Abstract
The Computing Research Laboratory (CRL) at New Mexico State University is currently engaged in the design of language teaching software, based on previously developed mature artificial intelligence and machine translation technologies within CRL. Our approach is unique because it uses the robustness of a natural language processing (NLP) system which incorporates both general world knowledge and task domain knowledge (Metallel), beliefs ascription (ViewGen), and semantic parsing techniques (PREMO) in the service of better student-system interaction.
Broadly stated, the central theoretical goal of our project is to investigate the uses of participant modeling through belief ascription in the development of an intelligent tutoring system (ITS) for second language learning, not only for the purpose of improved student-system interactions, but for the purpose of monitoring student performance and planning corrective intervention. We aim to produce a sophisticated, flexible, NLP-based tutoring system that will, on the one hand, help students acquire and maintain second language skills and, on the other, function as a workstation for investigating issues in second language acquisition and pedagogy.
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© 1992 Springer-Verlag Berlin Heidelberg
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Wilks, Y., Farwell, D. (1992). Building an Intelligent Second Language Tutoring System from Whatever Bits you Happen to Have Lying Around. In: Swartz, M.L., Yazdani, M. (eds) Intelligent Tutoring Systems for Foreign Language Learning. NATO ASI Series, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77202-3_17
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DOI: https://doi.org/10.1007/978-3-642-77202-3_17
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