From Awareness to Action: The Effects of Experiential Learning on Educating Users about Dark Patterns
Jingzhou Ye, Yao Li, Wenting Zou, Xueqiang Wang
Abstract
Dark patterns (DPs) refer to unethical user interface designs that deceive users into making unintended decisions, compromising their privacy, safety, financial security, and more. Prior research has mainly focused on defining and classifying DPs, as well as assessing their impact on users, while legislative and technical efforts to mitigate them remain limited. Consequently, users are still exposed to DP risks, making it urgent to educate them on avoiding these harms. However, there has been little focus on developing educational interventions for DP awareness. This study addresses this gap by introducing DPTrek, an experiential learning (EL) platform that educates users through simulated real-world DP cases. Both qualitative and quantitative evaluations show the effectiveness of DPTrek in helping users identify and manage DPs. The study also offers insights for future DP education and research, highlighting challenges such as user-unfriendly taxonomies and the lack of practical mitigation solutions.
• Security and privacy → Social aspects of security and privacy; • Social and professional topics → Computing education.
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Cited by top-tier papers2
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- Unveiling the Tricks: Automated Detection of Dark Patterns in Mobile ApplicationsJieshan Chen, Jiamou Sun, Sidong Feng, Zhenchang Xing et al.UIST 2023 · 42 citations
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