Eliciting Production of L2 Target Structures through Priming Activities
Bibliographic record
Abstract
Abstract: This study focuses on the pedagogical applications of structural priming research in an English for academic purposes (EAP) context, investigating whether priming activities are an effective tool for eliciting production of target grammatical structures. University students across four EAP classes carried out a total of 6 information-exchange activities over a 13-week semester. Some students received information-exchange activities that provided models of the target structures (e.g., primes), while other students received activities without any models. Analysis of the students’ novel utterances generated from sentence fragments (e.g., prompts) indicated that students who carried out the priming activities produced more target structures following prime sentences than they did in the absence of primes. In addition, students who did priming activities produced significantly more relative clauses and adverbial clauses overall than did students who carried out the activities without models, but there was no difference in their production of passives. Implications and suggestions for instructors interested in incorporating priming activities in L2 classrooms are discussed.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".