Critical Appraisal of Information on the Web in Practice: Undergraduate Students’ Knowledge, Reported Use, and Behaviour / Évaluation critique de l’information sur la toile : une vision pratique : les connaissances des étudiants de premier cycle, leur uti
Bibliographic record
Abstract
Undergraduates use a wide range of information resources for academic and nonacademic purposes, including web sites that range from credible, peer reviewed, online journal sites, to biased and inaccurate promotional web sites. Students are taught basic critical appraisal skills, but do they apply these skills to make decisions about information in different web sites? In an experimental setting, undergraduate students examined pairs of web sites containing conflicting information based on different aspects of critical appraisal, namely credibility of the author of the information, purpose of the web site, and last update of the site, and answered multiple choice questions about the conflicting information. Results indicated that students failed to use critical appraisal criteria, and that while knowledge of and self-reported use of these criteria were related to each other, they were not related to behaviour. This research demonstrates the need for alternative strategies for critical appraisal instruction and assessment. Les étudiants de premier cycle consultent une vaste gamme de sources d’information à des fins universitaires et non universitaires, y compris des sites Web allant de revues en ligne crédibles et évaluées par des pairs à des sites Web promotionnels partials et inexacts. On enseigne aux étudiants des méthodes de base d’évaluation critique, mais mettent-ils ces méthodes en pratique pour prendre des décisions relativement à l’information tirée de différents sites Web? Dans un cadre expérimental, les étudiants de premier cycle ont étudié des paires de sites Web contenant des informations contradictoires en se fondant sur différents aspects de l’évaluation critique, notamment la crédibilité de l’auteur de l’information, l’intention du site Web et la dernière mise à jour du site, et ont répondu à des questions à choix multiples concernant les informations contradictoires. Les résultats indiquent que les étudiants n’ont pas utilisé les critères d’évaluation critique et que si les connaissances et l’utilisation de ces connaissances déclarée par les étudiants étaient reliées, cette relation ne correspondait toutefois pas au comportement observé. Cette recherche démontre la nécessité de stratégies de rechange en matière d’enseignement de l’évaluation critique et son évaluation.
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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 | 0.048 | 0.167 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".