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

arXiv: https://arxiv.org/abs/2410.03018 · HTML: https://mlsanity.com/paper/2410.03018/

## 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 (most cited first, 15 of 15)

- [Applying Large Language Models and Chain-of-Thought for Automatic Scoring](https://mlsanity.com/paper/2312.03748/) (2023)
- [Bias in Generative AI](https://mlsanity.com/paper/2403.02726/) (2024)
- [Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Education](https://mlsanity.com/paper/2401.00832/) (2024)
- [NERIF: GPT-4V for Automatic Scoring of Drawn Models](https://mlsanity.com/paper/2311.12990/) (2023)
- [Gemini Pro Defeated by GPT-4V: Evidence from Education](https://mlsanity.com/paper/2401.08660/) (2023)
- [AI Gender Bias, Disparities, and Fairness: Does Training Data Matter?](https://mlsanity.com/paper/2312.10833/) (2023)
- [Using ChatGPT for Science Learning: A Study on Pre-service Teachers' Lesson Planning](https://mlsanity.com/paper/2402.01674/) (2024)
- [PhysicsAssistant: An LLM-Powered Interactive Learning Robot for Physics Lab Investigations](https://mlsanity.com/paper/2403.18721/) (2024)
- [Can generative AI and ChatGPT outperform humans on cognitive-demanding problem-solving tasks in science?](https://mlsanity.com/paper/2401.15081/) (2024)
- [Pseudo AI Bias](https://mlsanity.com/paper/2210.08141/) (2022)
- [Collaborative Learning with Artificial Intelligence Speakers (CLAIS): Pre-Service Elementary Science Teachers' Responses to the Prototype](https://mlsanity.com/paper/2401.05400/) (2023)
- [Realizing Visual Question Answering for Education: GPT-4V as a Multimodal AI](https://mlsanity.com/paper/2405.07163/) (2024)
- [Generative AI as a Learning Buddy and Teaching Assistant: Pre-service Teachers' Uses and Attitudes](https://mlsanity.com/paper/2407.11983/) (2024)
- [Quantifying Confounding Bias in Generative Art: A Case Study](https://mlsanity.com/paper/2102.11957/) (2021)
- [Validating an Instrument for Teachers' Acceptance of Artificial Intelligence in Education](https://mlsanity.com/paper/2406.10506/) (2024)

## Built on by (most cited first, 8 of 8)

- [A Systematic Assessment of OpenAI o1-Preview for Higher Order Thinking in Education](https://mlsanity.com/paper/2410.21287/) (2024)
- [Generative AI and Agency in Education: A Critical Scoping Review and Thematic Analysis](https://mlsanity.com/paper/2411.00631/) (2024)
- [Human Experts' Evaluation of Generative AI for Contextualizing STEAM Education in the Global South](https://mlsanity.com/paper/2511.19482/) (2025)
- [TACLA: An LLM-Based Multi-Agent Tool for Transactional Analysis Training in Education](https://mlsanity.com/paper/2510.17913/) (2025)
- [Build AI Assistants using Large Language Models and Agents to Enhance the Engineering Education of Biomechanics](https://mlsanity.com/paper/2511.15752/) (2025)
- [Glocalizing Generative AI in Education for the Global South: The Design Case of 21st Century Teacher Educator AI for Ghana](https://mlsanity.com/paper/2504.07149/) (2025)
- [ExpertAgent: Enhancing Personalized Education through Dynamic Planning and Retrieval-Augmented Long-Chain Reasoning](https://mlsanity.com/paper/2510.07456/) (2025)
- [Education-centered critical policy analysis of AI: Ghana's AI strategy as a case](https://mlsanity.com/paper/2608.16910/) (2026)

## 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.