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In the context of human–computer interaction, a modality is the classification of a single independent channel of input/output between a computer and a human. Such channels may differ based on sensory nature (e.g., visual vs. auditory), [1] or other significant differences in processing (e.g., text vs. image). [2]
In recent applications, digital learning platforms have leveraged multimedia instructional design principles to facilitate effective online learning. A prime example includes e-learning platforms that offer users a balanced combination of visual and textual content, segmenting information and enabling user-paced learning.
The most common such interface combines a visual modality (e.g. a display, keyboard, and mouse) with a voice modality (speech recognition for input, speech synthesis and recorded audio for output). However other modalities, such as pen-based input or haptic input/output may be used. Multimodal user interfaces are a research area in human ...
These phenomena are very similar, however, split-attention conditions do not need to be present in order for the spatial contiguity principle to take effect. [1] The spatial contiguity principle is the idea that corresponding information is easier to learn in a multimedia format when presented close together rather than separate or farther apart.
Information is presented through the design of digital media, engaging with multimedia to offer a multimodal principle of composition. Standard words and pictures can be presented as moving images and speech in order to enhance the meaning of words.
In short-term sentence recall studies, emphasis is placed on words in a distractor-word list when requesting information from the remembered sentence. This demonstrates the modality effect can be more than auditory or visual. [2] For serial recall, the modality effect is seen in an increased memory span for auditorally presented lists. Memory ...
In his book The Humane Interface, Jef Raskin defines modality as follows: "An human-machine interface is modal with respect to a given gesture when (1) the current state of the interface is not the user's locus of attention and (2) the interface will execute one among several different responses to the gesture, depending on the system's current state."
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.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...