Annotation of Knowledge Amount and Learning Level to Web Pages explaining Academic Concepts

抄録

In last few years, the Internet and Web contents have become remarkable tools for studying. However, most search engines that can find Web contents applicable for studying are not beginner friendly. Learners must manually compare several pages on the search engine to find beginner friendly Web contents. Visual intelligibility in Web page layout and beginner friendly Web page texts are the requirements of Web contents for beginners. In this paper, we develop a dataset of Web pages explaining academic concepts, to which we manually annotate their knowledge amount and learning level. This paper especially focuses on math and science academic fields such as statistics, calculus, linear algebra, mechanics, electromagnetics, chemistry, programming, and IT. In those academic fields, we collect major Web sites explaining academic concepts and manually annotate their knowledge amount and learning level to Web pages of those sites. Finally, we analyze the knowledge amount and learning level of each of those collected major Web sites.