Demo Data from VLDB 2026 / reviewers in the wild / expert
Kyra Derrick
dblp:374/9498
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0005-9082-1199ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Usable security · 77% Privacy and data protection · 23% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computing education · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computing education › k-12 education
k-12 computing education |
0.8 | 1 | 2024 | Teaching Middle Schoolers about the Privacy Threats of Tracking and Pervasive Personalization: A Classroom Intervention Using Design-Based Research · CHI 2024 |
Usable security › usable privacy
privacy literacy |
0.8 | 1 | 2024 | Teaching Middle Schoolers about the Privacy Threats of Tracking and Pervasive Personalization: A Classroom Intervention Using Design-Based Research · CHI 2024 |
Privacy and data protection › privacy of vulnerable populations
adolescent online privacy |
0.2 | 1 | 2024 | Teaching Middle Schoolers about the Privacy Threats of Tracking and Pervasive Personalization: A Classroom Intervention Using Design-Based Research · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
design-based research · 1.5classroom intervention · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Teaching Middle Schoolers about the Privacy Threats of Tracking and Pervasive Personalization: A Classroom Intervention Using Design-Based ResearchabstractWith the pervasive and evolving use of tracking and AI to make inferences about online platform users, it has become imperative for adolescents—a key demographic using such platforms—to develop a deep understanding of these practices to protect their privacy. Traditionally, K-12 cybersecurity education has largely been confined to extracurricular activities, limiting underrepresented students’ access. To resolve this shortcoming, we partnered with a rural-identifying middle school to deliver AI-related privacy education in classrooms. Using Design-Based Research methodology, we identified students’ AI-related privacy learning needs and developed six education modules. This paper focuses on the design, classroom implementation, and evaluation of module #2, covering the privacy threats of Tracking and Pervasive Personalization (TaPP). Student assessment outcomes show they developed transferable foundational knowledge of the privacy implications of tracking and personalization after participating in the TaPP module. Our findings demonstrate the benefits of integrating AI-related privacy education into existing K-12 curricula. Sushmita Khan, Mehtab Iqbal, Oluwafemi Osho, Khushbu Singh, Kyra Derrick, Philip Nelson, Lingyuan Li, Emily Sidnam-Mauch, Nicole Bannister, Kelly Caine, Bart P. Knijnenburg |
CHI | 5 |