The Cross-linguistic Development of Address Form Use in Telecollaborative Language Learning: Two Case Studies
Bibliographic record
Abstract
In this paper we explore the influences of the telecollaborative learning environment on the development of L2 pragmatic competence in foreign language learning from a sociocultural perspective (Lantolf, 2000). Typically, telecollaboration involves the application of global computer networks in foreign language study (e.g., Warschauer, 1996) for the purposes of linguistic development and intercultural learning. In particular, we focus on the ‘microgenesis’ or development of the T/V distinction in pronouns of address as a test case representative of broader L2 pragmatic concerns. We present two detailed case studies of this phenomenon: one for French (tu vs. vous) and one for German (du vs. Sie). The rationale for this type of analysis emerges from Vygotsky's developmental approach to cognition (1978) where it is emphasized that development can only be understood by specifying its history. We argue that, in contrast to the traditional language classroom, the telecollaborative language class provides the learner with increased opportunities for social interaction with native-speaking peers and, thus, with a wider range of discourse options (Kramsch, 1985a) for the disambiguation of the numerous sociopragmatic meanings of the pronouns of address in French and German.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".