AI Educator Summit

 Real World Learning's Market Value Assets — Client Connected Projects, internships, entrepreneurial experiences, and industry credentials — are designed to give students authentic, skills-based experiences that connect learning to life beyond the classroom. AI literacy belongs in that same space.


Presenters will share how AI literacy competencies, including, evaluating AI-generated content, understanding how generative and agentic AI tools work, recognizing bias, and using AI ethically in professional contexts, align naturally with the skills RWL already prioritizes: problem-solving, professional communication, critical thinking, and student agency.


A centerpiece of the session is a model of cross-sector collaboration between a higher education faculty member and a K–12 partner educator. Presenters will share the idea of embedding AI literacy into a Client Connected Project, adding a layer of intentional AI skill-building that prepares students not just for the project but for the AI-enabled workplaces they are entering. This model is replicable, and attendees will leave with the tools to adapt it in their own districts and classrooms.

This session will explore ways to integrate AI literacy into everyday instruction. Using tools like Kira, we will explore strategies to help students understand how to use AI in safe, ethical, and responsible ways that enhance learning. Walk away with ready-to-use ideas that save time, spark curiosity, and empower students as informed, responsible users of AI.

• Prompt structures that work
• Iterative prompting and refinement
• Common pitfalls and how to avoid them

Assessment should inform instruction — but the realities of grading workload often mean that valuable student learning data goes underutilized. What if AI could help close that gap?


In this session, participants will explore how AI-powered tools can transform assessment practices by streamlining the creation of interactive, standards-aligned assessments and rubrics that capture meaningful data about student understanding. Educators will learn practical approaches to AI-enhanced feedback systems that provide more detailed, personalized responses to student work — freeing up time for the instructional planning and relationship-building that matter most.


Beyond grading efficiency, this session focuses on what comes after assessment: using student learning data to drive personalized instruction. Participants will practice interpreting AI-generated growth insights to identify learning patterns, form flexible groups, and design targeted instructional strategies that meet each student where they are. The session emphasizes maintaining teacher expertise and professional judgment as the foundation for all assessment decisions, with AI serving as a tool that amplifies — rather than replaces — educator insight.


Participants will leave with actionable strategies for designing assessments that genuinely inform instruction and approaches for using learning analytics to differentiate effectively across diverse classroom contexts.

AI can write the essay, solve the problem, and answer the question…but it can't replace your student's voice, experience, or reasoning process. Learn practical strategies for redesigning existing assignments so that AI assistance becomes irrelevant (or at least insufficient). Walk away with a concrete process for transforming the most at-risk assignments into tasks that require authentic thinking, personal reflection, and demonstrable skill. No tech expertise required. Just a willingness to rethink what we're really asking students to do.