Natural Language Processing and Deep Learning for Blended Learning as an Aspect of Computational Linguistics

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Abstract

Machine learning has been used for several years already in information science to create algorithms which enable computers to solve problems without giving them particular tasks and instructions to perform these tasks. This paper attempts to concentrate on possibilities of this AI (artificial intelligence) subfield inasmuch it could prove helpful for blended learning. It brings possible questions which are connected to e-learning, blended learning and machine learning and its utilization in university courses. It also brings several questions of computational linguistics which could prove extremely helpful in blended learning processes in which it could bring big data analysis. These phenomena are relatively new, therefore, neglected by blended learning scholars, thus this paper brings these new ideas together and wants to present new ideas and concepts which will be utilized in blended learning area. It also suggests new approach to blended learning, coined by the term blended learning 2.0, which implements modern approaches such as computational linguistics and corpus linguistics into the utilization of e-platforms in the educational process.

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Pikhart, M. (2021). Natural Language Processing and Deep Learning for Blended Learning as an Aspect of Computational Linguistics. In Advances in Intelligent Systems and Computing (Vol. 1231 AISC, pp. 842–848). Springer. https://doi.org/10.1007/978-3-030-52575-0_69

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