Questionnaires to Inform a Usability Test Conducted on a CALL Dictionary Prototype
Bibliographic record
Abstract
Questionnaires are often considered a suitable instrument to gather data on language learners’ experiences. To test the usability of an online dictionary prototype, a series of questionnaires were distributed to a class of language learners before and after they completed a language task at the computer using the dictionary prototype. Measures of task effectiveness and efficiency were obtained and correlated with the questionnaires’ results. This study shows how the questionnaire results informed the overall measure of usability and, in particular, addressed user satisfaction, a more subjective yet a central component of this measure. Pre-questionnaires prepared learners for the task, whereas post-questionnaires fostered a reflection about the task process and its outcome. Hence, it is argued that combining observation and questionnaire techniques in that context was effective in providing a fuller insight into the learner-task-tool interaction at the computer. In this CALL research and development context, questionnaires served a double function as an evaluative and a pedagogical instrument.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".