mlsanityData to 14 Oct 2026

A4L: An Architecture for AI-Augmented Learning

arXiv 2505.06314 ↗First posted 8 May 2025cs.CY cs.AIcited by 4

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Abstract (arXiv)

AI promises personalized learning and scalable education. As AI agents increasingly permeate education in support of teaching and learning, there is a critical and urgent need for data architectures for collecting and analyzing data on learning, and feeding the results back to teachers, learners, and the AI agents for personalization of learning at scale. At the National AI Institute for Adult Learning and Online Education, we are developing an Architecture for AI-Augmented Learning (A4L) for supporting adult learning through online education. We present the motivations, goals, requirements of the A4L architecture. We describe preliminary applications of A4L and discuss how it advances the goals of making learning more personalized and scalable.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 3 of its 17 references that are in the map. First posted on arXiv 8 May 2025.

Builds on

3 of 17 references.

References · 3

  1. 2024Jill Watson: A Virtual Teaching Assistant powered by ChatGPTcited by 24
  2. 2024HTN-Based Tutors: A New Intelligent Tutoring Framework Based on Hierarchical Task Networkscited by 3
  3. 2025Enhanced Question-Answering for Skill-based learning using Knowledge-based AI and Generative AIcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.