Role of Iranian EFL Teachers about Using Pronunciation Power Software in the Instruction of English Pronunciation
Why this work is in the frame
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Bibliographic record
Abstract
Many studies are related to the use of computer technology in learning and teaching but less work has been done to understand how computer technology users feel about them and how this technology helps in developing teachers’ teaching methods. Pronunciation Power software is one of the computer technologies for teaching English pronunciation. This study examined the role of Iranian teachers in utilizing Pronunciation Power software in pronunciation instruction. The researchers used qualitative method consisted of semi-structured interview questions with a volunteer sample of four teachers from an open university in Lahijan, Iran. The researchers answered the research question pertinent to the role of Iranian teachers about utilizing this software in the instruction of pronunciation. Based on the obtained findings, pronunciation power software changed the Iranian teachers' roles from a dispenser of information to a facilitator of information. This change of role gave them more autonomy and greater opportunities in teaching pronunciation.
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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 | 0.008 |
| 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 | 0.001 |
| 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