Systematic Literature Review for the Use of AI Based Techniques in Adaptive Learning Management Systems

被引：8

作者：

Nadimpalli, Vamsi Krishna ^{[1
]}

Hauser, Florian ^{[1
]}

Bittner, Dominik ^{[1
]}

Grabinger, Lisa ^{[1
]}

Staufer, Susanne ^{[1
]}

Mottok, Juergen ^{[1
]}

机构：

[1] Tech Univ Appl Sci Regensburg, Regensburg, Germany

来源：

PROCEEDINGS OF THE 5TH EUROPEAN CONFERENCE ON SOFTWARE ENGINEERING EDUCATION, ECSEE 2023 | 2023年

关键词：

Learning Management System (LMS); Artificial Intelligence; Learning style; Learning paths; Learning content organization; RECOMMENDER SYSTEM; CLASSIFICATION; OBJECTS; STYLES; CONSTRUCTION; RECOGNITION;

D O I：

10.1145/3593663.3593681

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Nowadays, learning management systems are widely employed in all educational institutions to instruct students as a result of the increasing in online usage. Today's learning management systems provide learning paths without personalizing them to the characteristics of the learner. Therefore, research these days is concentrated on employing AI-based strategies to personalize the systems. However, there are many different AI algorithms, making it challenging to determine which ones are most suited for taking into account the many different features of learner data and learning contents. This paper conducts a systematic literature review in order to discuss the AI-based methods that are frequently used to identify learner characteristics, organize the learning contents, recommend learning paths, and highlight their advantages and disadvantages.

引用

页码：83 / 92

页数：10

共 74 条

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