The Effects of the Read 180 Program on Oral Reading Fluency, Linguistic Comprehension, and Reading Comprehension with Secondary Special Education Students
Bibliographic record
Abstract
There is great concern about secondary special education students reading achievement in decoding, listening comprehension, and reading comprehension. The READ 180 Program is an evidence and scientific based reading program that includes direct instruction, computer aided instruction, and reading materials that are high interest and implement the common core. The purpose of this study was to see the differences in oral reading fluency, linguistic comprehension, and reading comprehension in a pretest posttest model over a fourteen-week testing period. Ten ninth grade secondary students who were reading below the 25th percentile were instructed with the READ 180 Program with fidelity (90 minutes a day, four days a week, for fourteen weeks). The students were pretested and posttested with the Listening Comprehension Adolescent and the Gate MacGinitie Reading Comprehension Test. The students oral reading fluency was progressed monitored weekly with one minuet timed eighth grade reading probes from easyCBM that tracked total words read correctly, and the total number of miscues (words mispronounced, or omitted). The results showed that the students increased in the number or words read correctly and had a statistically significant decrease in miscues. In addition, on the Listening Comprehension pretest and posttest, the students realized a statistically significant increase on their posttest scores. The reading comprehension pretest and posttest scores did not see any change over the fourteen-week testing period. The results of the study conclude that the READ 180 Program had an effect on the student's oral reading fluency and listening comprehension posttest scores.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".