Sensor Data for Learning Support: Achievements, Open Questions & Opportunities

نویسندگان

  • Haeseon Yun
  • Monika Domanska
  • Albrecht Fortenbacher
  • Niels Pinkwart
  • Mina Ghomi
چکیده

A recent trend in the field of learning analytics is to use sensor data about learners to support self-regulated learning. Combining personal, sensor based data with log data derived from a learning environment is a very promising approach, but also poses big challenges for the design of learner models and learner interaction methods, for the interpretation techniques of such data, and on applicable learning scenarios with their ethical and privacy demands. This paper provides a brief review of the emerging field of sensory aided learning analytics, and presents first results towards modeling and developing solutions for sensor-based adaptive learning in different learning contexts.

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تاریخ انتشار 2016