| Title | Online teaching quality evaluation based on emotion recognition and improved AprioriTid algorithm |
| Authors | 於慧 |
| Issue Date | 2021 |
| Publisher | Journal of Intelligent and Fuzzy Systems |
| Keywords | AprioriTid algorithm Emotion recognition improved algorithm online teaching quality evaluation |
| Citation | Journal of Intelligent & Fuzzy Systems. 2021;40(4):7037-7047. |
| Abstract | The association rule algorithm in data mining is used to study the factors that may affect students' performance, to make suggestions for teaching work, and to provide decision-making basis for teachers and teaching administrators, which has practical significance. There are many potential applications for facial expression recognition technology. For example, in the teaching process, facial expression recognition technology helps teachers understand students and judge students' reactions to certain things. Based on the current research status of emotion recognition and data mining algorithms, this paper improves the AprioriTid algorithm and constructs an online teaching quality evaluation model based on teaching needs. In addition, this article applies the model constructed in this article to the evaluation of English online teaching quality and evaluates teaching quality through data mining. The experimental research shows that the model constructed in this paper has good performance. |
| ISSN | 1064-1246 |
| Appears in Collections: | 大学英语教研室 |
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