ARTFul: adaptive review technology for flipped learning

  • Authors:
  • Daniel Szafir;Bilge Mutlu

  • Affiliations:
  • University of Wisconsin, Madison, Madison, Wisconsin, USA;University of Wisconsin, Madison, Madison, Wisconsin, USA

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2013

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Abstract

Internet technology is revolutionizing education. Teachers are developing massive open online courses (MOOCs) and using innovative practices such as flipped learning in which students watch lectures at home and engage in hands-on, problem solving activities in class. This work seeks to explore the design space afforded by these novel educational paradigms and to develop technology for improving student learning. Our design, based on the technique of adaptive content review, monitors student attention during educational presentations and determines which lecture topic students might benefit the most from reviewing. An evaluation of our technology within the context of an online art history lesson demonstrated that adaptively reviewing lesson content improved student recall abilities 29% over a baseline system and was able to match recall gains achieved by a full lesson review in less time. Our findings offer guidelines for a novel design space in dynamic educational technology that might support both teachers and online tutoring systems.