Input-based tasks for beginner-level learners: An approximate replication and extension of Erlam & Ellis (2018)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it