Design, Development, and Evaluation of a Cybersecurity, Privacy, and Digital Literacy Game for Tweens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tweens are avid users of digital media, which exposes them to various online threats. Teachers are primarily expected to teach children safe online behaviours, despite not necessarily having the required training or classroom tools to support this education. Using the theory of procedural rhetoric and established game design principles, we designed a classroom-based cybersecurity, privacy, and digital literacy game for tweens that has since been deployed to over 300 Canadian elementary schools. The game, A Day in the Life of the JOs , teaches children about 25 cybersecurity, privacy, and digital literacy topics and allows them to practice what they have learned in a simulated environment. We employed a user-centered design process to create the game, iteratively testing its design and effectiveness with children and teachers through five user studies (with a total of 63 child participants and 21 teachers). Our summative evaluation with children showed that the game improved their cybersecurity, privacy, and digital literacy knowledge and behavioural intent and was positively received by them. Our summative evaluation with teachers also showed positive results. Teachers liked that the game represented the authentic experiences of children on digital media and that it aligned with their curriculum requirements; they were interested in using it in their classrooms. In this article, we discuss our process and experience of designing a production quality game for children and provide evidence of its effectiveness with both children and teachers.
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.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it