The Efficacy of Structural Priming on the Acquisition of Double Object Construction by Chinese EFL Learners
Bibliographic record
Abstract
Structural priming refers to the tendency of speakers to reuse the same structural pattern as one that was previously encountered (Bock, 1986). The effectiveness of structural priming has been an issue of much discussion in the field of second language acquisition over decades. This study aims at investigating the role of structural priming in Chinese English-as-a-foreign-language (EFL) learners’ acquisition of double object (DO) construction. Specifically, it addresses two questions: (i) whether structural priming can facilitate second language acquisition of English DO construction in the short-term and long-term; (ii) whether different priming conditions by manipulating the intervening lags between prime and target have different learning effect. With a pretest-treatment–posttest–delayed posttest research design, 60 intermediate level Chinese EFL learners from three intact English classrooms in a junior college were assigned to three groups: control group, no-lag priming group and long-lag priming group. Results showed that the two treatment groups showed an overall increase in DO production in picture description tasks after the structural priming treatment, whereas the control group remained almost the same in target structure production over the three testing sessions. In addition, the no-lag priming group outperformed the long-lag priming group in the immediate posttest. These findings suggested that structural priming facilitated Chinese EFL learners’ acquisition of DO construction both in the short-term and long-term. Moreover, manipulating the lags between prime and target can only mediate the short-term learning effect. These results are analyzed in light of frequency effect and contextual effect in the frame of usage-based theory of language acquisition.
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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 | 0.000 | 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) | 0.001 | 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".