Research on Data-driven Feedback Teaching Service

DOI

10.2991/icat2e-17.2016.23How to use a DOI?

Keywords

Data-driven, Feedback, Big data, Teaching services

Abstract

In recent years, most of the teaching service models in universities are linear in the exploration of big data in education, and people who use data are mainly researchers and policy makers, the process of data generation is static. Aiming at this problem, this paper proposes a data-driven feedback teaching service model. The model is characterized by: 1) the service mode is closed and nonlinearity; 2) the process of data generation is cyclic and dynamic; 3) the results of the data analysis are fed back to the participants in the teaching activities, intervening the process of generating data effectively. Finally, two examples are given to illustrate the effectiveness of the proposed model.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiangbo Shu
AU  - Li Wang
AU  - Xu Wang
AU  - Min Zhi
AU  - Taihe Cao
AU  - Hai Liu
PY  - 2017/03
DA  - 2017/03
TI  - Research on Data-driven Feedback Teaching Service
BT  - Proceedings of The 2017 International Conference on Advanced Technologies Enhancing Education (ICAT2E 2017)
PB  - Atlantis Press
SP  - 97
EP  - 102
SN  - 2352-5398
UR  - https://doi.org/10.2991/icat2e-17.2016.23
DO  - 10.2991/icat2e-17.2016.23
ID  - Shu2017/03
ER  -