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EduYelp: A Mobile Phone Application to Help Users Searching and Rating Educational Apps and ToolsWeilu Tian, M.A. in Communication and Education
This project presents a design of a mobile phone application “EduYelp” aimed to effectively aid users find the best educational apps they need. The purpose of the design is to establish a trustworthy rating system and an online learning platform for users to exchange opinions, so that users could better navigate and manage the educational online resources. The design process was guided by the studies on mobile searching behavior and online ranking credibility. Marchionini(1992) stated that “humans will seek the path of least cognitive resistance” (p. 156), and Griffiths (1996), who found that “increasing the cognitive burden placed on the user can affect successful retrieval of information. Where an application required fewer actions from the user, greater success was achieved as there was less possibility for a user to make an error” (p. 203). In addition, the study by Hengshu Zhu(2014) on ranking fraud has found that some App developers resort to some fraudulent means to deliberately boost their Apps and eventually manipulate the chart rankings on an App store. Based on the same problem in electronic commerce system, Wang et al. (2008) proposed a system to improve Amazon’s review system by adding two factors: review credibility and time decay. Mui et al. (2001) proposed a Bayesian probabilistic technique to weight a rating based on the rater’s personality. The results of these studies are significant to identify design issues in this project and guide the development of design solutions. The iterative use of the preference filters for app searching, coupled with the technique to weight the rating based on the user’s credibility, the App was aimed to provides users with an effective credible assessment standard for apps.Also, by creating an online community for interactive communication and peer review for the App users, the project intended to provide the chance for collaborative learning of online users.