Enriching Education Through Data Mining

Education is acknowledged to be the primary vehicle for improving the economic well-being of people [1,6]. Textbooks have a direct bearing on the quality of education imparted to the students as they are the primary conduits for delivering content knowledge [9]. They are also indispensable for fostering teacher learning and constitute a key component of the ongoing professional development of the teachers [5,8]. Many textbooks, particularly from emerging countries, lack clear and adequate coverage of important concepts [7]. In this talk, we present our early explorations into developing a data mining based approach for enhancing the quality of textbooks. We discuss techniques for algorithmically augmenting different sections of a book with links to selective content mined from the Web. For finding authoritative articles, we first identify the set of key concept phrases contained in a section. Using these phrases, we find web (Wikipedia) articles that represent the central concepts presented in the section and augment the section with links to them [4]. We also describe a framework for finding images that are most relevant to a section of the textbook, while respectingglobal relevancy to the entire chapter to which the section belongs. We pose this problem of matching images to sections in a textbook chapter as an optimization problem and present an efficient algorithm for solving it [2].