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Machine Learning and Modern Education

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e-Learning, e-Education, and Online Training (eLEOT 2018)

Abstract

Machine learning is an important branch of artificial intelligence, which simulates human’s real learning activities by machine so that the machine can acquire corresponding skills, knowledge and processing means to achieve artificial intelligence. The process of machine learning is the process of obtaining certain knowledge by a specific activity for a machine with a certain purpose, which is manifested as knowledge from unknown to known, and from the concrete to the abstract. The learning process of human brain is the process of acquiring knowledge, skills and attitudes through interaction with teachers, students and teaching information in the teaching context. It also shows the unknown and the known, and focuses on migration and application. Based on the consistency between machine learning and modern education, and based on the analysis of the theoretical basis and relationship between the two, machine learning is applied to modern education, which paves the way for the common development of the two.

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References

  1. Yang, Z.: Development status and trends of research on machine learning. Inf. Control 01, 34–37 (1987)

    Google Scholar 

  2. Xu, X.: On Robert Gagne academic thought and its revelation. J. Ningbo University (Educ. Sci. Ed.) 31(01), 15–18 (2009)

    Google Scholar 

  3. Huang, K.: Machine learning and modern educational technology. In: Computer and Education-Proceedings of the 12th Annual Academic Conference of the National Association of Computer-Aided Education. Computer-Assisted Education Committee of the China Artificial Intelligence Society. Professional Committee of Computer Aided Education of China Artificial Intelligence Society, p. 4 (2005)

    Google Scholar 

  4. Zhang, X., Zhang, L.: On machine learning and its application in education. Inf. comput. (Theoret. Ed.) 24, 165–166+173 (2015)

    Google Scholar 

  5. Huang, W.: A brief analysis of machine learning and its application in education. Sci. Technol. Inf. 18, 648–649 (2011)

    Google Scholar 

  6. Liu, X.: Thinking of machine learning and educational teaching. Sci. Technol. Inf. 18, 648–649 (2011)

    Google Scholar 

  7. Zhu, Z., Peng, H.: Deep learning: the core pillar of Wisdom education. China Educ. J. 05, 36–45 (2017)

    Google Scholar 

  8. Guo, Y., Feng, S.: Research on machine learning theory. China Sci. Technol. Inf. 14, 208–209+214 (2010)

    Google Scholar 

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Correspondence to Yun Lin.

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Chai, M., Lin, Y., Li, Y. (2018). Machine Learning and Modern Education. In: Liu, S., Glowatz, M., Zappatore, M., Gao, H., Jia, B., Bucciero, A. (eds) e-Learning, e-Education, and Online Training. eLEOT 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 243. Springer, Cham. https://doi.org/10.1007/978-3-319-93719-9_6

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