3. Context-aware Ubiquitous Learning Environment (CULE)

CULE has the abilities to detect the learner’s context and to adapt its behavior accordingly (G´omez and Fabregat, 2010, Hsu et al., 2016; Gomez et al. 2016; Wu et al., 2012). Examples of contextual entities in a learning environment are the learner’s current place, position, time, other nearby learners, learning style, and learning history (Hasanov, and Laine, 2017). Context-aware learning environments can detect the learner’s context and adapt learning materials to match the context. The support for context-awareness is essential in these systems so that they can make learning contextually relevant. It helps to situate students in real-world learning scenarios. 

Examples of learning environments that combine real-life contexts and digital-world resources to provide students with direct experiences of the real world with sufficient learning support, Minami et al. 2004; Hung et al. 2014; Wu et al. 2013a,b.

Examples of using mobile, wireless communication and sensing technologies for developing CULE, Ogata and Yano 2004, Hwang et al. 2008; Tsai et al. 2012, Hwang et al. 2012.

CULE detect the real-world status of learners using sensing technologies such as RFID/NFC, GPS, Camera, Microphone, IR (infrared)-based sensors, interact with the learner through wireless networks, present learning guidance, and offer supplementary materials or feedback. 

Current challenges: incorporating intelligent tutoring or adaptive learning techniques to context-aware ubiquitous learning

References and Further reading:

PH Hung, GJ Hwang, YF Lin, TH Wu, IH Su, Seamless connection between learning and assessment- applying progressive learning tasks in mobile ecology inquiry. Educ Tech Soc 16(1), 194–205 (2013).

R Joiner, J Nethercott, R Hull, J Reid, Designing educational experiences using ubiquitous technology. Comput. Hum. Behav. 22(1), 67–76 (2006).

GJ Hwang, CC Tsai, HC Chu, Kinshuk, CY Chen, A context-aware ubiquitous learning approach to conducting scientific inquiry activities in a science park. Australas. J. Educ. Technol. 28(5), 931–947 (2012).

IC Hung, XJ Yang, WC Fang, GJ Hwang, NS Chen, A context-aware video prompt approach to improving in-field reflection levels of students. Comput. Educ. 70(1), 80–91 (2014).

H Ogata, Y Yano, Context-Aware Support For Computer-Supported Ubiquitous Learning, in Paper presented at the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education (JhongLi, Taiwan, 2004). 

Y Rogers, S Price, C Randell, DS Fraser, M Weal, G Fitzpatrick, Ubi-learning integrating indoor and outdoor learning experiences. Communications of the ACM 48(1), 55–59 (2005).

HK Wu, SWY Lee, HY Chang, JC Liang, Current status, opportunities and challenges of augmented reality in education. Comput. Educ. 62, 41–49 (2013a)

PH Wu, GJ Hwang, WH Chai, An expert system-based context-aware ubiquitous learning approach for conducting science learning activities. Educ. Technol. Soc. 16(4), 217–230 (2013b).

HC Chu, GJ Hwang, CC Tsai, A knowledge engineering approach to developing mindtools for context-aware ubiquitous learning. Comput. Educ. 54(1), 289–297 (2010).

GJ Hwang, CC Tsai, SJH Yang, Criteria, strategies and research issues of context-aware ubiquitous learning. Educ. Technol. Society 11(2), 81–91 (2008).

PS Tsai, CC Tsai, GJ Hwang, Developing a survey for assessing preferences in constructivist context-aware ubiquitous learning environments. J. Comp. Assist. Learn. 28(3), 250–264 (2012).

IC Hung, XJ Yang, WC Fang, GJ Hwang, NS Chen, A context-aware video prompt approach to improving in-field reflection levels of students. Comput. Educ. 70(1), 80–91 (2014).

M Minami, H Morikawa, T Aoyama, The Design Of Naming-Based Service Composition System For Ubiquitous Computing Applications, in In the Proceedings of the 2004 International Symposium on Applications and the Internet Workshops (SAINTW’04) (IEEE Computer Society, Washington, DC, 2004), pp. 304–312.

Hsu, T., Chiou, C., Tseng, J. C. R., and Hwang, G. (2016). Development and Evaluation of an Active Learning Support System for Context-Aware Ubiquitous Learning. Learning Technologies, IEEE Transactions on Learning Technologies, 9(1):37–45.

G´omez, S. and Fabregat, R. (2010). Context-Aware Content Adaptation in mLearning. In Proceedings of the 9th World Conference on Mobile and Contextual Learning.

G´omez, S., Zervas, P., Sampson, D. G., and Fabregat, R. (2014). Context-aware adaptive and personalized mobile learning delivery supported by UoLmP. Journal of King Saud University - Computer and Information Sciences, 26(1):47–61.

Wu, P.-H., Hwang, G.-J., Su, L.-H., and Haung, Y. (2012). A Context-Aware Mobile Learning System for Supportive Cognitive Apprenticeships in Nursing Skills Training. Educational Technology & Society, 5(1):223–236.

Gomez, J., Huete, J., and Hernandez, V. (2016). A contextualized system for supporting active learning. IEEE CSEDU 2017 - 9th International Conference on Computer Supported Education Transactions on Learning Technologies, (99):196–202.

Hasanov, A. and Laine, T. A Survey of Context-awareness in Learning Environments in 2010-2016. In Proceedings of the 9th International Conference on Computer Supported Education (CSEDU 2017) - Volume 1, pages 234-241.


Última modificación: sábado, 8 de febrero de 2020, 06:21