Psychometric Properties of a Digital Citizenship Questionnaire
Bibliographic record
Abstract
<p class="apa">The purpose of this study was twofold, i.e. to examine the extent to which students’ self-reported use of digital technology constituted meaningful and interpretable dimensions of the digital citizenship construct, and to test the adequacy of the construct in terms of its reliability, convergent validity, discriminant validity, and measurement equivalence for male and female students. The sample consisted of 391 undergraduates from 15 institutions of higher education in Malaysia. The data were collected using a self-reported 17-item questionnaire measuring university students’ digital citizenship behaviours. The results of the study supported and extended the results of previous work on students’ behaviors when using digital technology. The study found evidence that students’ digital citizenship is a valid and reliable multidimensional construct, and the measurement is gender-invariant. The findings are useful in making evidence-informed decisions in choosing and developing instructional interventions to produce ethical and responsible technology users, and in informing future research in the area.</p>
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".