mlsanityData to 7 Oct 2026

Generative AI for Education (GAIED): Advances, Opportunities, and Challenges

arXiv 2402.01580 ↗First posted 2 Feb 2024cs.CY cs.AIcited by 13

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Abstract (arXiv)

This survey article has grown out of the GAIED (pronounced "guide") workshop organized by the authors at the NeurIPS 2023 conference. We organized the GAIED workshop as part of a community-building effort to bring together researchers, educators, and practitioners to explore the potential of generative AI for enhancing education. This article aims to provide an overview of the workshop activities and highlight several future research directions in the area of GAIED.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 29 of its 63 references that are in the map. First posted on arXiv 2 Feb 2024.

Builds on

29 of 63 references.

References · 29

  1. 2015Deep Knowledge Tracingcited by 328
  2. 2023The Robots are Here: Navigating the Generative AI Revolution in Computing Educationcited by 85
  3. 2022The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialoguescited by 78
  4. 2022Do People Engage Cognitively with AI? Impact of AI Assistance on Incidental Learningcited by 53
  5. 2023Computing Education in the Era of Generative AIcited by 50
  6. 2023LitCab: Lightweight Language Model Calibration over Short- and Long-form Responsescited by 44
  7. 2023Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutorscited by 38
  8. 2023Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preferencecited by 37
  9. 2023Merging Generated and Retrieved Knowledge for Open-Domain QAcited by 36
  10. 2023Generating High-Precision Feedback for Programming Syntax Errors using Large Language Modelscited by 34
  11. 2023Prompt Problems: A New Programming Exercise for the Generative AI Eracited by 31
  12. 2020Variational Item Response Theory: Fast, Accurate, and Expressivecited by 29
17 more
  1. 2022Repairing Bugs in Python Assignments Using Large Language Modelscited by 28
  2. 2023Exploring the Potential of Large Language Models to Generate Formative Programming Feedbackcited by 28
  3. 2023Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learningcited by 24
  4. 2023Next-Step Hint Generation for Introductory Programming Using Large Language Modelscited by 20
  5. 2022Towards Process-Oriented, Modular, and Versatile Question Generation that Meets Educational Needscited by 19
  6. 2018Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inferencecited by 16
  7. 2023Neural Task Synthesis for Visual Programmingcited by 13
  8. 2023Code Soliloquies for Accurate Calculations in Large Language Modelscited by 9
  9. 2022Efficient Argument Structure Extraction with Transfer Learning and Active Learningcited by 5
  10. 2023Generative AI in the Classroom: Can Students Remain Active Learners?cited by 5
  11. 2023AuthentiGPT: Detecting Machine-Generated Text via Black-Box Language Models Denoisingcited by 5
  12. 2023Are LLMs Useful in the Poorest Schools? TheTeacher.AI in Sierra Leonecited by 4
  13. 2023EHRTutor: Enhancing Patient Understanding of Discharge Instructionscited by 4
  14. 2023Efficient Classification of Student Help Requests in Programming Courses Using Large Language Modelscited by 4
  15. 2021Play to Grade: Testing Coding Games as Classifying Markov Decision Processcited by 3
  16. 2023What Skills Do You Need When Developing Software Using ChatGPT? (Discussion Paper)cited by 3
  17. 2023The Behavior of Large Language Models When Prompted to Generate Code Explanationscited by 3

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