Recommendation in Personalised Peer-Learning Environments (1712.03077v2)

Abstract: Recommendation in Personalised Peer Learning Environments (RiPPLE) is an adaptive, crowdsourced, web-based, student-facing, open-source platform that employs exemplary techniques from the fields of machine learning, crowdsourcing, learning analytics and recommender systems to provide personalised content and learning support at scale. RiPPLE presents students with a repository of tagged multiple-choice questions and provides instant feedback in response to student answers. The repository of the questions is created in partnership with the students through the use of crowdsourcing. RiPPLE uses students responses to the questions to approximate their knowledge states. Based on their knowledge state and learning needs, each student is recommended a set of personalised questions. For students that are interested in providing learning support, seeking learning support or finding study partners, RiPPLE recommends peer learning sessions based on their availability, knowledge state and preferences. This paper describes the RiPPLE interface and an implementation of that interface that has been built at the University of Queensland. The RiPPLE platform and a reference implementation are released as an open-source package under the Apache 2.0 license via GitHub.