The DOI matches its Crossref record.
Context awareness and adaptation in mobile learning
Abstract
This study investigates the importance of context-awareness and adaptation in mobile learning. Context-aware mobile learning that senses mobile environment and reacts to changing context during learning process has four interaction modes with three mobile entities of different mobility. Contexts in mobile learning are categorized into six dimensions that form a context space. Several mobile learning systems are examined according to the definition of context-aware mobile learning. Challenging issues of context awareness and adaptation are explored.
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Research works printed but not linked: 17
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Cited by
A Systematic Review of Studies on Educational Robotics
Anwar, S., Bascou, N. A., Menekse, M., & Kardgar, A. (2019) · Journal of Pre-College Engineering Education Research (J-PEER) · doi:10.7771/2157-9288.1223 · Cited by 419
Metadata
- Authors
- Wang, Y.-K.
- Affiliations
- Fu Jen Catholic University (TW)
- Corresponding author
- Yuan-Kai Wang
- ORCID
- Yuan-Kai Wang
- Venue
- The 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education, 2004. Proceedings.
- Publisher
- IEEE
- Published
- 2004-06-10
- Pages
- 154-158
- OpenAlex
- W2167416412
- Cited by
- 166
- References
- 0
- Citations by year
- 2026: 1 · 2023: 3 · 2022: 5 · 2021: 2 · 2020: 1 · 2019: 8 · 2018: 8 · 2017: 5 · 2016: 7 · 2015: 11 · 2014: 10 · 2013: 13 · 2012: 16
- FWCI
- 3.19
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Wireless, Mobile and Ubiquitous Technology in Education (WMUTE) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- context-aware learning, mobile learning, contextual adaptation, context space, interaction modes, mobile entities, mobile learning systems
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