How long can naturalistic L2 pronunciation learning continue in adults? A 10-year study
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
We examined the naturalistic pronunciation development of two groups of L2 speakers over 10 years. Initially, 50 beginner ESL students participated in production tasks; despite attrition, the tasks were administered eight more times. Here we report listener judgements of accentedness, comprehensibility and fluency for the remaining six Mandarin and 12 Slavic language speakers at Year 10. Analyses of listener judgments of accentedness, comprehensibility, and fluency of utterances recorded at the 2-month, 1-year, 2-year, 7-year and 10-year points revealed that the Slavic language speakers improved in comprehensibility and fluency at each comparison point, while the Mandarin speakers’ results were variable; there was improvement in comprehensibility from Year 7 to Year 10, but only after worsening at earlier points. The Slavic language group showed improvement in accentedness several times, whereas the Mandarin group showed no improvement in accentedness at any point. The data were examined for individual differences in learning trajectories. Interview responses and a survey of language use were compared to participants’ trajectories. Some speakers showed steady improvement from Year 7 to Year 10, but the majority plateaued or regressed. We also elicited speakers’ views of their progress. The results are interpreted through Complexity Theory and the Willingness to Communicate framework. Suggestions are made for research and teaching interventions.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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