A Video-Conferencing English–Spanish eTandem Exchange
Bibliographic record
Abstract
This study analyzed eTandem video-conferencing exchanges between five pairs of university students of English as a foreign language (EFL) and Spanish as a foreign language (SFL). The exchanges, which involved discussion of seven tasks, took place on a weekly basis. Drawing on an interactionist perspective (Ellis et al., 2001a; Loewen, 2005), the study explored the impact of incidental noticing on subsequent language learning. Data were collected from two sources: transcripts of all the video-conferencing sessions and immediate and delayed post-tests. Drawing on Loewen’s (2005) framework of analysis, the transcripts revealed that students generated a total of 915 focus-on-form episodes (FFEs). As measured by the post-tests, participants recalled over half of the targeted FFE linguistic items. In contrast to previous studies (Loewen, 2005; Shekary & Tahririan, 2006), where successful uptake was a predictor for L2 learning, the present study revealed that the only significant predictor was deferred timing. More generally, the present study supports the claim that eTandem video-conferencing is a useful activity for promoting L2 acquisition.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".