Leveraging Generative AI in Science Lesson Study: Transforming Density Concept Instruction through ChatGPT Integration
Saved in:
| Title: | Leveraging Generative AI in Science Lesson Study: Transforming Density Concept Instruction through ChatGPT Integration |
|---|---|
| Language: | English |
| Authors: | Eric C. K. Cheng (ORCID |
| Source: | International Journal for Lesson and Learning Studies. 2025 14(3):215-236. |
| Availability: | Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight |
| Peer Reviewed: | Y |
| Page Count: | 22 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Secondary Education Elementary Education Grade 7 Junior High Schools Middle Schools |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Communities of Practice, Secondary School Teachers, Science Teachers, Grade 7, Faculty Development, Cooperative Planning, Critical Thinking, Technological Literacy, Pedagogical Content Knowledge, Learner Engagement, Science Instruction, Scientific Concepts, Concept Formation, Foreign Countries, Inquiry |
| Geographic Terms: | Hong Kong |
| DOI: | 10.1108/IJLLS-11-2024-0277 |
| ISSN: | 2046-8253 |
| Abstract: | Purpose: This study investigates the integration of generative AI within the Lesson Study framework in secondary science education, examining its potential to enhance pedagogical development and professional learning outcomes. Design/methodology/approach: A case study was conducted in a high school in Hong Kong, following four science teachers implementing a ChatGPT-supported Lesson Study while teaching density concepts to 30 Grade 7 students. Data collection included pre-post test, pre-lesson planning meetings, classroom observations, semi-structured interviews, focus groups, and artefact analysis, with thematic analysis following Braun and Clarke's approach. Findings: The pre-post test results suggest improvements across all density concepts. The integration of ChatGPT in the Lesson Study enhanced collaborative planning efficiency and pedagogical discussions while maintaining critical thinking. Teachers demonstrated growth in technological pedagogical content knowledge, while students showed increased engagement and autonomy in conceptual exploration. Success factors included clear AI usage guidelines, collaborative implementation, and effective scaffolding of student AI use. Research limitations/implications: Limitations include the single case study context, specific subject focus, and potential novelty effect of technology use. Future research should explore long-term impacts across diverse educational contexts and subjects. Practical implications: The findings provide actionable guidelines for educators implementing AI-supported Lesson Study, emphasising the importance of clear protocols, collaborative planning, and balanced integration of AI tools while maintaining pedagogical integrity. Social implications: The study demonstrates how AI integration in educational practices can support both teacher professional development and student learning while preserving critical thinking and autonomous learning capabilities, contributing to broader discussions about AI's role in education. Originality/value: This study provides novel insights into the systematic integration of generative AI within Lesson Study, demonstrating practical approaches for balancing technological capabilities with pedagogical objectives in science education. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1493073 |
| Database: | ERIC |
| Abstract: | Purpose: This study investigates the integration of generative AI within the Lesson Study framework in secondary science education, examining its potential to enhance pedagogical development and professional learning outcomes. Design/methodology/approach: A case study was conducted in a high school in Hong Kong, following four science teachers implementing a ChatGPT-supported Lesson Study while teaching density concepts to 30 Grade 7 students. Data collection included pre-post test, pre-lesson planning meetings, classroom observations, semi-structured interviews, focus groups, and artefact analysis, with thematic analysis following Braun and Clarke's approach. Findings: The pre-post test results suggest improvements across all density concepts. The integration of ChatGPT in the Lesson Study enhanced collaborative planning efficiency and pedagogical discussions while maintaining critical thinking. Teachers demonstrated growth in technological pedagogical content knowledge, while students showed increased engagement and autonomy in conceptual exploration. Success factors included clear AI usage guidelines, collaborative implementation, and effective scaffolding of student AI use. Research limitations/implications: Limitations include the single case study context, specific subject focus, and potential novelty effect of technology use. Future research should explore long-term impacts across diverse educational contexts and subjects. Practical implications: The findings provide actionable guidelines for educators implementing AI-supported Lesson Study, emphasising the importance of clear protocols, collaborative planning, and balanced integration of AI tools while maintaining pedagogical integrity. Social implications: The study demonstrates how AI integration in educational practices can support both teacher professional development and student learning while preserving critical thinking and autonomous learning capabilities, contributing to broader discussions about AI's role in education. Originality/value: This study provides novel insights into the systematic integration of generative AI within Lesson Study, demonstrating practical approaches for balancing technological capabilities with pedagogical objectives in science education. |
|---|---|
| ISSN: | 2046-8253 |
| DOI: | 10.1108/IJLLS-11-2024-0277 |
