Research on Teaching Methods of Autonomous Learning in Mechanical Courses

DOI

10.2991/iceemr-17.2017.85How to use a DOI?

Keywords

mechanical courses, information technology, autonomous learning, teaching methods

Abstract

With the increasing requirement of the society for the ability of the talents, the cultivation mode of the autonomous learning ability is crucial in improving the student's independence and innovation. Mechanical courses are the most importance basic courses of engineering colleges. As the rapid development of information technology, traditional teaching mode has lost the attraction for young college students. Therefore, an innovative change is desired in mechanical teaching area in the colleges to adapt to the trend of social development. This paper mainly aims to make a systematic study of multi-teaching methods and autonomous learning methods in mechanical courses. The research includes techniques and methods of teaching, teaching students in accordance with their aptitude, the reform of assessment methods, and other aspects. It's very important for satisfying the needs of individualized learning and facilitating efficient autonomous learning. Multi-teaching methods have been adopted in the experimental class. The results indicated that student's interest in learning mechanical courses and teaching quality has been improved, and the students showed a high degree of satisfaction with the course.

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  - Hongxia Wang
AU  - Qiang Liu
PY  - 2017/05
DA  - 2017/05
TI  - Research on Teaching Methods of Autonomous Learning in Mechanical Courses
BT  - Proceedings of the 2017 International Conference on Education, Economics and Management Research (ICEEMR 2017)
PB  - Atlantis Press
SP  - 337
EP  - 340
SN  - 2352-5398
UR  - https://doi.org/10.2991/iceemr-17.2017.85
DO  - 10.2991/iceemr-17.2017.85
ID  - Wang2017/05
ER  -