Input-based tasks for beginner-level learners: An approximate replication and extension of Erlam & Ellis (2018)
Bibliographic record
Abstract
Erlam & Ellis (2018) published, in Canadian Modern Language Review, an experimental study that investigated the effect of input-based tasks on the acquisition of vocabulary and markers of plurality by adolescent near-beginner learners of L2 (second language) French. The present paper reports an approximate replication of the original study with the aim of confirming or disconfirming the results.1 The research questions of both studies addressed the receptive acquisition of new vocabulary and the receptive and productive acquisition of markers of plurality resulting from instruction using input-based tasks. Both studies investigated near-beginner adolescent learners of French. The teacher, the students’ usual classroom teacher, was the same in both studies. In the replication study, a new, larger group of students were investigated, the length of the instruction was increased, involving the development of additional tasks, and productive as well as the receptive knowledge of the vocabulary items was assessed. The results of the replication study confirm and extend those of the original study. The teachers’ views about the role of input-based tasks with near-beginner learners remained constant in the two studies. The paper concludes with a discussion of the contribution that approximate replications can make to instructed second language acquisition research.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reproducibility · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.016 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".