The State of the Art and Future Tendency of Smart Education

Zheng Qinghua; Dong Bo; Qian Buyue; Tian Feng; Wei Bifan; Zhang Weizhan; Liu Jun

doi:10.7544/issn1000-1239.2019.20180758

Journal of Computer Research and Development > 2019 > 56(1): 209-224. > DOI: 10.7544/issn1000-1239.2019.20180758 CSTR: 32373.14.issn1000-1239.2019.20180758

Zheng Qinghua, Dong Bo, Qian Buyue, Tian Feng, Wei Bifan, Zhang Weizhan, Liu Jun. The State of the Art and Future Tendency of Smart Education[J]. Journal of Computer Research and Development, 2019, 56(1): 209-224. DOI: 10.7544/issn1000-1239.2019.20180758

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The State of the Art and Future Tendency of Smart Education

Zheng Qinghua^1,3,
Dong Bo^2,3,
Qian Buyue^1,3,
Tian Feng^1,3,
Wei Bifan^2,3,
Zhang Weizhan^1,3,
Liu Jun^1,3

¹(School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049)
²(School of Continuing Education, Xi’an Jiaotong University, Xi’an 710049)
³(National Engineering Laboratory for Big Data Analytics (Xi’an Jiaotong University), Xi’an 710049)

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Published Date: December 31, 2018

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Abstract

Abstract

At present the smart education pattern supported by information technology such as big data analytics and artificial intelligence has become the trend of the development of education informatization, and also has become a popular research direction in academic hotspots. Firstly, we investigate and analyze the data mining technologies of two kinds of educational big data including teaching behavior and massive knowledge resources. Secondly, we focus on four vital technologies in teaching process such as learning guidance, recommendation, Q&A and evaluation, including learning path generation and navigation, learner profiling and personalized recommendations, online smart Q&A and precise evaluation. Then we compare and analyze the mainstream smart education platforms at home and abroad. Finally, we discuss the limitations of current smart education research and summarize the research and development directions of online smart learning assistants, learner smart assessment, networked group cognition, causality discovery and other smart education aspects.
- smart education,
- educational big data,
- big data analytics,
- artificial intelligence,
- knowledge graph

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