Generative AI refers to the use of algorithms and models that can generate new content or data (in various modes such as text, image, presentation slide, audio, video, codes, etc.) based on patterns in existing information in response to human prompts (also in various modes). As ChatGPT, a large language model that uses deep learning techniques to generate human-like responses to natural language input, becomes a household name, the broader Artificial Intelligence (AI) paradigm of generative AI, of which ChatGPT belongs to, is also gaining attention beyond the computer science field.
Generative AI raises both hopes and fears, as it has enormous potential to disrupt our prevailing beliefs and practices in learning, teaching, and assessment. It may liberate learners, teachers, educational leaders, and administrators from performing certain relatively low-level learning, teaching, or administrative tasks, and yet introduce more demanding challenges and required skills to “work with” the technology effectively while addressing various challenges and avoiding possible pitfalls. The potential impact of generative AI in education is undoubtedly complex and multi-faceted.
This special issue will feature original academic papers on the opportunities and challenges of introducing and integrating generative AI into educational practices. Contributions are welcome on a range of themes, including but not limited to:
- Theoretical frameworks or epistemological perspectives for understanding and guiding the use of generative AI in education
- Critical analyses of the technological affordances and limitations of generative AI from a learning/pedagogical perspective
- Design frameworks or best practices for the use of generative AI in learning, teaching and assessment
- Teachers’ and students’ behaviours and perceptions within generative AI-supported teaching and learning experiences
- Generative AI for self-directed learning, personalised learning or adaptive learning
- Generative AI for improving accessibility, equity and inclusivity in education
- Generative AI for lifelong learning or workplace learning
- Generative AI for pre-service and in-service teacher education
- Implications of generative AI for the teaching profession and competency requirements
- Use of generative AI in education/school administration
- Systemic or policy implications of generative AI in education (national, regional or school level)
- Implications of educational use of generative AI for AI literacy, information literacy or multimodal literacy
- Academic integrity, ethical and social implications of educational use of generative AI
- Future directions for research and practice in the use of generative AI in education
