Research on educational applications based on diagnostic learning analytics in the context of big data analytics
In the context of the significant data era, this paper explores the educational applications based on diagnostic learning analytics technology to improve personalized learning and teaching effects in the educational process. The study adopts a multidimensional feature fusion approach to construct a...
| 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-2024-0624 |
| _version_ | 1797279157917319168 |
|---|---|
| author | Zhang Naimin Zhang Linlin |
| author_facet | Zhang Naimin Zhang Linlin |
| author_sort | Zhang Naimin |
| collection | DOAJ |
| description | In the context of the significant data era, this paper explores the educational applications based on diagnostic learning analytics technology to improve personalized learning and teaching effects in the educational process. The study adopts a multidimensional feature fusion approach to construct a cognitive diagnostic model to predict learners’ knowledge status and future learning performance. Through actual data testing, the model can effectively predict the students’ knowledge mastery state and analyze the students’ learning process in depth. The experimental results show that the diagnostic model exhibits high efficiency and accuracy in predicting students’ knowledge mastery status, with an accuracy rate of 92.97%, significantly better than traditional teaching methods. In addition, the study explores the encoding method of learners’ multidimensional features and constructs a dynamic diagnostic model of test factors and student factors based on graph attention network. The study provides a new learning analysis and diagnostic method in the education field, which helps improve the effect of personalized learning. |
| first_indexed | 2024-03-07T16:20:13Z |
| format | Article |
| id | doaj.art-e5ebed099eaf42bfb1a0f57c8f4821cc |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-07T16:20:13Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-e5ebed099eaf42bfb1a0f57c8f4821cc2024-03-04T07:30:43ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns-2024-0624Research on educational applications based on diagnostic learning analytics in the context of big data analyticsZhang Naimin0Zhang Linlin11Hebei Oriental University, Langfang, Hebei, 065000, China.1Hebei Oriental University, Langfang, Hebei, 065000, China.In the context of the significant data era, this paper explores the educational applications based on diagnostic learning analytics technology to improve personalized learning and teaching effects in the educational process. The study adopts a multidimensional feature fusion approach to construct a cognitive diagnostic model to predict learners’ knowledge status and future learning performance. Through actual data testing, the model can effectively predict the students’ knowledge mastery state and analyze the students’ learning process in depth. The experimental results show that the diagnostic model exhibits high efficiency and accuracy in predicting students’ knowledge mastery status, with an accuracy rate of 92.97%, significantly better than traditional teaching methods. In addition, the study explores the encoding method of learners’ multidimensional features and constructs a dynamic diagnostic model of test factors and student factors based on graph attention network. The study provides a new learning analysis and diagnostic method in the education field, which helps improve the effect of personalized learning.https://doi.org/10.2478/amns-2024-0624diagnostic learningmultidimensional featuresgraph attention network94a08 |
| spellingShingle | Zhang Naimin Zhang Linlin Research on educational applications based on diagnostic learning analytics in the context of big data analytics Applied Mathematics and Nonlinear Sciences diagnostic learning multidimensional features graph attention network 94a08 |
| title | Research on educational applications based on diagnostic learning analytics in the context of big data analytics |
| title_full | Research on educational applications based on diagnostic learning analytics in the context of big data analytics |
| title_fullStr | Research on educational applications based on diagnostic learning analytics in the context of big data analytics |
| title_full_unstemmed | Research on educational applications based on diagnostic learning analytics in the context of big data analytics |
| title_short | Research on educational applications based on diagnostic learning analytics in the context of big data analytics |
| title_sort | research on educational applications based on diagnostic learning analytics in the context of big data analytics |
| topic | diagnostic learning multidimensional features graph attention network 94a08 |
| url | https://doi.org/10.2478/amns-2024-0624 |
| work_keys_str_mv | AT zhangnaimin researchoneducationalapplicationsbasedondiagnosticlearninganalyticsinthecontextofbigdataanalytics AT zhanglinlin researchoneducationalapplicationsbasedondiagnosticlearninganalyticsinthecontextofbigdataanalytics |