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

Abstract—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. Keywords-recommendation; books; K-12; teachers I

Pitako -- Recommending Game Design Elements in Cicero

Recommender Systems are widely and successfully applied in e-commerce. Could they be used for design? In this paper, we introduce Pitako1, a tool that applies the Recommender System concept to assist humans in creative tasks. More specifically, Pitako provides suggestions by taking games designed by humans as inputs, and recommends mechanics and dynamics as outputs. Pitako is implemented as a new system within the mixed-initiative AI-based Game Design Assistant, Cicero. This paper discusses the motivation behind the implementation of Pitako as well as its technical details and presents usage examples. We believe that Pitako can influence the use of recommender systems to help humans in their daily tasks.Comment: Paper accepted in the IEEE Conference on Games 2019 (COG 2019

Enhancing Classroom Instruction with Online News

Purpose Investigate how school teachers look for informational texts for their classrooms. Access to current, varied, and authentic informational texts improves learning outcomes for K-12 students, but many teachers lack resources to expand and update readings. The Web offers freely-available resources, but finding suitable ones is time-consuming. This research lays the groundwork for building tools to ease that burden. Methodology This paper reports qualitative findings from a study in two stages: (1) a set of semi-structured interviews, based on the Critical Incident Technique, eliciting teachers’ information-seeking practices and challenges; and (2) observations of teachers using a prototype teaching-oriented news search tool under a think-aloud protocol. Findings Teachers articulated different objectives and ways of using readings in their classrooms; goals and self-reported practices varied by experience level. Teachers struggled to formulate queries that are likely to return readings on specific course topics, instead searching directly for abstract topics. Experience differences did not translate into observable differences in search skill or success in the lab study. Originality and Value There is limited work on teachers’ information-seeking practices, particularly on how teachers look for texts for classroom use. This paper describes how teachers look for information in this context, setting the stage for future development and research on how to support this use case. Understanding and supporting teachers looking for information is a rich area for future research, due to the complexity of the information need and the fact that teachers are not looking for information for themselves