mlsanityData to 7 Oct 2026

Promises and challenges of generative artificial intelligence for human learning

arXiv 2408.12143 ↗First posted 22 Aug 2024cs.HCcited by 17

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Abstract (arXiv)

Generative artificial intelligence (GenAI) holds the potential to transform the delivery, cultivation, and evaluation of human learning. This Perspective examines the integration of GenAI as a tool for human learning, addressing its promises and challenges from a holistic viewpoint that integrates insights from learning sciences, educational technology, and human-computer interaction. GenAI promises to enhance learning experiences by scaling personalised support, diversifying learning materials, enabling timely feedback, and innovating assessment methods. However, it also presents critical issues such as model imperfections, ethical dilemmas, and the disruption of traditional assessments. Cultivating AI literacy and adaptive skills is imperative for facilitating informed engagement with GenAI technologies. Rigorous research across learning contexts is essential to evaluate GenAI's impact on human cognition, metacognition, and creativity. Humanity must learn with and about GenAI, ensuring it becomes a powerful ally in the pursuit of knowledge and innovation, rather than a crutch that undermines our intellectual abilities.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Aug 2024.

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Citing papers per year: 2025: 9; 2026: 8.

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  1. 2025Does the Prompt-based Large Language Model Recognize Students' Demographics and Introduce Bias in Essay Scoring?cited by 5
  2. 2025Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the roomcited by 3
  3. 2025From Passive Tool to Socio-cognitive Teammate: A Conceptual Framework for Agentic AI in Human-AI Collaborative Learningcited by 3
  4. 2026Distinguishing performance gains from learning when using generative AIcited by 2
  5. 2025Generative AI as a Pillar for Predicting 2D and 3D Wildfire Spread: Beyond Physics-Based Models and Traditional Deep Learningcited by 1
  6. 2025CurLL: A Developmental Framework to Evaluate Continual Learning in Language Modelscited by 1
  7. 2025Agentic AI as Undercover Teammates: Argumentative Knowledge Construction in Hybrid Human-AI Collaborative Learningcited by 1
  8. 2025Designing AI-Resilient Assessments Using Interconnected Problems: A Theoretically Grounded and Empirically Validated Frameworkcited by 1
  9. 2026Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modellingcited by 1
  10. 2025Exploring Artificial Intelligence Tutor Teammate Adaptability to Harness Discovery Curiosity and Promote Learning in the Context of Interactive Molecular Dynamicscited by 0
  11. 2025Socratic Mind: Impact of a Novel GenAI-Powered Assessment Tool on Student Learning and Higher-Order Thinkingcited by 0
  12. 2026Investigating Self-regulated Learning Sequences within a Generative AI-based Intelligent Tutoring Systemcited by 0
5 more
  1. 2026Human-AI Collaboration Reconfigures Group Regulation from Socially Shared to Hybrid Co-Regulationcited by 0
  2. 2026Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Educationcited by 0
  3. 2026Toward Measuring AI's Effects on Skill Formation: The Stock-Formation Gapcited by 0
  4. 2026SCAN: A Decision-Making Framework for Effective Task Allocation with Generative AIcited by 0
  5. 2026Education-centered critical policy analysis of AI: Ghana's AI strategy as a casecited by 0