PI: Xinran Zhu (EPOL); Co-PI: Liam Magee (EPOL)
The rapid development and deployment of generative AI tools are transforming society and redefining the boundaries between human and artificial intelligence in creative endeavors across various domains. In education, key questions arise: what remains essential to teach, and how should teaching be adapted in an AI-mediated society to prepare students for this evolving landscape? To address these questions, the proposed project aims to develop and deploy intelligent technologies that empower higher education students to engage in ethical and productive collaborations with AI during collaborative knowledge creation activities. This goal will be achieved through a system of interconnected design components: (a) SynthesisAI, a GenAI-powered technological innovation that augments the process of synthesizing and generating new ideas from existing knowledge; and (b) pedagogical strategies designed to integrate the AI tool into classrooms, with a focus on centering student agency and fostering collaborative knowledge creation. The research plan is structured around two interrelated thrusts. Thrust 1 (Co-Design and Implementation) will elaborate on the design space of SynthesisAI through co-design workshops with higher education instructors, followed by classroom implementation. Thrust 2 (Classroom Research) will integrate SynthesisAI into college-level classrooms to support student knowledge creation while iteratively refining the intervention using design-based research.
PI: Mari Altshuler (C&I); Co-PI: Scott Filkins (C&I)
Other Personnel: Adam Poetzel (C&I); Curtis Mason (C&I); Cara Gutzmer & Sue Talbott (Office of School & Community Experiences)
Bridging university coursework with the realities of K-12 classrooms is a persistent challenge in teacher education. For teachers who are balancing students’ needs with district expectations, university research can feel like a burden. For preservice teachers, the disconnect between their courses and field experiences can be a barrier to imagining themselves implementing what they are learning in their future classrooms. Feelings of anxiety towards math are common for preservice elementary teachers, making these tensions particularly salient for elementary math teacher education. In the Illinois elementary math methods course sequence, students explore, rehearse, enact, and debrief pedagogical practices intended to build their skills and confidence, but disconnected and varied field placements limit the opportunities for preservice teachers to enact and learn from these practices in elementary classroom settings. This study will advance knowledge in the field of teacher education by exploring and documenting the development of an intentional, mutually beneficial, and sustainable partnership between teacher education elementary math methods courses and a local school. In this study, we ask: How can staff and faculty in a teacher education program and from a local school come together to develop an innovative partnership that supports both preservice teacher learning and the school’s goals for math education? Ultimately, this seed project will support the visioning work for the development of a university-school partnership that could last many years into the future and serve as a model for partnerships between other teacher education methods classes and local schools and for teacher education programs at other institutions.
PI: Jina Kang (C&I)
Consultants: Saadedine Shehab (Siebel Center for Design); Christian Millan-Hernandez (University Laboratory High School)
Extended Reality (XR) offers transformative tools for exploring complex scientific concepts through immersive visualization and interaction. Recent advancements in pass-through XR address traditional VR limitations, such as social isolation, by enabling collaborative knowledge-building through verbal and non-verbal interactions in co-located settings. While these advancements expand XR’s potential, leveraging its benefits for equitable STEM education requires intentional design that prioritizes inclusivity and addresses diverse learner needs. This project employs a design justice framework to meet this challenge, emphasizing the inclusion of end users, community accountability, and equitable distribution of benefits. Through iterative design approaches, including human-centered design and co-design, the project engages diverse high school students as co-designers to create inclusive XR learning environments. By participating in the design process, these students are empowered as active contributors to STEM education solutions while fostering their sense of belonging and interest in STEM. The project comprises three design phases. Youth co-designers will develop user stories during co-design sessions, create low- to mid-fidelity prototypes, and test XR activities. A teacher will collaborate to align learning activities with standards and provide feedback on student designs. The resulting XR activities will promote inclusivity and broaden participation in STEM education. This pilot study establishes the foundation for a broader initiative to design, implement, and evaluate XR science learning applications. It will generate empirical evidence and resources to inform future external grants and create pathways for achieving equitable and transformative STEM education.
PI: Nicolas Tanchuk (EPOL); Co-PIs: Rebecca Taylor (EPOL); Tim McIlvain (Illinois Learning Technology Center)
This collaborative project addresses the pressing need to equip educators and students with a robust understanding of the social and technical issues involved in the progression from current AI technologies to artificial super-intelligence (ASI). ASI technologies are anticipated to surpass human problem-solving capacities, profoundly impacting areas such as democracy, health, and the environment. However, current AI literacy initiatives focus primarily on technical aspects of current forms of AI, neglecting foundational ethical, social, epistemic, and political dimensions critical to navigating ASI's transformative potential. This project aims to conceptualize and advance deep AI-ASI literacy, which integrates technical knowledge with reflection on foundational questions of AI design and development to foster democratic decision-making. Through a three-phase research plan, in collaboration with the Learning Technology Center, it seeks to map and enhance the assets of high school computer science teachers. Phase 1 involves systematic reviews of relevant literature and interviews with 30 educators to identify assets, barriers, and supports for robustly integrating these broader dimensions. Phase 2 (the focus of this Seed Award) will develop a survey of 380 educators to validate findings and analyze existing curricular resources. These phases lay the groundwork for Phase 3, in which external funding will be sought to co-develop scalable instructional tools and resources with teachers and instructional leaders. One key question we will explore in this project is whether case studies are a useful instructional technology to enable deliberation about the interdisciplinary questions related to the development of powerful forms of AI.