A reform path for English learning based on data mining algorithms
This paper utilizes data mining algorithms to predict the evaluation value of new items by target users in an interactive learning environment. To enhance data quality, redundant data in the dataset is eliminated. To provide better learning recommendations and personalized services, prediction accur...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-01-01
|
| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.01112 |
| _version_ | 1797340653003210752 |
|---|---|
| author | Zhou Haiping Zhang Qian |
| author_facet | Zhou Haiping Zhang Qian |
| author_sort | Zhou Haiping |
| collection | DOAJ |
| description | This paper utilizes data mining algorithms to predict the evaluation value of new items by target users in an interactive learning environment. To enhance data quality, redundant data in the dataset is eliminated. To provide better learning recommendations and personalized services, prediction accuracy is assessed by calculating the deviation between predicted and actual ratings. Teachers and students can use the analysis results of feature weights, correct word cut scores, and other indicators obtained from data mining as key learning references. In the data mining analysis of students’ English learning data, the feature weight is 0.921, which helps to assess students’ knowledge mastery and learning effect more accurately. |
| first_indexed | 2024-03-08T10:06:18Z |
| format | Article |
| id | doaj.art-f7a77f989d014fa1b703b3fcfb97fda4 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:06:18Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-f7a77f989d014fa1b703b3fcfb97fda42024-01-29T08:52:39ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01112A reform path for English learning based on data mining algorithmsZhou Haiping0Zhang Qian11Hebei Polytechnic Institute, Shijiazhuang, Hebei, 050091, China.1Hebei Polytechnic Institute, Shijiazhuang, Hebei, 050091, China.This paper utilizes data mining algorithms to predict the evaluation value of new items by target users in an interactive learning environment. To enhance data quality, redundant data in the dataset is eliminated. To provide better learning recommendations and personalized services, prediction accuracy is assessed by calculating the deviation between predicted and actual ratings. Teachers and students can use the analysis results of feature weights, correct word cut scores, and other indicators obtained from data mining as key learning references. In the data mining analysis of students’ English learning data, the feature weight is 0.921, which helps to assess students’ knowledge mastery and learning effect more accurately.https://doi.org/10.2478/amns.2023.2.01112english learningpredicting target usersdata miningfeature weightsword slicing68p05 |
| spellingShingle | Zhou Haiping Zhang Qian A reform path for English learning based on data mining algorithms Applied Mathematics and Nonlinear Sciences english learning predicting target users data mining feature weights word slicing 68p05 |
| title | A reform path for English learning based on data mining algorithms |
| title_full | A reform path for English learning based on data mining algorithms |
| title_fullStr | A reform path for English learning based on data mining algorithms |
| title_full_unstemmed | A reform path for English learning based on data mining algorithms |
| title_short | A reform path for English learning based on data mining algorithms |
| title_sort | reform path for english learning based on data mining algorithms |
| topic | english learning predicting target users data mining feature weights word slicing 68p05 |
| url | https://doi.org/10.2478/amns.2023.2.01112 |
| work_keys_str_mv | AT zhouhaiping areformpathforenglishlearningbasedondataminingalgorithms AT zhangqian areformpathforenglishlearningbasedondataminingalgorithms AT zhouhaiping reformpathforenglishlearningbasedondataminingalgorithms AT zhangqian reformpathforenglishlearningbasedondataminingalgorithms |