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OwlGuard: A Cognitive Science-Backed Intervention to Address Challenges in Data Literacy

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2025-05-22

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Lakhani, Anika Vinod. 2025. OwlGuard: A Cognitive Science-Backed Intervention to Address Challenges in Data Literacy. Bachelors Thesis, Harvard University Engineering and Applied Sciences.

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Abstract

This thesis presents the novel artifact creation of OwlGuard, a browser extension designed to enhance user engagement with and comprehension of privacy policies, as well as a user study testing the effectiveness of OwlGuard. Using a mixed-methods approach with 12 participants aged 20-23, the study employed a within-subjects design to compare interactions with privacy policies both with and without the OwlGuard extension. Key findings include: - OwlGuard likely reduces perceived complexity and increasing comprehensibility of privacy policies for certain websites, particularly those with lengthy or complex policies. - Post-study results showed increased self-perceived data literacy and improved accessibility of privacy policies after using OwlGuard. - Participants spent an average of 42.7 seconds on privacy policies (40.7 seconds specifically among experimental data), significantly longer than the 19 seconds reported in previous literature. - Computer science majors demonstrated significantly longer reading durations (54.1 seconds on average) compared to those of non-CS majors (34.5 seconds on average). - Qualitative feedback indicated that OwlGuard made privacy policies more approachable and understandable, especially for non-CS participants. Participants enjoyed the customization, fun "theme" elements, and adorable owl animation. - The study supports both a user-centric and research-centric design approach by modeling so with the improvement of privacy policy engagement. The study also highlights several exciting areas for future research and refinement of the OwlGuard browser extension.

This thesis is motivated by a deep desire to improve status-quo data literacy in order to foster a more equitable society both online and offline.

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data, privacy, user study, Computer science

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