QUESTIONNAIRES IN SECOND LANGUAGE RESEARCH: CONSTRUCTION, ADMINISTRATION, AND PROCESSING
Bibliographic record
Abstract
QUESTIONNAIRES IN SECOND LANGUAGE RESEARCH: CONSTRUCTION, ADMINISTRATION, AND PROCESSING. Zoltán Dörnyei. Mahwah, NJ: Erlbaum, 2003. Pp. viii + 156. $37.50 cloth, $22.50 paper. In the introduction to this volume, Dörnyei suggests that, although questionnaires are frequently employed by second language researchers, “there does not seem to be sufficient awareness in the profession about the theory of questionnaire design and processing” (p. 1). Looking to the various branches of research in the social sciences, such as psychometrics, social psychology, and sociology, Dörnyei notes that many of the questionnaires in second language research fail to meet the standards for reliability and validity because the researchers are apparently unfamiliar with the principles of questionnaire construction, administration, and processing. This book is intended to be a practical, easily understood guide for researchers to use when working with self-administered pencil-and-paper questionnaires. It achieves this aim.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.050 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.011 |
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".