Putting Struggling Readers on the PHAST Track
Bibliographic record
Abstract
PHAST (for Phonological and Strategy Training) is a research-based remedial reading program that attempts to capitalize upon current research on reading disabilities and their remediation. The focus of the program is on the primary obstacles to word identification learning and independent decoding that most disabled readers face and the steps necessary to help these children achieve independent reading skills. A framework of phonologically based remediation was used as a foundation upon which a set of flexible and effective word identification strategies were scaffolded in an integrated developmental sequence. The program uses a combination of direct instruction and dialogue-based metacognitive training, with the pedagogical emphasis shifting from an initial direct instruction, remedial focus to increasingly metacognitive-strategy-based methods. A continuum of intervention over 70 hours provides both (a) remediation of the basic phonological awareness and letter-sound-learning deficits of disabled readers and (b) specific training of five word identification strategies that offer different approaches to the decoding of unfamiliar words and exposure to different levels of subsyllabic segmentation. Explicit instruction in the application and monitoring of multiple word identification strategies and their application to text-reading activities continues throughout the PHAST Program. PHAST training provides the disabled reader with the opportunity to become a flexible reader who approaches new words in or out of context with multiple strategies and has the ability to evaluate the success of their application. The PHAST Program was developed following the controlled evaluation of its components in laboratory classroom settings and recent positive results from their sequential combination. PHAST represents a new integrated approach to programming in this area using instructional components that have already demonstrated their efficacy with children with severe reading disabilities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".