mlsanityData to 14 Oct 2026

Transforming Teachers' Roles and Agencies in the Era of Generative AI: Perceptions, Acceptance, Knowledge, and Practices

arXiv 2410.03018 ↗First posted 3 Oct 2024cs.CY cs.AIcited by 8

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Abstract (arXiv)

This paper explores the transformative impact of Generative Artificial Intelligence (GenAI) on teachers' roles and agencies in education, presenting a comprehensive framework that addresses teachers' perceptions, knowledge, acceptance, and practices of GenAI. As GenAI technologies, such as ChatGPT, become increasingly integrated into educational settings, teachers are required to adapt to evolving classroom dynamics, where AI plays a significant role in content creation, personalized learning, and student engagement. However, existing literature often treats these factors in isolation, overlooking how they collectively influence teachers' ability to effectively integrate GenAI into their pedagogical practices. This paper fills this gap by proposing a framework that categorizes teachers into four roles -- Observer, Adopter, Collaborator, and Innovator -- each representing different levels of GenAI engagement, outlining teachers' agencies in GenAI classrooms. By highlighting the need for continuous professional development and institutional support, we demonstrate how teachers can evolve from basic GenAI users to co-creators of knowledge alongside GenAI systems. The findings emphasize that for GenAI to reach its full educational potential, teachers must not only accept and understand its capabilities but also integrate it deeply into their teaching strategies. This study contributes to the growing literature on GenAI in education, offering practical implications for supporting teachers in navigating the complexities of GenAI adoption.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 15 of its 48 references that are in the map. First posted on arXiv 3 Oct 2024.

Builds on

15 of 48 references.

References · 15

  1. 2023Applying Large Language Models and Chain-of-Thought for Automatic Scoringcited by 69
  2. 2024Bias in Generative AIcited by 19
  3. 2024Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Educationcited by 15
  4. 2023NERIF: GPT-4V for Automatic Scoring of Drawn Modelscited by 13
  5. 2023Gemini Pro Defeated by GPT-4V: Evidence from Educationcited by 12
  6. 2023AI Gender Bias, Disparities, and Fairness: Does Training Data Matter?cited by 8
  7. 2024Using ChatGPT for Science Learning: A Study on Pre-service Teachers' Lesson Planningcited by 8
  8. 2024PhysicsAssistant: An LLM-Powered Interactive Learning Robot for Physics Lab Investigationscited by 8
  9. 2024Can generative AI and ChatGPT outperform humans on cognitive-demanding problem-solving tasks in science?cited by 7
  10. 2022Pseudo AI Biascited by 6
  11. 2023Collaborative Learning with Artificial Intelligence Speakers (CLAIS): Pre-Service Elementary Science Teachers' Responses to the Prototypecited by 5
  12. 2024Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AIcited by 5
3 more
  1. 2024Generative AI as a Learning Buddy and Teaching Assistant: Pre-service Teachers' Uses and Attitudescited by 5
  2. 2021Quantifying Confounding Bias in Generative Art: A Case Studycited by 1
  3. 2024Validating an Instrument for Teachers' Acceptance of Artificial Intelligence in Educationcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 5; 2026: 1.

8 papers.