The Canadian Journal of Applied Linguistics: 14, 1 (2011): pp. 194-221 The Influence of the Social Interactional Context on Test Performance: A Sociocultural View
Bibliographic record
Abstract
This study investigated the influence of the social interactional context on test performance from a sociocultural perspective. Two oral language test tasks were used and parallel task versions were developed using two test methods: the individual context and the group context. The tests were administered to 23 ESL students. Both quantitative and qualitative methods were employed to analyze the data. Results of this study, particularly the significantly different discourses generated from the individual context and the group context show that analysis of the influence of the social interactional context on test performance from a sociocultural perspective offers language test developers and researchers useful information about test development and test validation inquiry. Implications of applying sociocultural theory in second language oral performance assessment are discussed.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".