Abstract
Personalized learning is a hot topic in education study in recent years. How to evaluate the students and find out the problem, is a problem that has to be solved in the study of individualized learning. Although the traditional education platform enables students to make full use of network resources, it does not really realize students’ personalized learning. This study analyzes the general reference model of the adaptive learning system to understand the characteristics of each part. And we established an adaptive learning system model for foreign language writing to realize students’ individual independent learning. In order to provide reference for the future research and application of adaptive learning technology, this study also makes an in-depth analysis of the adaptive learning technology and its application. It shows that adaptive learning technology is involved in a wide range of fields, but its application fields tend to be concentrated. The improvement of learning style model and the application of education big data and adaptive engine provide more accurate and intelligent personalized learning services for learners.
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References
Qiang, J., Wei, Z., Pengjiao, W.: Personalized adaptive online learning analysis model and implementation based on big data. China Educ. Technol. 1, 85–92 (2015)
Zhiting, Z., Demei, S.: New paradigm of education technology research based on big data. E-educ. Res. 10, 5–13 (2010)
Xiaoji, Y.: Research on the construction of personalized teaching information service platform based on big data application. Inf. Sci. 11, 53–56 (2015)
Zhiting, Z., Bin, H., Demei, S.: Reverse innovation in information-based education. Educ. Res. (3), 5–12+50 (2014)
Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. Lecture Notes in Computer Science, vol. 4321, pp. 3–53. Springer, Heidelberg (2007)
Qiang, J., Wei, Z., Pengjiao, W.: Study on the architecture of adaptive learning system based on GALSRM model. Mod. Distance Educ. 1, 71–77 (2013)
Ma, X., Zhong, S., Xu, D.: Research on support model and implementation mechanism of personalized adaptive learning system from the perspective of big data. China Educ. Technol. 4, 97–102 (2017)
Bian, L., Xie, Y.: Research on the adaptive strategy of adaptive learning system. In: Zhang X., Zhong S., Pan Z., Wong K., Yun R. (eds.) Entertainment for Education. Digital Techniques and Systems. Edutainment. Lecture Notes in Computer Science, vol. 6249, pp. 203–214. Springer, Heidelberg (2010)
Jia-Jiunn, L., Ya-Chen, Ch., Shiou-Wen, Y.: Designing an adaptive web-based learning system based on students’ cognitive styles identified online. Comput. Educ. 58(1), 209–222 (2012)
Mulwa, C., Lawless, S., Sharp, M., Wade V.: A web-based framework for user-centred evaluation of end-user experience in adaptive and personalized e-learning systems. In: WI-IAT 2011 Proceedings of the IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, pp. 351–356. IEEE (2011)
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Liu, JH., Ruan, LX., Zhou, YY. (2019). Application of Big Data on Self-adaptive Learning System for Foreign Language Writing. In: Xiong, N., Xiao, Z., Tong, Z., Du, J., Wang, L., Li, M. (eds) Advances in Computational Science and Computing. ISCSC 2018 2018. Advances in Intelligent Systems and Computing, vol 877. Springer, Cham. https://doi.org/10.1007/978-3-030-02116-0_11
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DOI: https://doi.org/10.1007/978-3-030-02116-0_11
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