arXiv AI June 4, 2026 By Rubens Lacerda Queiroz, Cabral Lima, Fabio Ferrentini Sampaio, Priscila Machado Vieira Lima

How do machines learn? Evaluating the AIcon2abs method

arXiv:2401. 07386v5 Announce Type: cross Abstract: This study expands on previous work that introduced the AIcon2abs method (AI from Concrete to Abstract: Demystifying Artificial Intelligence to the general public), an innovative approach designed to increase public understanding of machine learning (ML) across diverse age groups, including K-12 students, and aims to evaluate its effectiveness.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 4

AI from concrete to abstract: demystifying artificial intelligence to the general public

arXiv:2006. 04013v6 Announce Type: cross Abstract: Artificial Intelligence (AI) has been adopted in a wide range of domains.

By Rubens Lacerda Queiroz, F\'abio Ferrentini Sampaio, Cabral Lima, Priscila Machado Vieira Lima

arXiv AI

Jun 18

AI-Driven Assessment of Human Tutors: Linking Training Performance to Real-Life Practice

arXiv:2606. 18617v1 Announce Type: cross Abstract: There exist numerous tutor training platforms.

By Danielle R. Thomas, Marie Cynthia Abijuru Kamikazi, Clara Brandt, Conrad Borchers, Kenneth R. Koedinger

llms

arXiv AI

Jul 14

Metacognition in LLMs: Foundations, Progress, and Opportunities

arXiv:2607. 11881v1 Announce Type: cross Abstract: Metacognition is a foundational component of intelligence critical to effective learning, problem solving, decision-making, communication, and more.

By Gabrielle Kaili-May Liu, Areeb Gani, Jacqueline Lu, Jordan Thomas, Mark Steyvers, Arman Cohan

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arXiv AI

Jun 12

Generativism: Toward a Learning Theory for the Age of Generative Artificial Intelligence

arXiv:2606. 12441v1 Announce Type: cross Abstract: The four dominant learning theories of behaviorism, cognitivism, constructivism, and connectivism show significant conceptual limitations as generative artificial intelligence (AI) proliferates in educational settings.

By Shan Li, Juan Zheng

arXiv AI

Jul 2

DigitalCoach: Communication and Grounding Gaps in Human and Agentic Computer Use Coaching

arXiv:2606. 31980v1 Announce Type: cross Abstract: Agents are increasingly capable of automating software tasks, but can they teach humans how to use software themselves?

By Meng Chen, Anya Ji, Tsung-Han Wu, Tobias Maringgele, David M. Chan, Alane Suhr, Amy Pavel

agents multimodal benchmarks

arXiv AI

Jun 2

Beyond One-shot: AI Agents for Learning in Field Experiments

arXiv:2606. 02458v1 Announce Type: new Abstract: Organizations routinely run experiments for A/B testing, yet the data generated from one experiment is underutilized to inform subsequent intervention design.

By Junjie Luo, Ritu Agarwal, Gordon Gao

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Related stories

AI from concrete to abstract: demystifying artificial intelligence to the general public

AI-Driven Assessment of Human Tutors: Linking Training Performance to Real-Life Practice

Metacognition in LLMs: Foundations, Progress, and Opportunities

Generativism: Toward a Learning Theory for the Age of Generative Artificial Intelligence

DigitalCoach: Communication and Grounding Gaps in Human and Agentic Computer Use Coaching

Beyond One-shot: AI Agents for Learning in Field Experiments