The implementation of the cognitive theory of multimedia learning in the design and evaluation of an AI educational video assistant utilizing large language models.

The integration of Artificial Intelligence (AI) holds immense potential for revolutionizing education; especially, in contexts where multimodal learning experiences are designed. This paper investigated the potential benefits of Generative Artificial Intelligence (AI) in education, concentrating on the design and evaluation of an AI Educational Video Assistant tailored for multimodal learning experiences. The tool, utilizing the principles of the Cognitive Theory of Multimedia Learning (CTML), comprises three modules: Transcription, Engagement, and Reinforcement, each focusing on distinct aspects of the learning process.

A semi supervised approach to Arabic aspect category detection using Bert and teacher-student model.

Aspect-based sentiment analysis tasks are well researched in English. However, we find such research lacking in the context of the Arabic language, especially with reference to aspect category detection. Most of this research is focusing on supervised machine learning methods that require the use of large, labeled datasets.