A readability level prediction tool for K-12 books

The readability level of a book is a useful measure for children and teenagers (teachers, parents, and librarians, respectively) to identify reading materials suitable for themselves (their K-12 readers, respectively). Unfortunately, majority of published books are assigned a readability level range, such as K-3, instead of a single readability level for their intended readers, by professionals, which is not useful to the end-users who look for books at a particular grade level. This leads to the development of readability formulas/analysis tools. These formulas/tools, however, require at least an excerpt of a book to estimate its readability level, which is a severe constraint due to copyright laws that often prohibit book content from being made publicly accessible. To alleviate the text constraint imposed on readability analysis on books, we have developed TRoLL, which relies heavily on metadata of books that is publicly and readily accessible from reputable book-affiliated online sources, besides using snippets of books, if they are available, to predict the readability level of books. Based on a multi-dimensional regression analysis, TRoLL determines the grade level of any book instantly, even without a sample text in the book, which is its uniqueness. TRoLL handles the entire spectrum of readability levels, i.e., the well-known K-12 grade-level range. Unlike its counterparts, TRoLL explicitly considers the topical suitability of (the content of) a book in determining its readability level, which is one of the unique features of TRoLL as a readability-level prediction tool. Furthermore, TRoLL is a significant contribution to the educational community, since its computed book readability levels can (i) enrich K-12 readers’ book selections and thus can enhance their reading for learning experience, and (ii) aid parents, teachers, and librarians in locating reading materials suitable for their K-12 readers, which can be a time-consuming and frustrating task that does not always yield a quality outcome. Empirical studies conducted using a large set of K-12 books have verified the prediction accuracy of TRoLL and demonstrated its superiority over existing well-known readability formulas/analysis tools.