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This practitioner paper describes the Making Sense of Models (MSM) curriculum that bridges math and science learning through agent based modeling and rich computational thinking investigations that do not require teaching computer programming in middle school classrooms. The MSM curriculum supports students in the NGSS skill of reasoning about how and why a phenomenon happens. After developing decoding skills, students are able to assess the validity of a model based on comparing mechanisms in the model to what they learned about the phenomenon being modeled. The paper also describes how the MSM curriculum supports students’ ability to reason about scientific models and the real world. 

Artificial intelligence (AI) has rapidly pervaded and reshaped almost all walks of life, but efforts to promote AI literacy in K-12 schools remain limited. There is a knowledge gap in how to prepare teachers to teach AI literacy in inclusive classrooms and how teacher-led classroom implementations can impact students. This paper reports a comparison study to investigate the effectiveness of an AI literacy curriculum when taught by classroom teachers. The experimental group included 89 middle school students who learned an AI literacy curriculum during regular school hours. The comparison group consisted of 69 students who did not learn the curriculum. Both groups completed the same pre and post-test. The results show that students in the experimental group developed a deeper understanding of AI concepts and more positive attitudes toward AI and its impact on future careers after the curriculum than those in the comparison group. This shows that the teacher-led classroom implementation successfully equipped students with a conceptual understanding of AI. Students achieved significant gains in recognizing how AI is relevant to their lives and felt empowered to thrive in the age of AI. Overall this study confirms the potential of preparing K-12 classroom teachers to offer AI education in classrooms in order to reach learners of diverse backgrounds and broaden participation in AI literacy education among young learners. 

In the face of the rising prevalence of artificial intelligence (AI) in daily life, there is a need to integrate lessons on AI literacy into K12 settings to equitably engage young adolescents in critical and ethical thinking about AI technologies. This exploratory study reports findings from a teacher professional development project designed to advance teacher AI literacy in preparation for teaching an AI curriculum in their inclusive middle school classrooms. Analysis compares the learning experiences of 30 participating teachers (including Computer Science, Science, Math, English, and Social Studies teachers). Results suggest Science teachers’ understanding of AI concepts, particularly logic structures, is on average higher than their non-Science teacher counterparts. Teacher interviews reveal several thematic differences in Science teachers’ learning from the AI PD as compared to their counterparts, namely learning from reflective discourse with diverse groups. Findings offer insights on the depth and quality of Science teacher AI literacy after participating in an AI teacher PD, with implications for future research in the integration of AI education into Science teachers’ inclusive K12 classrooms. 

In the face of the rising prevalence of artificial intelligence (AI) in daily life, there is a need to integrate lessons on AI literacy into K12 settings to equitably engage young adolescents in critical and ethical thinking about AI technologies. This exploratory study reports findings from a teacher professional development project designed to advance teacher AI literacy in preparation for teaching an AI curriculum in their inclusive middle school classrooms. Analysis compares the learning experiences of 30 participating teachers (including Computer Science, Science, Math, English, and Social Studies teachers). Results suggest Science teachers’ understanding of AI concepts, particularly logic structures, is on average higher than their non-Science teacher counterparts. Teacher interviews reveal several thematic differences in Science teachers’ learning from the AI PD as compared to their counterparts, namely learning from reflective discourse with diverse groups. Findings offer insights on the depth and quality of Science teacher AI literacy after participating in an AI teacher PD, with implications for future research in the integration of AI education into Science teachers’ inclusive K12 classrooms.