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Research on Feedback Service for Teaching Based on Educational Data Mining
2022 International Conference on Machine Learning and Knowledge Engineering, MLKE 2022 ; : 306-309, 2022.
Article in English | Scopus | ID: covidwho-1861136
ABSTRACT
Under the serious influence of COVID-19, online teaching has become a mainstream teaching mode. During the online teaching, it is difficult for teachers to evaluate and intervene in students' learning in real time. Therefore, for students who lack self-control, it is possible to be stuck in low learning efficiency and even failure of course assessment. How to obtain valid information of students' learning status in time during the online teaching process is a hot research topic at present. This paper proposes a feedback service for teaching based on educational data mining. It can, through a reasonable analysis of the data submitted in form of students' homework, accurately screen out students who have difficulties in learning a certain course and give directions to achieve the purpose of optimizing the teaching. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Reviews Language: English Journal: 2022 International Conference on Machine Learning and Knowledge Engineering, MLKE 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Reviews Language: English Journal: 2022 International Conference on Machine Learning and Knowledge Engineering, MLKE 2022 Year: 2022 Document Type: Article