Exploring the Mental Model of Web Page Scrap: Design Suggestion of an AI-Powered In-Browser Scrap Tool and Its Usability Evaluation

초록

People use diverse read-it-later tools to save webpages for future uses; however, difficulties in scrap retrieval remain. Our study aims to understand users' mental models of read-it-later tools and suggests a new tool, Read-It-Now, for web scraping. We conducted interviews to identify web scraping habits and developed four main design recommendations for read-it-later tools: tool hierarchy, contextual aids, proactive triggers, and multiple navigation strategies. With a focus on the proactive trigger that facilitates scrap retrieval, Read-It-Now is designed to recommend relevant web scraps based on a comparison of the title of the current browser tab. We tested the design prototype against traditional bookmarks and found that users preferred Read-It-Now because of its simplicity and effectiveness; however, explanations for scrap recommendations could be improved.

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