Writing for the (virtual) other: The presence and impact of intertextual relationships on online L2 exchanges using CMC
Bibliographic record
Abstract
Abstract: In my research I explore the practical implications of socially-based theories of language and writing, especially those of M.M. Bakhtin, within university foreign language classrooms. Specifically, I examine how these theories can inform the design, implementation and analysis of computer-mediated communication (CMC) intercultural exchanges as a support in L2 writing development. I describe a recent online intercultural exchange between Chilean university students enrolled in English Pedagogy and Canadian university students enrolled in Spanish, who were in touch using CMC tools to meet, share their writing and engage in peer review. I used a qualitative approach to analyze the students writing in the blog, identifying instances of intertextuality and the passing back and forth of language across the students? writings. The intercultural CMC exchange offered positive conditions for the sharing of language, which led to contextualized learning of new lexical items and the creation of intertextually richer student compositions in the L2.Resumen: Se exploran las implicaciones de teor?as sociales de lenguaje y escritura, en particular las de Mija?l Bajt?n, en la ense?anza de idiomas extranjeros a nivel universitario. Observo el impacto de las teor?as en el dise?o, implementaci?n y an?lisis de intercambios culturales con uso de la Comunicaci?n Mediada por Ordenador (CMO) para el desarrollo de la escritura en L2. Se describe un intercambio intercultural virtual entre universitarios chilenos de pedagog?a en ingl?s y universitarios canadienses estudiando espa?ol, quienes usaron herramientas de CMO para conocerse, compartir sus trabajos escritos y hacer revisi?n en pares. Los datos analizados incluyen la escritura de los estudiantes en el blog en ingl?s y espa?ol. Us? un enfoque cualitativo para analizar los textos producidos en el blog, identificando instancias de intertextualidad y intercambio de lenguaje en los textos. El intercambio intercultural con CMO ofreci? condiciones positivas para el intercambio de lenguaje, inspirando el aprendizaje contextualizado de nuevos elementos l?xicos y la creaci?n de redacciones intertextuales enriquecidas en la L2.
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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 | 0.005 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".