Open Learning Analytics: A Systematic Review of Benchmark Studies using Open University Learning Analytics Dataset (OULAD)

被引：4

作者：

Alhakbani, Haya A. ^{[1
]}

Alnassar, Fatema M. ^{[2
]}

机构：

[1] Imam Mohammad Ibn Saud Islamic Univ IMSIU, Riyadh, Saudi Arabia

[2] Goldsmiths Univ London, London, England

来源：

PROCEEDINGS OF 2022 7TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING TECHNOLOGIES, ICMLT 2022 | 2022年

关键词：

Virtual Learning Environment (VLE); Open Learning Analytics (OLE); Open University Learning Analytics Dataset (OULAD); Students' Performance Evaluation;

D O I：

10.1145/3529399.3529413

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Virtual learning has gained increased importance because of the recent pandemic situation. A mass shift to virtual means of education delivery has been observed over the past couple of years, forcing the community to develop efficient performance assessment tools. Open University Learning Analytics Dataset (OULAD) is one of the most comprehensive and benchmark datasets in the learning analytics domain. This paper presents the review of benchmark studies performed using OULAD to assess the performance of students in a Virtual Learning Environment (VLE). The presented review aims to highlight the status of technological advancements in this domain and potential future research directions.

引用

页码：81 / 86

页数：6

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