Knowledge Awareness Map for Computer-Supported Ubiquitous Language-Learning
WMTE '04 Proceedings of the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education (WMTE'04)
Context Awareness and Adaptation in Mobile Learning
WMTE '04 Proceedings of the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education (WMTE'04)
Educational Metadata for Mobile Learning
WMTE '04 Proceedings of the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education (WMTE'04)
Design and development of a mobile learning management system adaptive to learning style of students
WMTE '05 Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education
An Approach for Detecting Learning Styles in Learning Management Systems
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
Context-Aware Computing Applications
WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications
Advanced Adaptivity in Learning Management Systems by Considering Learning Styles
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
An adaptive context-aware mobile learning framework based on the usability perspective
International Journal of Mobile Learning and Organisation
Activities, context and ubiquitous computing
Computer Communications
International Journal of Mobile Learning and Organisation
Embracing calibration in body sensing: using self-tweaking to enhance ownership and performance
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
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The purpose of this paper is to present the data analysis obtained from our interview study, which showed that participants had different individual mobile learning (hereafter, abbreviated as m-learning) preferences. The understanding of these preferences for different m-learning requirements can be used as a foundation for building successful personalised m-learning applications catered to learners' individual m-learning needs. Participants' dynamic m-learning preferences (including location of study, noise/distraction level in a location and time of day) are described. We propose a context-aware personalised m-learning application based on these m-learning preferences. Six scenarios are given to illustrate the m-learning preferences of different learners. The system architecture consists of a learner profile, personalisation mechanism and learning object repository. An initial m-learning preference questionnaire is used to obtain learners' dynamic m-learning preferences. Current context values are retrieved from context-aware technologies. Appropriate learning objects are selected to learners based on their preferences and context values.