Background: In the midst of digital transformation, schools are transforming their classrooms as they prepare students for a world increasingly automated by new technologies, including artificial intelligence (AI). During curricular implementation, it has not made sense to teachers to teach AI as a stand-alone subject as it is not a traditional discipline in schools. As such, subject matter teachers may need to take on the responsibility of integrating AI content into discipline-based lessons to help students make connections and see its relevance rather than present AI as separate content. This paper reports on a study that piloted a new lesson package in science classrooms to introduce students to the idea of AI. Specifically, the AI-integrated science lesson package, designed by the research team, provided an extended activity that used the same context as an existing lesson activity. Three science teachers from different schools piloted the lesson package with small groups of students and provided feedback on the materials and implementation. Findings: The findings revealed the teachers’ perceptions of integrating AI into science lessons in terms of the connection between AI and science, challenges when implementing the AI lesson package and recommendations on improvements. First, the teachers perceived that AI and science have similarities in developing accurate models with quality data and using simplified reasoning, while they thought that AI and science play complementary roles when solving scientific problems. Second, the teachers thought that the biggest challenge in implementing the lesson package was a lack of confidence in content mastery, while the package would be challenging to get buy-in from teachers regarding curriculum adaptation and targeting the appropriate audience. Considering these challenges, they recommended that comprehensive AI resources be provided to teachers, while this package can be employed for science enrichment programs after-school. Conclusions: The study has implications for curriculum writers who design lesson packages that introduce AI in science classrooms and for science teachers who wish to contribute to the development of AI literacy for teachers and the extension of the range of school science and STEM to students.

This study aims to explore how to use an AI chatbot pedagogically in scientific inquiry by developing a guided-inquiry activity using an AI chatbot and applying it. The developed guided-inquiry activity consisted of designing and doing inquiry activities using the transmission of sound as the topic. In this activity, a chatbot, which was given the name Inquirybot, was designed with conversation flow and scripts for guiding the inquiry design process. By applying the developed inquiry activities and Inquirybot to fifth- and sixth-grade gifted students, we found several practical possibilities and challenges for using an AI chatbot in scientific inquiry. Based on the results, future tasks and educational implications are discussed in terms of efficiently adapting AI chatbots in scientific-inquiry activities.

The use of group drawing to promote student‐generated representation is a common instructional strategy as it combines the benefits of using visual representation and collaborative talk. Although the affordances of group drawing have increasingly been emphasized in science education, few studies have investigated how drawing as a visual mode interacts with group discourse as a verbal mode as well as how that interaction facilitates the development of students' collective ideas. Informed by theories in classroom discourse and multimodality, this paper examines the interaction process between a verbal and visual mode of representation as groups of students engaged in collaborative drawing during guided science inquiry lessons. On the basis of the analysis of data from a science class that adopted group drawing, we found and documented a recurring pattern, Plan‐Draw‐Evaluate or PDE pattern, in how the interaction between the verbal and visual modes occurred during collaborative drawing. This PDE pattern consisted of a triad of moves that alternate between the two modes and fulfilled various discursive purposes, such as suggesting, requesting, recording, visualizing, elaborating, agreeing, and rejecting. The PDE pattern provided a basic social structure that facilitated the collaboration and progression of students' ideas. With illustrations of PDE patterns and its variations, we argue that the PDE pattern provides an insight into the dynamic organization of interactions involved in group drawing that takes into consideration the multimodal affordances of verbal and visual modes of representation and the progression of ideas developed through collaborative discourse.

The purpose of this study is to investigate the process of students’ construction of scientific explanations through drawing explanatory diagrams. For this, we observed fifth and sixth graders’ drawing processes in a gifted science class involving learning physics concepts in mechanics. The analysis was carried out on three pictorial representational levels: sensory (e.g. observed materials), unseen substance (e.g. molecules) and unseen non-substance (e.g. forces). We found that there were five patterns of interplay depending on the sequential path through the pictorial representational levels. All students began drawing explanatory diagrams from the sensory level as the first step and then constructed explanations using the unseen levels based on the interplay among different levels. In the process of forming meaningful relationships among the three levels of representation, students focused on a specific phenomenon through drawing at a sensory level and extended their making sense of the phenomenon from what happened to why it happened. Based on these findings, we suggest how teachers can use the interplay among the different pictorial representational levels to guide students in generating scientific explanations through drawing.