Online English writing teaching method that enhances teacher–student interaction
A significant component of the online learning platform is the online exercise assessment system, which has access to a wealth of past student exercise data that may be used for data mining research. However, the data from the present online exercise system is not efficiently used, making each exerc...
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| Format: | Article |
| Language: | English |
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De Gruyter
2024-03-01
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| Series: | Journal of Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jisys-2023-0235 |
| _version_ | 1797229649521016832 |
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| author | Jiang Yaqiu |
| author_facet | Jiang Yaqiu |
| author_sort | Jiang Yaqiu |
| collection | DOAJ |
| description | A significant component of the online learning platform is the online exercise assessment system, which has access to a wealth of past student exercise data that may be used for data mining research. However, the data from the present online exercise system is not efficiently used, making each exercise less relevant for students and decreasing their interest and interaction with the teacher as she explains the activities. In light of this, this research creates an exercise knowledge map based on the connections between workouts, knowledge points, and previous tournaments. The neural matrix was then improved using cross-feature sharing and feature augmentation units to deconstruct the workout recommendation model. The study also developed an interactive text sentiment analysis model based on the expansion of the self-associative word association network to assess how students interacted after the introduction of the personalized exercise advice teaching approach. The outcomes demonstrated that the suggested model’s mean diversity value at completion was 0.93, an increase of 0.14 and 0.23 over collaborative filtering algorithm and DeepFM (deep factor decompose modle), respectively, and that the proposed model’s final convergence value was 92.3%, an improvement of 2.3 and 4.1% over the latter two models. The extended model used in the study outperformed the support vector machine (SVM) and Random Forest models in terms of accuracy by 5.9 and 1.7%, respectively. In terms of F1 value indicator, the model proposed by the research has a value of 90.4%, which is 2.5 and 2.1% higher than the SVM model and Random Forest model; in terms of recall rate indicators, the model proposed by the research institute has a value of 94.3%, which is an increase of 6.2 and 9.8% compared to the latter two models. This suggests that the study’s methodology has some application potential and is advantageous in terms of customized recommendation and interactive sentiment recognition. |
| first_indexed | 2024-04-24T15:15:57Z |
| format | Article |
| id | doaj.art-58e340920e8c47769748a19bba4b9cc6 |
| institution | Directory Open Access Journal |
| issn | 2191-026X |
| language | English |
| last_indexed | 2024-04-24T15:15:57Z |
| publishDate | 2024-03-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Intelligent Systems |
| spelling | doaj.art-58e340920e8c47769748a19bba4b9cc62024-04-02T09:20:11ZengDe GruyterJournal of Intelligent Systems2191-026X2024-03-01331839810.1515/jisys-2023-0235Online English writing teaching method that enhances teacher–student interactionJiang Yaqiu0College of General Studies, Changchun College of Electronic Technology, Changchun, 130000, ChinaA significant component of the online learning platform is the online exercise assessment system, which has access to a wealth of past student exercise data that may be used for data mining research. However, the data from the present online exercise system is not efficiently used, making each exercise less relevant for students and decreasing their interest and interaction with the teacher as she explains the activities. In light of this, this research creates an exercise knowledge map based on the connections between workouts, knowledge points, and previous tournaments. The neural matrix was then improved using cross-feature sharing and feature augmentation units to deconstruct the workout recommendation model. The study also developed an interactive text sentiment analysis model based on the expansion of the self-associative word association network to assess how students interacted after the introduction of the personalized exercise advice teaching approach. The outcomes demonstrated that the suggested model’s mean diversity value at completion was 0.93, an increase of 0.14 and 0.23 over collaborative filtering algorithm and DeepFM (deep factor decompose modle), respectively, and that the proposed model’s final convergence value was 92.3%, an improvement of 2.3 and 4.1% over the latter two models. The extended model used in the study outperformed the support vector machine (SVM) and Random Forest models in terms of accuracy by 5.9 and 1.7%, respectively. In terms of F1 value indicator, the model proposed by the research has a value of 90.4%, which is 2.5 and 2.1% higher than the SVM model and Random Forest model; in terms of recall rate indicators, the model proposed by the research institute has a value of 94.3%, which is an increase of 6.2 and 9.8% compared to the latter two models. This suggests that the study’s methodology has some application potential and is advantageous in terms of customized recommendation and interactive sentiment recognition.https://doi.org/10.1515/jisys-2023-0235exercisepersonalized recommendationneural matrixknowledge graphdiversity meanaccuracy |
| spellingShingle | Jiang Yaqiu Online English writing teaching method that enhances teacher–student interaction Journal of Intelligent Systems exercise personalized recommendation neural matrix knowledge graph diversity mean accuracy |
| title | Online English writing teaching method that enhances teacher–student interaction |
| title_full | Online English writing teaching method that enhances teacher–student interaction |
| title_fullStr | Online English writing teaching method that enhances teacher–student interaction |
| title_full_unstemmed | Online English writing teaching method that enhances teacher–student interaction |
| title_short | Online English writing teaching method that enhances teacher–student interaction |
| title_sort | online english writing teaching method that enhances teacher student interaction |
| topic | exercise personalized recommendation neural matrix knowledge graph diversity mean accuracy |
| url | https://doi.org/10.1515/jisys-2023-0235 |
| work_keys_str_mv | AT jiangyaqiu onlineenglishwritingteachingmethodthatenhancesteacherstudentinteraction |