Middle School Girls’ Attitudes and Engagement in Generative AI Cybersecurity Summer Camp
Bibliographic Data
| ID | 22042308 |
|---|---|
| Authors | Jiabao Wen (0009-0002-7631-7701, Southern Methodist University, corresponding author), Marc T Sager (0000-0003-0927-4115, Southern Methodist University), Saki Milton (0009-0000-0653-4167, Southern Methodist University), Tiffani Martin (Wiotech (Sweden)), Rebekah Skeete (Girls Incorporated), Candace Walkington (0000-0002-2338-8760, Southern Methodist University) |
| Year | 2026 |
| Volume | 16 |
| Issue | 7 |
| Pages | 1099 |
| Publication date | 2026-07-09 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci16071099 |
| OpenAlex | W7167791555 |
| Language | EN |
| References cited | 46 |
Informal science, technology, engineering, and mathematics (STEM) learning settings can provide early and accessible opportunities for students who have been historically underrepresented in computing to engage with cybersecurity concepts and emerging technologies. This one-group pretest-posttest mixed-methods study examined a week-long, GenAI-integrated informal cybersecurity summer camp for 33 underrepresented and underserved racial and ethnic minority (UUREM) middle school girls. The study investigated pre-post patterns in perceived cybersecurity knowledge, domain-specific self-efficacy, interest, utility value, career aspirations, and selected AI-literacy practices. Quantitative findings showed the strongest support for increases in perceived cybersecurity knowledge and cyber threat identification self-efficacy, both of which remained significant after Holm adjustment for multiple comparisons. Networking and web management self-efficacy showed preliminary unadjusted increases, whereas overall cybersecurity interest, enjoyment and intent to pursue, utility value, career aspirations, and the remaining self-efficacy domains did not show statistically significant differences. Qualitative observations documented activity-specific engagement, collaborative discussion of cybersecurity ideas, and mentor-mediated GenAI practices such as prompt development, output comparison, and script revision. These findings suggest that informal GenAI-integrated cybersecurity programs may support selected aspects of perceived learning and cybersecurity self-efficacy, while highlighting the need for more rigorous designs, validated AI-literacy measures, and longer-term follow-up
African american · Ethnic group · Qualitative analysis · Qualitative property · Qualitative research · Gender and Technology in Education · Information and Cyber Security · Teaching and Learning Programming
Fear Appeals and Information Security Behaviors
Academic self-efficacy
Interaction Analysis
Do multiple outcome measures require p-value adjustment?
Tools for Scaffolding Students in a Complex Learning Environment
Generative AI in Education and Research
Motivational Beliefs, Values, and Goals
Intrinsic and extrinsic motivation from a self-determination theory perspective
The Four-Phase Model of Interest Development
The Organization of Informal Learning
Understanding Racially Minoritized Girls’ Perceptions of Their STEM Identities, Abilities, and Sense of Belonging in a Summer Camp
The paradox of self-efficacy and technological dependence
Integrating large language models into project-based learning based on self-determination theory
The effect of an intervention personalizing mathematics to students’ career and popular culture interests on mathematics interest and learning
Beyond efficiency
From recorded to AI ‐generated instructional videos
A Systematic Literature Review on Cyber Security Education for Children
Self-efficacy
An Asynchronous Online Professional Development for Enhancing Elementary Cybersecurity and Cryptology Education in Informal Learning Environments
Learning Environment, Motivation and Interest
Coefficient alpha and the internal structure of tests
Using thematic analysis in psychology
Which is more predictive
Grounded Theory and Sensitizing Concepts
Demonstrating Rigor Using Thematic Analysis
| Citation velocity | historical |
|---|---|
| Highly cited | No |