Using Repeated- Reading and Listening –While- Reading via Text-To- Speech APPs. in Developing Fluency and Comprehension
Why this work is in the frame
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Bibliographic record
Abstract
One of the challenges in teaching a foreign language is: finding appropriate ways to enable students to develop their reading fluency and comprehension. Repeated reading and listening-while-reading are two significant strategies that enhance students’ fluency and comprehension. This study aimed to develop fluency and comprehension of EFL college students. During the treatment, the teacher trained the students to use some free Text to Speech apps that support oral repeated reading RR and listening while reading LWR activities. Pre-post tests were used to assess students’ reading fluency and comprehension. Data obtained from the tests were analyzed statistically through SPSS software. Results indicated development in students’ reading fluency and comprehension. Conclusions suggested the use of RR and LWR through Text to speech apps to assist the reading skills of higher education students. It is recommended that TTS Apps are promising tools that can be integrated into reading instruction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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