PERMARUN- A Persuasive Game to Improve User Awareness and Self-Efficacy Towards Secure Smartphone Behaviour
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
Android smartphones have undergone various changes and, uniformity in design (both hardware and software) has become common in most phones. Yet, security and privacy issues persist and grow along with the evolution of smartphones. Recent research shows that user awareness is still low, and they do not follow secure behaviour while using smartphones. Although a handful of works exist for improving user awareness and self-efficacy, none of them educate the users about Android Permissions in a contextual manner. In this paper, we discuss our persuasive game - "PermaRun", which teaches and motivates users to follow secure smartphone behaviour, increases user awareness and self-efficacy about android permissions. We conducted a Heuristic Evaluation for Playability (HEP) and Persuasiveness Evaluation (PE). The result shows that players had a positive experience playing the game, and they found the game playable and persuasive.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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