Collaborative writing in mixed classes: What do heritage and second language learners think?
Bibliographic record
Abstract
Abstract This study investigates heritage language (HL) and second language (L2) learners' attitudes and perceptions of their mixed HL–L2 interactions. As part of the activities of a 10‐week course, eight Spanish HL learners and 10 L2 learners worked in mixed dyads to complete a series of collaborative writing tasks designed to leverage their complementary strengths and weaknesses. A beginning‐of‐quarter and an end‐of‐quarter questionnaire were administered. Learners' responses revealed that HL and L2 learners alike had a highly positive experience that changed their initial reluctance toward collaborative writing. Most learners noticed language gains and an improvement in their writing skills. Yet both HL and L2 participants agreed that L2 learners, who were generally perceived as less proficient, benefited more. HL learners also reported affective benefits from their role as linguistic and cultural experts. Although some challenges were noticed, overall, findings support the use of collaborative writing tasks in mixed classes.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".