Wiki as a Tool in Teaching Translation: An Online Peer-Assessment Model of Evaluation
Bibliographic record
Abstract
The complexities of the real professional world the trainee translators are to enter requires the utilization of the large scale instruction, flexibility and highly facilitated and interactive learning that online learning and its associated facilities put at our disposal within an instructional design. This paper is an attempt to investigate the effect of incorporating wiki (an asynchronous text-based online collaborative tool) in a web-based social constructivist specialized translator training workshop on trainee translators’ performance in comparison with conventional contact classrooms applying the same instructional framework. An experimental research methodology was utilized to answer the research question and test the hypothesis. The results revealed that using such a collaborative tool as wiki in the translator training workshop had improved the performance of future translators as a consequence of more developed translation and translator competences when compared with the conventional contact classroom.
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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 | 0.074 | 0.178 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".