Jennifer S. Beaudin1, Stephen S. Intille1, Emmanuel Munguia Tapia1, Randy Rockinson1, and Margaret E. Morris2
1 House_n, Massachusetts Institute of Technology
One Cambridge Center, 4FL,
Cambridge, MA 02142 USA
{jbeaudin, intille} (at) mit.edu
2 Digital Health Group, Intel Corporation
20270 NW AmberGlen Court; AG1-102
Beaverton, OR 97006 USA
Margaret.Morris (at) intel.com
We explore the use of ubiquitous sensing in the home for context-sensitive 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.
Beaudin, J.S., S.S. Intille, E. Munguia Tapia, R. Rockinson, and M.E. Morris, Context-sensitive microlearning of foreign language vocabulary on a mobile device, in Proceedings of the European Ambient Intelligence Conference 2007. 2007 (to appear).
This work was supported by Intel Corporation. We thank our participants for the generous contribution of their time and their detailed feedback, and TIAX LLC for collaboration on the PlaceLab. The sensors used were developed with support from National Science Foundation grant #0313065. The PlaceLab stay was funded by Microsoft Research.