Interacting inside and outside of the language classroom
Bibliographic record
Abstract
To extend the reach of the second language (L2) classroom, learners may be given opportunities to interact with native speakers through contact assignments or volunteer work organized through their L2 program. An underlying assumption of these practices is that `real-world' and classroom experience offer different but complementary opportunities for oral interaction. The nature of the difference is not well documented, however, which makes it difficult to assess the relative contributions that interaction in the two environments may make to the language learning process. In this study, we compared selected aspects of oral interaction experienced by two advanced adult L2 speakers of English in two contexts: one where they were students in a nine-week communicative ESL class and another where they were volunteer tutors in a three-week summer program for academically at-risk English-speaking children. The findings revealed differences in the types and quantities of activities during which oral interaction occurred, the frequency with which they were completed, and the degree of attention that the participants paid to language during communication. Overall, these differences reflected the different roles the L2 speakers assumed in the two contexts: that of language `learner' in the classroom and of language `user' outside the classroom.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".