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Utilization of Artificial Intelligence Technology in Higher Education Management

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DOI: 10.23977/aduhe.2023.051916 | Downloads: 69 | Views: 852

Author(s)

Longlong Wang 1,2

Affiliation(s)

1 School of Education, Philippine Women's University, Ermita Manila, Metro Manila, Philippine
2 Department of Accounting, Shandong College of Economics and Business, Weifang, Shandong, China

Corresponding Author

Longlong Wang

ABSTRACT

Traditional university education management has issues such as low efficiency and lack of personalization. As artificial intelligence (AI) technology develops rapidly, its application in educational management in universities is increasingly becoming a focus of attention for academics and educational institutions. To explore the application of AI technology in higher education management, this paper focused on personalized course recommendations for students. The data from the 2010 KDD Cup Education Data Mining Challenge dataset was collected and cleaned using Talend and Apache Spark tools; information features were extracted using information gain, and finally the data was trained using the C4.5 decision tree algorithm to obtain a recommendation model. After experiments, the precision of this model for students' preferences in course selection reached 94%, and the F1 value of the model reached 0.93, indicating that the model had good precision and comprehensiveness. At the same time, the highest recommended course click through rate reached 0.39, indicating that the personalized recommendation ability of the model was excellent. This model improved the efficiency of students' course selection and the utilization of educational resources, exploring new ways for university education management.

KEYWORDS

University Education Management, Artificial Intelligence Technology, Personalized Course Recommendation, C4.5 Decision Tree Algorithm

CITE THIS PAPER

Longlong Wang, Utilization of Artificial Intelligence Technology in Higher Education Management. Adult and Higher Education (2023) Vol. 5: 121-128. DOI: http://dx.doi.org/10.23977/aduhe.2023.051916.

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