Promoting students’ data literacy using technologies through lesson study

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Abstract
Purpose: This article examines a lesson study (LS) approach bringing teachers and university faculty together to develop a lesson in data literacy using transformative technologies, including Generative Artificial Intelligence (Gen-AI) such as ChatGPT. Design/methodology/approach: An LS team with four teachers from a private school, facilitated by three researchers, conducted two iterations of LS on teaching scatterplots using technologies. Multiple data were collected: Videos of research lessons, videos of lesson planning and post-lesson debriefings, and post-LS focus student group and teacher interviews. Based on an enriched LS framework (Lewis, 2016), this study investigates both students’ and teachers’ learning. Findings: The students learned new concepts and skills to investigate contextual problems using technologies through the data literacy cycle. Teachers developed an understanding of relevant statistical concepts and pedagogical content knowledge needed for teaching the topic in a technology-rich environment. Teachers realized the potential of using Gen-AI for planning lessons and were eager to explore the effective use of Gen-AI further. Meanwhile, some challenges in using Gen-AI in LS were identified. Research limitations/implications: This study focuses on both teachers’ and students’ perceived learning based on interview data. However, the integration of classroom teaching data and debriefing data could provide a richer picture of their learning processes. Practical implications: This study demonstrates how data literacy could be taught through addressing contextual problems using various technologies, revealing both positive effects and associated challenges. Originality/value: The study contributes to a better understanding of how transformative technology like Gen-AI could be incorporated into LS to strengthen teachers’ and students’ learning.

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