| Theme |
Description/Key Takeaways |
Project Examples
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| Expanding accessibility for learners through digital tools |
Six projects were explicitly focused on developing digital tools that expand accessibility for learners with disabilities and neurodivergent learners. Some projects are at the stage of co-designing with learners to understand their needs. Other projects have built AI and mixed-reality tools such as sensory extension devices, ASL sign recognition, and screen readers to reduce barriers in STEM education. |
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| Alternative modalities in CS education |
Seven projects used alternative modalities such as AI, AR/VR, tangible computing, and interdisciplinary learning to offer students opportunities to engage with CS. These projects often focused on the development of immersive, mixed-reality environments and AI tools that supported collaborative learning in CS. Notably, one project developed a framework that uses AI to generate code from natural language descriptions. |
|
| VR/AR tools in STEM education |
Twelve projects developed VR/AR tools to better support understanding of STEM concepts ranging from computational thinking in early childhood classrooms to mining engineering courses in postsecondary settings. For science and engineering classes, the tools provided simulations of laboratory conditions that allowed students to gain “hands-on” experience. In math, novel modeling and visualization of abstract math concepts in mixed reality created opportunities for multimodal learning. Two projects in younger grades also integrated a learner’s surroundings to ground learnings in computational thinking and math. |
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| Innovations in workforce development |
Four projects utilized AR/VR and AI technology for workforce training in high-stakes or high-risk situations that can’t be easily replicated, such as medical emergencies and construction safety. Key achievements include new knowledge about AR’s impact on workers’ perception of safety hazards, the development of a multi-user VR experience, and increased training impact through narrative-driven games. |
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| Broadening participation of marginalized groups through technology |
Five projects are leveraging technology for the empowerment of underrepresented groups and expanding equity in the areas of literacy, social studies, data science, CS, and language learning. These projects are intentional about co-designing with underrepresented groups, particularly Black youths, Indigenous communities, and women of color. Notable key achievements include the development of novel learning algorithms for speech technology for young speakers of African American English (AAE) as well as a role-based, advocacy-driven data literacy platform for Black youths. |
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| Centering educators in AI/ML tools |
Ten projects designed AI/ML tools that generate feedback for student work or teacher instruction to aid teachers in K-12 and postsecondary classrooms. These projects often utilize generative AI for tasks that are traditionally time and resource intensive (e.g., grading papers, monitoring student work, and providing personalized feedback in real time). Notably, one project focused on using AI to reduce bias in teaching through simulated environments while another integrated AI algorithms into web-conferencing tools to monitor team productivity. Four of the projects are in the process of co-designing with teachers to ensure that the final product reflects teachers’ most pressing needs. |
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| Co-designing with youths |
Seven projects explicitly involved youths in the design process of the final product. In most cases, these youths are from marginalized groups with inequitable access to technology due to their race or disability status. Co-design varied in format—some projects sought the input of youths for more accessible tools and games while others focused on the development of new curricula. One project in particular conducted numerous summer co-design workshops and discovered the need to develop an open-source tool to engage participants in more active, equitable co-design. |
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| LLM limitations and successes |
Three projects mentioned the use of LLM in developing technology to support teachers. Two projects demonstrated successes with LLM in extracting key information from math and science work. For argumentative text, however, LLM struggled in identifying the relevant information. |
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