THE CONSTRUCT VALIDITY OF GRAMMATICALITY JUDGMENT TESTS AS MEASURES OF IMPLICIT AND EXPLICIT KNOWLEDGE
Bibliographic record
Abstract
Grammaticality judgment tests (GJTs) have been, and continue to be, frequently used in the field of SLA as a measure of learners’ linguistic ability in the second language (L2). However, only a few studies have examined their construct validity as measures of implicit and explicit knowledge (Bowles, 2011; R. Ellis, 2005), and even fewer have explored in detail how features of these tests, such as time pressure and task stimulus, affect their construct validity (Loewen, 2009). The purpose of this paper is to examine the effect that time pressure and task stimulus have on the type of knowledge representations on which L2 learners draw when performing GJTs. The results show that the grammatical and ungrammatical sections of a timed and an untimed GJT loaded differently in both exploratory and confirmatory factor analyses. This finding can be interpreted as indicating that grammatical and ungrammatical sentences constitute measures of implicit and explicit knowledge, respectively. Additionally, the results show that time pressure and task stimulus have significant effects on learners’ performance on GJTs.
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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 | 0.021 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".