Evaluating the Impact of a Game-Based Hackathon on Cybersecurity and AI Confidence: A Quantitative Study With Exploratory Gender Analysis

Publication Date

1-1-2026

Document Type

Conference Proceeding

Publication Title

Conference Proceedings IEEE SOUTHEASTCON

DOI

10.1109/SoutheastCon63549.2026.11476343

Abstract

Game-based learning interventions such as hackathons are increasingly used to address gaps in cybersecurity and artificial intelligence (AI) literacy; however, empirical evaluations that quantify their impact using rigorous statistical methods remain limited. This paper presents a quantitative evaluation of a game-based cybersecurity and AI hackathon, examining changes in participants' self-reported confidence across three constructs: cybersecurity knowledge, AI conceptual understanding, and application of cybersecurity and AI concepts. Anonymous pre- and post-event survey data were analyzed using independent-samples t-tests and effect size measures (Cohen's d and Hedges' g). Results indicate statistically significant and practically meaningful gains in cybersecurity knowledge confidence and applied confidence, with moderate and small-tomoderate effect sizes, respectively. In contrast, confidence in AI conceptual understanding did not exhibit statistically significant change and showed negligible effects. Exploratory gender-based analyses revealed consistent directional patterns across groups, with stronger gains observed for cybersecurity-related constructs than for AI concepts. These findings suggest that short-term, experiential hackathons are particularly effective for concrete cybersecurity learning outcomes, while AI conceptual confidence may require longer or more explicitly scaffolded instructional approaches.

Funding Sponsor

WITH Foundation

Keywords

AI literacy, Cybersecurity education, engineering education, experiential learning, game-based learning, hackathons

Department

Computer Science; Mathematics and Statistics

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