Speech Recognition Software Contributes to Reading Development for Young Learners of English
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thirty-six English language learners aged 6;8 to 12;6 years received practice with The Reading Tutor, which uses speech recognition to listen to oral reading and provides context-sensitive feedback. A crossover research design controlled effects of classroom instruction. The first subgroup worked with the software for 3.5 months, and following a week's crossover period, the second subgroup worked for a subsequent 3.5 months. Both groups were assessed to obtain comparable gains both in regular classroom with English as an Additional Language (EAL) support and in the classroom condition with EAL support plus the Reading Tutor. Oral reading fluency was assessed by the DIBELS measure. Fluency was also calculated by the program, and grade level of materials mastered was assessed by the software's logs. Both groups made significant gains in oral reading fluency and grade level of materials mastered, according to measures internal to the software. For one period, gains in fluency following experience with the program appeared to have been slightly larger than gains with regular classroom instruction and EAL support only.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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