Applications of generative models such as Generative Adversarial Networks (GANs) have made their way to social media platforms that children frequently interact with. While GANs are associated with ethical implications pertaining to children, such as the generation of Deepfakes, there are negligible eforts to educate middle school children about generative AI. In this work, we present a generative models learning trajectory (LT), educational materials, and interactive activities for young learners with a focus on GANs, creation and application of machine-generated media, and its ethical

This framework identifies 10 foundational career competency areas correlated to characteristics of future work at the Human Technology Frontier and what thought leaders in the field believe successful workers in those environments need to know and be able to do. It is meant as a guide for teachers interested in helping their students develop the foundations of skills, knowledge, and abilities needed to be successful in life when they exit formal schooling. Many of the suggested competencies may already be included in the curriculum or pedagogy in K-8 classrooms. In those cases, this guide may

The ITEST Small Working Group on Computational Thinking (CT) has completed its White Paper titled: Computational Thinking for Youth. The paper aims to describe what computational thinking looks like when practiced by youth in ITEST and other NSF funded programs and how educators can support growth in computational thinking. It shares examples of CT as observed in middle school projects. It also shares observations in the form of a model that describes three stages that youth appear to progress through as their computational thinking skills evolve.