Mixed Teaching Reform of Computer Major Courses Under the Background of Intelligent Teaching

Mengyi Xie

2023

Abstract

Conventional teaching reform methods focus on teaching quality, and the implementation of teaching reform did not combine the characteristics of professional courses, resulting in poor teaching reform results. Therefore, under the background of intelligent teaching, this paper studies the mixed teaching reform of computer courses. Based on the background of intelligent teaching, the mixed teaching system of computer professional courses is constructed, and the mixed application level of intelligent teaching is improved from multiple perspectives, so as to realize the efficient reform of computer professional courses. Through the analysis of examples, it is verified that the teaching quality of the reform method is better and can be applied in real life.

Paper Citation

in Harvard Style

Xie M. (2023). Mixed Teaching Reform of Computer Major Courses Under the Background of Intelligent Teaching. In Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT; ISBN 978-989-758-677-4, SciTePress, pages 161-164. DOI: 10.5220/0012276500003807

in Bibtex Style

@conference{anit23,
author={Mengyi Xie},
title={Mixed Teaching Reform of Computer Major Courses Under the Background of Intelligent Teaching},
booktitle={Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT},
year={2023},
pages={161-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012276500003807},
isbn={978-989-758-677-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT
TI - Mixed Teaching Reform of Computer Major Courses Under the Background of Intelligent Teaching
SN - 978-989-758-677-4
AU - Xie M.
PY - 2023
SP - 161
EP - 164
DO - 10.5220/0012276500003807
PB - SciTePress