TEACHx 2026

Generative AI is a probabilistic engine; by definition, it can only predict the future based on the statistical averages of the past. As we face a new era of leading through uncertainty, how do we teach students to imagine futures that the data cannot predict?


This session introduces Speculative Pedagogy, moving the AI conversation from functional "prompt engineering" to critical "future building." Aligning with the AI, Digital Literacy & Innovative Learning track, this interactive presentation moves beyond theory into a hands-on "Future Archaeology" lab. Participants will act as archivists from the year 2050, "recovering" fictional artifacts—from AI-governed syllabi to manifestos for human-led research—to expose the hidden biases and limitations of today’s algorithmic world.


Rather than a standard lecture, this session utilizes a high-impact 15-minute "Sprint." You will use the Open Speculative Pedagogy Framework (OSPF) to prototype low-stakes, discipline-specific interventions that prioritize human agency over machine efficiency. You will leave with a versatile toolkit to help students interrogate the "black box" of AI, transforming technological "friction" into a powerful site of critical inquiry and creative resistance.

As U.S. college classrooms grow increasingly diverse, Spanish as a Heritage Language (SHL) courses must be intentionally designed for accessibility, inclusion, and digital readiness. This 45-minute interactive presentation showcases the redesign of course materials, Canvas modules, and policies in an SHL track using Universal Design for Learning (UDL), Open Educational Resources (OER), and critical AI literacy.


Guided by UDL, the course integrates multimodal OER, scaffolded academic literacy supports, transparent assignment design, and flexible assessment options to address heritage learners’ uneven reading and writing development. The Canvas site was streamlined for clarity and accessibility, and policies were revised to emphasize flexibility, growth, and equity.


To prepare students for a rapidly evolving world, the course also incorporates structured, ethical engagement with generative AI tools. Drawing on digital competency guidance from UNESCO, students critically evaluate AI outputs, examine linguistic bias, and use AI as a tool for revision and rhetorical analysis.


Participants will engage in brief collaborative activities to redesign assignments and reflect on inclusive AI practices. Attendees will leave with practical strategies for implementing UDL principles, enhancing digital literacy, and creating more accessible, student-centered learning environments.

As digital accessibility requirements under WCAG 2.1 AA and ADA Title II become increasingly stringent, higher education institutions face significant challenges in providing compliant audio descriptions (AD) for visual-heavy instructional videos. This session presents the results of a pilot project that established a cost-effective, scalable workflow for creating ADs in educational videos in collaboration with human describers/reviewers and Artificial Intelligence (AI).   
Focused on an online Bachelor’s program, the project implemented an iterative process to develop a hybrid workflow: 1) auditing video content by human reviewers based on instructional reliance on graphics, 2) generating baseline descriptions using AI and by human describers, 3) conducting human reviews to ensure pedagogical alignment, and 4) providing feedback on description for AI training and usability experience. We will discuss the challenges and successes of this hybrid workflow. The collaboration highlights refinement areas: humans corrected AI misalignments of on-screen events, adjusted overly detailed descriptions of temporary visual elements, and ensured context was introduced effectively.  
The AI tool will be introduced with AI-created descriptions for sample videos. The presenters will share visual description guidelines for structuring descriptions of technical visuals, such as diagrams, tables, and software for UI interactions. This presentation offers an actionable roadmap for leveraging AI for sustainable and compliant video accessibility. 

Motion capture technology, long established in industries such as sports, animation, and medical research, is a powerful tool for mapping and analyzing human movement. Its precision and ability to visualize biomechanical detail offer unique benefits when applied to music education—particularly in piano pedagogy, where mastery of physical nuance supports and enhances expressive performance.


Our project at Northwestern University, conducted in partnership with the Northwestern IT Emerging Technologies Lab, investigates motion capture as a platform to modernize piano instruction. By combining wearable sensor data from instructors with synchronized MIDI and multi-angle video, we facilitate dynamic visualization of expert technique—granting students access to practical demonstrations that surpass the limits of conventional teaching. The system’s interactive features, including targeted practice modes and accessible tools, encourage self-directed learning and promote a more informed development and understanding of playing habits.


Through iterative design and continued collaboration with faculty and students, we are refining this approach to prioritize accessibility and expand functionality. Beyond technical advancement, our work highlights how motion capture can foster creativity, exploration, and personalized learning—helping learners bridge the gap between understanding of physicality and technical execution in a technology-driven landscape.

This session introduces a new approach to designing an AI‑enhanced assessment for online learning, created to deepen student engagement and support experiential learning in a course on NCAA Compliance in the M.S. in Sports Administration Program at the Northwestern University School of Professional Studies. Developed through a cross‑departmental partnership, the project brought together learning designers, faculty, and academic staff in the Office of Distance Learning, working closely with programmers in the Northwestern Emerging Technologies Lab. Rather than adopting third‑party tools, the team became early adopters of Discourse AI, a custom-built GenAI web application used across several Northwestern courses. Discourse AI employs “AI Personas” as fictional conversation partners, allowing students to role‑play career‑relevant scenarios in a safe, low‑stakes environment. This design prioritizes inquiry, strategy, and decision‑making over simple answer generation, while ensuring instructors remain central as subject‑matter authorities through their feedback on student–AI transcripts. The resulting assignment simulated a real-world compliance investigation within Canvas—an experience previously unattainable in an asynchronous format. The presentation will outline the assignment structure, share insights from its initial implementation, present student survey data and feedback, and describe plans for refinement. Attendees will gain practical guidance for using custom AI tools to create meaningful, immersive learning experiences and expand the pedagogical potential of GenAI in higher education.

We all think differently. As a neurodivergent educator in a diverse classroom, I know how difficult communication can be. Sometimes understanding each other practically or empathically can be challenging. What seems obvious to one person can be confusing to another. In this event, we will learn games that creatively demonstrate the different ways we communicate and more importantly, the MANY ways we can be misunderstood. I’ll teach you games that build skills in clearer and more inclusive communication with interpersonal dynamics. Content includes a focus on how language and images can be interpreted differently. You’ll learn each game just like my students but with insider tips. Then, you’ll rotate through up to seven playing stations for hands-on experiences. A packet will be included with game directions, variations, reflection questions, etc. Apply these innovative games to the arc of a course, a specific unit, a class period, or a 15-minute exercise.  All of these have been successfully integrated into my university courses, but can be applied at any level. Pedagogically, these activities promote UDL in conjunction with gamification. 

While the rise of AI is helping education in many ways, it is hindering in others.  After giving an exam, I used to provide the opportunity for students to make up some points by revisiting what they got wrong and writing about what went wrong and how to fix it.  Last year, it became blatantly obvious that the majority of the class was using AI to complete this, thus defeating the objective.  Since I think there is great value in revisiting mistakes, this year I administered an oral exam to make up points.  Students knew that I could ask anything related to the exam topics.  In this talk, we will describe the experience and what we learned in the process, from student attitudes to the administrative burden.

For all the established benefits of implementing Universal Design for Learning (UDL), faculty face significant challenges putting it into practice, to the point development is done partially or abandoned entirely. In this interactive presentation, we guide instructors through the use of AI tools to reduce barriers to UDL implementation and reap the framework’s rewards. After comparing the pros and cons of various free AI models, participants will use a chosen tool and sample prompts to apply UDL principles to their own courses. Finally, we will leave everyone with baseline prompt frameworks that can be used for future UDL development.