Transforming Teachers' Roles and Agencies in the Era of Generative AI: Perceptions, Acceptance, Knowledge, and Practices
- URL: http://arxiv.org/abs/2410.03018v1
- Date: Thu, 3 Oct 2024 21:59:01 GMT
- Title: Transforming Teachers' Roles and Agencies in the Era of Generative AI: Perceptions, Acceptance, Knowledge, and Practices
- Authors: Xiaoming Zhai,
- Abstract summary: This paper explores the transformative impact of Generative Artificial Intelligence (GenAI) on teachers' roles and agencies in education.
It presents a comprehensive framework that addresses teachers' perceptions, knowledge, acceptance, and practices of GenAI.
- Score: 0.7416846035207727
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
Related papers
- Transforming Teacher Education in Developing Countries: The Role of Generative AI in Bridging Theory and Practice [0.7416846035207727]
The study focuses on Ghana, where challenges such as limited pedagogical modeling, performance-based assessments, and practitioner-expertise gaps hinder progress.
GenAI has the capacity to address these issues by supporting content knowledge acquisition, a role that currently dominates teacher education programs.
The study concludes by recommending empirical research to explore these roles further and develop practical steps for integrating GenAI into teacher education systems responsibly and effectively.
arXiv Detail & Related papers (2024-11-16T06:46:09Z) - Teacher agency in the age of generative AI: towards a framework of hybrid intelligence for learning design [0.0]
Generative AI (genAI) is being used in education for different purposes.
From the teachers' perspective, genAI can support activities such as learning design.
However, GenAI has the potential to negatively affect professional agency due to teachers' limited power.
arXiv Detail & Related papers (2024-07-09T08:28:05Z) - Securing the Future of GenAI: Policy and Technology [50.586585729683776]
Governments globally are grappling with the challenge of regulating GenAI, balancing innovation against safety.
A workshop co-organized by Google, University of Wisconsin, Madison, and Stanford University aimed to bridge this gap between GenAI policy and technology.
This paper summarizes the discussions during the workshop which addressed questions, such as: How regulation can be designed without hindering technological progress?
arXiv Detail & Related papers (2024-05-21T20:30:01Z) - Bringing Generative AI to Adaptive Learning in Education [58.690250000579496]
We shed light on the intersectional studies of generative AI and adaptive learning.
We argue that this union will contribute significantly to the development of the next-stage learning format in education.
arXiv Detail & Related papers (2024-02-02T23:54:51Z) - The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment [0.0]
We outline a practical, simple, and sufficiently comprehensive tool to allow for the integration of GenAI tools into educational assessment.
The AI Assessment Scale (AIAS) empowers educators to select the appropriate level of GenAI usage in assessments.
By adopting a practical, flexible approach, the AIAS can form a much-needed starting point to address the current uncertainty and anxiety regarding GenAI in education.
arXiv Detail & Related papers (2023-12-12T09:08:36Z) - A Model for Integrating Generative AI into Course Content Development [0.0]
"GAIDE" is a novel framework for using Generative AI (GenAI) to enhance educational content creation.
It aims to streamline content development, encourage the creation of dynamic materials, and demonstrate GenAI's utility in instructional design.
arXiv Detail & Related papers (2023-08-23T17:47:35Z) - The AI generation gap: Are Gen Z students more interested in adopting
generative AI such as ChatGPT in teaching and learning than their Gen X and
Millennial Generation teachers? [0.0]
Gen Z students were generally optimistic about the potential benefits of generative AI (GenAI)
Gen X and Gen Y teachers expressed heightened concerns about overreliance, ethical and pedagogical implications.
arXiv Detail & Related papers (2023-05-04T14:42:06Z) - Iterative Teacher-Aware Learning [136.05341445369265]
In human pedagogy, teachers and students can interact adaptively to maximize communication efficiency.
We propose a gradient optimization based teacher-aware learner who can incorporate teacher's cooperative intention into the likelihood function.
arXiv Detail & Related papers (2021-10-01T00:27:47Z) - Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI)
Curriculum [58.86139968005518]
The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education.
A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum.
The co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
arXiv Detail & Related papers (2021-01-19T11:26:19Z) - Distributed and Democratized Learning: Philosophy and Research
Challenges [80.39805582015133]
We propose a novel design philosophy called democratized learning (Dem-AI)
Inspired by the societal groups of humans, the specialized groups of learning agents in the proposed Dem-AI system are self-organized in a hierarchical structure to collectively perform learning tasks more efficiently.
We present a reference design as a guideline to realize future Dem-AI systems, inspired by various interdisciplinary fields.
arXiv Detail & Related papers (2020-03-18T08:45:10Z) - Explainable Active Learning (XAL): An Empirical Study of How Local
Explanations Impact Annotator Experience [76.9910678786031]
We propose a novel paradigm of explainable active learning (XAL), by introducing techniques from the recently surging field of explainable AI (XAI) into an Active Learning setting.
Our study shows benefits of AI explanation as interfaces for machine teaching--supporting trust calibration and enabling rich forms of teaching feedback, and potential drawbacks--anchoring effect with the model judgment and cognitive workload.
arXiv Detail & Related papers (2020-01-24T22:52:18Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.