WV educators based on employment setting (schools participating and those not participating in the phonological awareness project) and professional category (classroom teacher, reading specialist, speech-language pathologist) on answers to survey questions related to phonological awareness. Results showed no significant relationships between employment setting and responses. However, reading specialists reported spending more minutes per week providing phonological awareness instruction to children at risk for reading difficulty than did speech-language pathologists. Of concern was that over half of the responding speech-language pathologists reported no involvement in phonological awareness instruction in the regular curriculum, and over one-quarter reported that they did not provide phonological awareness instruction to children on their caseloads, who may be at risk for reading failure. DEDICATION I am dedicating this work to my family. I want to thank my family for supporting me and all of my decisions. Their unfailing encouragement, support, love, and faith motivated me to get an education and to continue it now and in the future. They have always been there for me and I am very grateful for everything.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".