Towards Defining a Valid Assessment Criterion of Pronunciation Proficiency in Non-Native English-Speaking Graduate Students
Bibliographic record
Abstract
Abstract: Intelligibility has been widely regarded as an appropriate goal for second language pronunciation teaching. Yet there is no universally accepted definition of intelligibility, nor any field-wide consensus on the best way to measure it. Further, there is little empirical evidence to suggest which pronunciation features are crucial for intelligibility to guide teachers in their instructional choices. This mixed-methods study examines whether intelligibility is an appropriate criterion for assessing pronunciation proficiency in the academic domain. Speech samples of eight non-native English speaking graduate students were elicited using the Test of Spoken English, a standardized test often used to screen international teaching assistants (ITAs). Results of a fine-grained analysis of the speech samples combined with intelligibility ratings of 18 undergraduate science students suggest that intelligibility, though an adequate assessment criterion, is a necessary but not a sufficient condition for international graduate students to instruct undergraduate courses as teaching assistants.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".