Multimodal learning - Wikipedia Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video
35 Multimodal Learning Strategies and Examples - Prodigy Education But many others have a shared preference among two or more types, making them multimodal learners Multimodal learners have a near-equal preference for different learning modes and can receive input from any of these modes
What is Multimodal AI? - IBM Multimodal AI refers to AI systems capable of processing and integrating information from multiple modalities or types of data These modalities can include text, images, audio, video or other forms of sensory input
Multimodal - What does it mean? - VARK Learn Being Multimodal means that when learning, you prefer to use two or more of the four VARK modalities – VISUAL (V), AURAL (A), READ WRITE (R), and KINESTHETIC (K) – rather than preferring a single modality
What is Multimodal AI? - DataCamp Multimodal learning is unlocking new possibilities for intelligent systems The combination of multiple data types during the training process makes multimodal AI models suitable for receiving multiple modalities of input type and generating multiple types of outputs
What is multimodal literacy? - Ellevation What is multimodal literacy? “Multimodal literacy” means that two or more means or types of communication are being used and aims to utilize multiple senses or modalities during the learning process The purpose is to engage all students with all learning styles
10 Multimodality Examples (2025) - Helpful Professor For instance, in a course on composition, an instructor may ask students to utilize multimodal forms of expression So, in addition to a text-based written composition, modes of expression could also include sound, images, and motion