Towards a knowledge management model for online translation learning

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Abstract

This paper endeavors to build a knowledge management model for translation learning with special reference to an on-line translation teaching platform. The Platform features a computable network of inter-related and hierarchically distributed conceptual representations of the knowledge in this field. The representation utilizes “tag-words” as the knowledge nodes to form a roadmap of navigation and also as the keywords to introduce theory-informed annotations. This knowledge management system of tag-words aims to advance our understanding of how the knowledge of language and use of language can be modeled in the source language context and remodeled in different settings of the target language context. With the help of this knowledge management system, we may explore the ontological representations of translation and provide a navigation roadmap capable of generating effective learning pathways for learners. Facilitated by the platform, learning activities may be designed to investigate the behavioral patterns of knowledge construction in specific translation learning tasks.

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Mu, Y., Tian, L., & Yang, W. (2018). Towards a knowledge management model for online translation learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11284 LNCS, pp. 198–207). Springer Verlag. https://doi.org/10.1007/978-3-030-03580-8_21

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