Context-sensitive microlearning of foreign language vocabulary on a mobile device

  • Authors:

  • Jennifer S. Beaudin;Stephen S. Intille;Emmanuel Munguia Tapia;Randy Rockinson;Margaret E. Morris

  • Affiliations:

  • Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA;Digital Health Group, Intel Corporation, Beaverton, OR

  • Venue:
  • AmI'07 Proceedings of the 2007 European conference on Ambient intelligence
  • Year:
  • 2007

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Abstract

We explore the use of ubiquitous sensing in the home for contextsensitive microlearning. To assess how users would respond to frequent and brief learning interactions tied to context, a sensor-triggered mobile phone application was developed, with foreign language vocabulary as the learning domain. A married couple used the system in a home environment, during the course of everyday activities, for a four-week study period. Built-in and stick-on multi-modal sensors detected the participants' interactions with hundreds of objects, furniture, and appliances. Sensor activations triggered the audio presentation of English and Spanish phrases associated with object use. Phrases were presented on average 57 times an hour; this intense interaction was found to be acceptable even after extended use. Based on interview feedback, we consider design attributes that may have reduced the interruption burden and helped sustain user interest, and which may be applicable to other context-sensitive, always-on systems.