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

机译:混合学习的自然语言处理和深度学习作为计算语言学的一个方面

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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.
机译:已经在信息科学中使用了多年的机器学习来创建算法,使计算机能够解决问题而不提供特定的任务和执行这些任务的说明。本文试图专注于这个AI(人工智能)子场的可能性,因为它可能会对混合的学习证明有助于。它带来了与电子学习,混合学习和机器学习以及大学课程的利用的可能问题。它还为计算语言学提供了几个问题,这可能证明它可以极大地帮助它可以带来大数据分析的混合学习过程。这些现象是相对较新的,因此,由混合学者忽略了忽视,因此本文将这些新想法带入了这些新想法,并希望呈现出在混合学习区中使用的新想法和概念。它还表明了混合学习的新方法,由混合学习2.0的术语,它实现了现代方法,例如计算语言学和语料库语言学,以利用教育过程中的电子平台。

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