Tapping into the Interpreting Process: Using Participant Reports to Inform the Interpreting Process in Educational Settings
Bibliographic record
Abstract
This article presents the results of a Canadian study that examined the correlation of verbal reporting processes and the quality of interpretation. Two types of verbal reports, Think Aloud Protocols (TAPs) and Stimulated Recalls (SRs), were collected and analyzed to explore how TAPS and SRs might reflect the quality of interpreting provided in educational settings and therefore be potential tools for improving interpreting education strategies. Twelve interpreters working in educational contexts were recruited to participate in a multi-stage research process. Each interpreter was asked to perform a Think Aloud while viewing a sample of classroom discourse in preparation for interpreting it. Each interpreter then provided an interpretation, followed by a post-interpreting Stimulated Recall review of the interpretation. The standardized samples chosen were based on videotaped authentic classroom instruction and represented classes at the elementary, middle school and high school levels. A Deaf child was described for each level of interpreting so that the interpreters could target their interpretation. The results showed that those interpreters who demonstrated higher order cognitive thinking skills and attended to teacher intent and student language preferences provided more effective interpreting than the interpreters who focused primarily on linguistic choices and interpreting decisions. The findings have implications for interpreters, interpreter educators and mentors, and teachers working with interpreters and Deaf students in mediated learning environments. By exploring the ways in which attention to discourse features and teacher-student needs could be heightened, interpreters could enhance the quality of interpretation provided to Deaf learners. Finally, questions for future research and implications for collaboration across countries are discussed.
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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 | 0.025 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".