Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)

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A Method for Online Course Evaluation Based on Continuous Bag-of-Words Model and Semantic Analysis—A Case Study of Statistics

Authors
Yongjie Chu1, 2, *, Cengceng Liu3
1School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China
2Institute of High-Quality Development Evaluation, Nanjing University of Posts and Telecommunications, Nanjing, China
3School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing, China
*Corresponding author. Email: chuyongjie@njupt.edu.cn
Corresponding Author
Yongjie Chu
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-040-4_116How to use a DOI?
Keywords
Online course reviews,; Course evaluation,; Continuous bag-of-words model; Semantic analysis
Abstract

With the rapid development of the Internet and multimedia, online courses have become one of the main ways for students to learn. Online course reviews are the comments the learners or students published voluntarily based on their real learning experience of a course, which include diverse information. This paper selects the statistics-related courses in the MOOC platform as the research object and obtains online reviews of seven courses, then employs natural language processing techniques to deal with the review data and further develops a method for online course evaluation. First, the continuous bag-of-words model is used to extract the feature words of courses from the online course reviews. Secondly, based on mutual information and semantic similarity analysis, this paper identifies and clusters the learners’ preferences for online courses, the preferences include six aspects. Finally, we compute the value and weight of each aspect of preference according to the sentiment propensity and the occurrence frequency of preference words, respectively. Then the overall score of each course is calculated using the above values. Based on the results, we proposed suggestions and enlightenments for the online course development and improvement.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-040-4_116
ISSN
2589-4900
DOI
10.2991/978-94-6463-040-4_116How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yongjie Chu
AU  - Cengceng Liu
PY  - 2022
DA  - 2022/12/27
TI  - A Method for Online Course Evaluation Based on Continuous Bag-of-Words Model and Semantic Analysis—A Case Study of Statistics
BT  - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
PB  - Atlantis Press
SP  - 765
EP  - 771
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-040-4_116
DO  - 10.2991/978-94-6463-040-4_116
ID  - Chu2022
ER  -