Abstract
Following current trends in language learning applications, a context-based language generating application was developed to aid learners in effective language acquisition. In an effort to not only match the user’s situation with a relevant sentence, but also combine context information to create heterogeneous sentences, a new data model was devised. This paper describes the structure of this model based on a sensing data classifier as well as the corresponding language database. It also depicts a usage scenario with a procedural description of the underlying processes.
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Cope, B., Kalantzis M.: Ubiquitous learning: an agenda for educational transformation. In: Ubiquitous Learning, pp. 3–14 (2009)
Hornby, A.S.: The situational approach in language teaching (I). ELT J. 4(4), 98–103 (1950)
Dey, A.K.: Providing Architectural Support for Building Context-Aware Applications. Diss, Georgia Institute of Technology (2000)
Vygotsky, L.S.: Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge (1980)
Kukulska-Hulme, A.: Language learning defined by time and place: a framework for next generation designs, pp. 1–13. Emerald Group Publishing Limited (2012)
Schilit, B.N., Adams, N., Want, R.: Context-aware computing applications. In: The First IEEE Workshop on Mobile Computing Systems and Applications, WMCSA (1994)
Kofod-Petersen, A., Mikalsen M.: Context: Representation and reasoning. Special issue of the Revue d’Intelligence Artificielle on Applying Context-Management (2005)
Lane, N.D., et al.: ZOE: a cloud-less dialog-enabled continuous sensing wearable exploiting heterogeneous computation. In: Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services. ACM (2015)
Chen, C.M., Li, Y.-L., Chen, M.-C.: Personalised context-aware ubiquitous learning system for supporting effective English vocabulary learning. Interact. Learn. Environ. 18(4), 341–364 (2010)
Petersen, S.A., Markiewicz, J.-K., Bjørnebekk, S.S.: Personalized and contextualized language learning: choose when, where and what. Res. Pract. Technol. Enhanced Learn. 4(01), 33–60 (2009)
Acknowledgment
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R7120-17-1007, SIAT CCTV Cloud Platform).
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Surridge, L., Park, Yh. (2018). A Mapping Model to Match Context Sensing Data to Related Sentences. In: Lee, W., Choi, W., Jung, S., Song, M. (eds) Proceedings of the 7th International Conference on Emerging Databases. Lecture Notes in Electrical Engineering, vol 461. Springer, Singapore. https://doi.org/10.1007/978-981-10-6520-0_13
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DOI: https://doi.org/10.1007/978-981-10-6520-0_13
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