TY - GEN
T1 - An automatic analysis and evaluation system used for teaching quality in MOOC environment
AU - Yang, Sicheng
AU - Dai, Yaping
AU - Li, Simin
AU - Zhao, Kaixin
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/7/15
Y1 - 2021/7/15
N2 - To solve the problem of automatically analyzing and evaluating the teaching content and effect of teachers in massive open online courses (MOOC) environment, an automatic teaching evaluation system is proposed in this paper to evaluate the sentiment of teacher and content of 'online classes'. Firstly, the multimodal sentiment analysis model based on voice and text is built, which can determine the degree of 'positive' and 'negative' sentiments of teachers. Then, the textbook and Baidu Encyclopedia are used as two kinds of syllabus. The '3D matching degree decision model' is built to compare the differences between the teaching content and the syllabus, then the matching degree of teaching content is given. According to the results of the sentiment analysis and matching with syllabus, the teaching quality can be effectively judged. Finally, experiments in are conducted in MOOC environment. The results of the automatic analysis and evaluation system used for teaching quality perform well.
AB - To solve the problem of automatically analyzing and evaluating the teaching content and effect of teachers in massive open online courses (MOOC) environment, an automatic teaching evaluation system is proposed in this paper to evaluate the sentiment of teacher and content of 'online classes'. Firstly, the multimodal sentiment analysis model based on voice and text is built, which can determine the degree of 'positive' and 'negative' sentiments of teachers. Then, the textbook and Baidu Encyclopedia are used as two kinds of syllabus. The '3D matching degree decision model' is built to compare the differences between the teaching content and the syllabus, then the matching degree of teaching content is given. According to the results of the sentiment analysis and matching with syllabus, the teaching quality can be effectively judged. Finally, experiments in are conducted in MOOC environment. The results of the automatic analysis and evaluation system used for teaching quality perform well.
KW - Massive open online courses (MOOC)
KW - Sentiment analysis
KW - Teaching content modeling
KW - Text match
UR - https://www.scopus.com/pages/publications/85116088124
U2 - 10.1109/DTPI52967.2021.9540117
DO - 10.1109/DTPI52967.2021.9540117
M3 - Conference contribution
AN - SCOPUS:85116088124
T3 - Proceedings 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence, DTPI 2021
SP - 38
EP - 41
BT - Proceedings 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence, DTPI 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021
Y2 - 15 July 2021 through 15 August 2021
ER -