Study on Graduation Design Teaching Reform Based on Big Data Information for Inter-disciplinary Talent

DOI

10.2991/icessms-16.2017.47How to use a DOI?

Keywords

Graduation Design; Big Data; Inter-disciplinary Talent; Data Mining

Abstract

Graduation design plays important role to improve the comprehensive ability of the cultivation object, whose methods and ways influence the training effect directly. This paper takes the computer professional graduation design based on big data information as the research object, and the graduation design topic selection, implementation and evaluation of the entire process as the main process. Using the data mining technology assisted with the internet information resources to avoid the repeatability of the topic selection, the loose of the implementation and the fuzzy of the evaluation for the graduation design, which can obtain good results such as the topic selection with instruction, the implementation has interaction and the evaluation has standard. Meanwhile, the cultivation object can grasp the frontier dynamic and the market demand during the graduation design process, which can improve the theory and practice ability at the same time. As a result, it can help the inter-disciplinary talent growth. Practice has proved that the graduation design using big data information can improve the effect of the cultivation of the inter-disciplinary talent.

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  - JianWu Zhang
PY  - 2017/02
DA  - 2017/02
TI  - Study on Graduation Design Teaching Reform Based on Big Data Information for Inter-disciplinary Talent
BT  - Proceedings of the 2016 2nd International Conference on Education, Social Science, Management and Sports (ICESSMS 2016)
PB  - Atlantis Press
SP  - 229
EP  - 233
SN  - 2352-5398
UR  - https://doi.org/10.2991/icessms-16.2017.47
DO  - 10.2991/icessms-16.2017.47
ID  - Zhang2017/02
ER  -