Using shadowing with mobile technology to improve L2 pronunciation
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
Shadowing has been demonstrated to improve various aspects of second language learners’ pronunciation but few studies have investigated whether these changes impact untrained listeners’ perceptions. In the present study, sixteen participants used iPods to practice shadowing short dialogues for eight weeks. The participants practiced at least four times per week for a minimum of 10 minutes each time, and recorded themselves while shadowing. Two tasks (a shadowing task and an extemporaneous speaking task) were administered as pre-, mid-, and post-tests, and were rated by 22 speakers of English. The shadowing task was rated for learners’ ability to imitate a speech model and the extemporaneous speaking task was rated for comprehensibility, accentedness, and fluency. Interview data were also collected during the study to gauge participants’ opinions of the activities. Results indicated that the participants improved significantly on all speaking measures apart from accentedness and were largely positive about the activities.
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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 | 0.001 | 0.000 |
| 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) | 0.001 | 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