Today, beyond language preferences, there are few ways for users to express fine-grained content preferences to Web servers for them to adapt, personalize, or customize content. Without user-preference tools, sites like simple.wikipedia.org resort to providing separate URLs instead of providing different views of content for the primary URL.
It would both benefit users and provide websites with new opportunities to better meet users' needs if users could express a greater number of content-customization preferences such as reading level, language fluency, and background knowledge. Artificial intelligence is making it easier for websites to customize content, creating new opportunities to meet finer-grained preferences.
The mission of this group is to explore and discuss mechanisms for users to express content-customization preferences. This group will explore and discuss topics including artificial intelligence, adaptive hypermedia, adaptive explanation, adaptive learning, adaptive instructional systems, and user modeling.
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For whom should large-scale repositories of knowledge, e.g., Wikipedia, phrase their content: article subject-matter experts, laypeople, or students? Similarly, what about technical documentation? Digital textbooks?
What if content authors could provide multiple intended audiences – differing with respect to their reading levels, language fluencies, and background knowledge – with multiple interrelated variations of Web resources?
What if content authors could provide software with styled content outlines and this software would formulate prompts for and interactions with artificial-intelligence systems to generate natural-language content for multiple intended audiences?
What if end-users could dynamically adjust their fine-grained content-related preferences by adjusting one or more “adaptation parameters” to maximize the subjective readability and comprehensibility of Web resources for themselves?
The Adaptation and Personalization Community Group intends to explore and to discuss these and many more related questions!
Technical topics of interest to our group include artificial intelligence, adaptive hypermedia, adaptive explanation, adaptive learning, adaptive instructional systems, and user modeling.
To browse and participate in our discussion area, please visit here.
Today, beyond language preferences, there are few ways for users to express fine-grained content preferences to Web servers for them to adapt, personalize, or customize content. Without user-preference tools, sites like simple.wikipedia.org resort to providing separate URLs instead of providing different views of content for the primary URL.
It would both benefit users and provide websites with new opportunities to better meet users’ needs if users could express a greater number of content-customization preferences such as reading level, language fluency, and background knowledge. Artificial intelligence is making it easier for websites to customize content, creating new opportunities to meet finer-grained preferences.
The mission of this group is to explore and discuss mechanisms for users to express content-customization preferences. This group will explore and discuss topics including artificial intelligence, adaptive hypermedia, adaptive explanation, adaptive learning, adaptive instructional systems, and user modeling.
This is a community initiative. This group was originally proposed on 2026-03-25 by
Adam Sobieski. The following people supported its creation: Aldo Gangemi, Adam Sobieski, Milton Ponson, Frances Gillis-Webber and Wolfgang Wimmer.
W3C’s hosting of this group does not imply endorsement of the activities.
w3c-cg/adaptation
