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

Vamsi Krishna Nadimpalli, Florian Häuser, Dominik Bittner, Lisa Grabinger, Susanne Staufer, Jürgen Mottok

202320 citationsDOI

Abstract

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.

Topics & Concepts

Computer scienceLearning ManagementAdaptive learningArtificial intelligenceKnowledge managementData scienceMachine learningMultimediaOnline Learning and AnalyticsIntelligent Tutoring Systems and Adaptive LearningEducational Technology and Assessment
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