Enhancing Education through Multimodal Learning Analytics and AI-as-a-Service
Keywords: education, machine learning, research and development, explosives, information and communication technology, Data analytics, behavioral sciences, learning (artificial intelligence), Multimodal Learning Analytics, Consumer electronics, Artificial In-telligence as a Service
Abstract
In recent years, Multimodal Learning Analytics (MMLA) has offered significant opportunities for improvement in education, student teaching, and learning processes. However, the recent explosive advancement of artificial intelligence tech-nologies has strongly impacted the scenario of disciplines related to the use of information technologies. The scopes of these new technologies are still unknown. This article describes the potential for developing and researching Artificial Intelligence as a Service (AIaaS) to improve current applications and research in MMLA. We present eight types of analysis that can be enhanced by AIaaS, as well as a comparative analysis of the most well-known AIaaS currently on the market. The combination of AIaaS and MMLA tools is expected to provide a new impulse for improving teaching-learning processes, which could positively impact the overall quality of education methodologies.
Más información
Título de la Revista: | 2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) |
Editorial: | IEEE Computer Society |
Fecha de publicación: | 2024 |
URL: | 10.1109/CHILECON60335.2023.10418760. |
DOI: |
10.1109/CHILECON60335.2023.10418760. |