Developing Generative AI-informed Pedagogies Using Lesson Study

Introduction

Generative AI (Gen-AI) tools, like Large Language Models (LLMs) and chatbots, possess immense potential to revolutionize learning at all levels. Ethical use of Gen-AI can transform K-12 teaching and learning by providing opportunities for personalized and adaptive learning, boosting creativity and critical thinking, enhancing accessibility and inclusivity, increasing engagement and motivation, and improving teacher productivity and data-driven decision making (Farrokhnia et al., 2023; Grassini, 2023; Ipek et al., 2023; UNESCO Education 2030, 2023). However, educators must develop pedagogical understanding and skills to effectively use Gen-AI, while addressing ethical concerns and practical challenges like academic integrity, data privacy, cognitive bias, and ensuring accessibility (Halaweh, 2023; Javaid et al., 2023; UNESCO Education 2030, 2023).

Preparing students for a future of Gen-AI advancement requires teachers to adapt and nurture creativity, critical thinking, and interdisciplinary learning (Calleja & Camilleri, 2021). Towards this end, Lesson Study (LS), which supports teacher learning and pedagogical innovation, is a highly effective international initiative (Huang et al., 2023). Camilleri and Calleja (2023) further call for utilizing LS to tackle educational challenges in Industry 4.0.
Integrating Gen-AI throughout the LS cycle (study, plan, teach, reflect) could:

1. generate targeted learning materials and resources, such as customized lesson plans, activities, worksheets, and assessments;
2. facilitate collaborative lesson planning and reflections, generating creative prompts, scenarios, and problem-solving challenges, simulating different teaching approaches and classroom scenarios;
3. personalize professional development and feedback by providing personalized feedback and recommendations for individual teachers, analyzing collective lesson study data; and
4. enhance communication and collaborations, facilitating online communities and forums for teachers to share resources, generating comprehensive reports summarizing lesson study findings and recommendations.

Gen-AI can also serve as a 'knowledgeable other', supporting teachers in critically analyzing research, planning tasks and lesson activities, designing observation tools, analyzing data, and even writing reports – a typically challenging and time-consuming task for many teachers.

We believe that those engaged in LS – teachers, facilitators, and school leaders – will leverage Gen-AI in ways that create previously unimaginable learning opportunities and outcomes for themselves and their students (Lo, 2023). By prioritizing teacher autonomy, we ensure Gen-AI remains a valuable assistant, not a replacement for professional expertise. This human-centered approach emphasizes responsibility for appropriate use and targeted outcomes – the teacher remains firmly in the lead. However, we must regularly scrutinize the impact of Gen-AI on LS practices and adapt its use based on feedback and evidence. 

This Special Issue explores how LS practitioners and researchers conceptualize and develop LS to improve teaching and student learning through the integration of Gen-AI while appropriately addressing relevant concerns. It serves as a forum where researchers, LS leaders, and teachers can share their thoughts, approaches, and models for developing LS practices with the use of Gen-AI-enabled applications. Hence, the Special Issue explores and shares best practices in integrating Gen-AI into teaching and learning using LS and aims to contribute to the development of guidelines for educators addressing relevant concerns.

List of topic areas

• Case studies: Comprehensive narratives detailing the integration of Gen-AI-informed pedagogies using LS, encompassing outcomes and valuable insights gained from the experience.
• Pedagogical applications: Exploring ways in which Gen-AI can support lesson planning, observation, and reflection.
• Teacher experiences: Action research reporting teachers' perspectives on using Gen-AI, including its impact on their professional development and classroom practices.
• Researcher experiences: Perspectives from researchers on using Gen-AI, including researching LS and their own professional development.
• Ethical and practical considerations: Discussions on ethical issues related to Gen-AI in LS, along with strategies for addressing them.
• LS: Development of pedagogical models or guiding frameworks that incorporate Gen-AI tools in teaching and learning.

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available here.

Author guidelines must be strictly followed.

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to "Please select the issue you are submitting to". 

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

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Key deadlines

Closing date for abstract submission: 30th April, 2024  

Opening date for manuscripts submissions (if agreed with publisher): 30th September, 2024

Closing date for manuscripts submission: 30th November, 2024