How Can We Help Our K-12 Teachers?: Using a Recommender to Make Personalized Book Suggestions

K-12 teachers, especially the ones who teach reading and literacy, are expected to guide their students to read in order to learn. Teachers can promote good reading habits among K-12 readers by offering books that match their interests. Unfortunately, finding the right book for each individual or group of students is not an easy task due to the huge volume of books available these days that cover a diversity of topics at varied reading levels. To address this problem, we have developed BReT, a book recommender for K-12 teachers. BReT adopts a multi-dimensional strategy to suggest books that simultaneously match the interests, preferences, and reading abilities of K-12 students based on the content, topics, literary elements, and grade levels specified by a teacher. BReT is novel, since it recommends books to K-12 teachers tailored to their individual students or groups of students, either for pleasure reading or fulfilling their current instructional activities. Unlike existing book-searching tools currently being used by teachers, which adopt a "one-size-fits-all" strategy, BReT offers personalized suggestions. Conducted empirical studies using Mechanical Turk have verified the effectiveness of BReT in making book recommendations.