The audio-recorder as a resource for L2 learning in study abroad
Bibliographic record
Abstract
Research on second language (L2) learning in study abroad (SA) often includes close analyses of audio or video recordings of interactions among speakers in the host country (Diao, 2022; Mitchell, 2023). These recordings are increasingly being collected by SA students themselves using handheld and/or mobile devices. Given that participants are aware and often in control of the recording process, some researchers (e.g., Gordon, 2013; Speer & Hutchby, 2003) have suggested that scholars should attend to how participants orient to the recorder as a resource for doing things (i.e., interactive and relational work) in talk. We take up these researchers’ call by examining participant-collected recordings of peer talk from two SA case studies: American learners of German in Germany and Japanese learners of English in Canada. Analyses reveal that the audio-recorder afforded participants additional opportunities to collaboratively do research, build informal relationships, and practice language while abroad. Our results highlight how integrating recording devices in SA can support those seeking more informal ways to practice the L2 with peers in context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".