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From Content to Comprehension: How AI Powers Every Step of Instruction

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Poster
Poster Theme: AI & Emerging Tech in Education
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Session description

Wayground's AI works across the full instructional journey: creating activities, adapting them for every learner — including students with IEPs and 504 plans — engaging students in real time, and surfacing what's actually working. Responsible innovation means AI that serves all students, not just some.

Outline

1. The Problem (intro panel): Most AI in ed-tech optimizes for the average learner. What does it look like when AI is designed for every learner?
2. The Framework: Wayground's four-stage instructional journey — Create, Adapt, Engage, Analyze — and where AI intervenes at each stage
3. Live Demo Stations (core of poster): One visual panel per stage showing real product examples, with emphasis on accommodations (text-to-speech, extended time, simplified language, IEP alignment)
4. Responsible Innovation: How guardrails, teacher control, and transparency are built into AI features — not bolted on
5. Takeaway: A one-page evaluation framework attendees can use to assess any AI tool against equity and instructional criteria

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Outcomes

1. Identify where AI can be embedded across the instructional journey — from content creation to real-time adaptation, engagement, and data analysis
2. Evaluate AI-powered tools against an equity lens, specifically for students with IEPs, 504 plans, and diverse learning needs
3. Apply a replicable framework for responsible AI adoption that balances innovation with inclusion
4. Articulate the difference between AI as a productivity shortcut vs. AI as an instructional equity lever

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Supporting research

Universal Design for Learning — CAST, 2018: Framework for flexible learning experiences that meet the needs of all students; Wayground's AI accommodations operationalize UDL principles at scale
AI and Personalized Learning — Zawacki-Richter et al., 2019: Systematic review finding AI's strongest educational impact is in adaptive learning and formative feedback
IDEA (Individuals with Disabilities Education Act): Federal mandate requiring appropriate accommodations — AI can reduce teacher burden while improving consistency
Formative Assessment and Achievement — Black & Wiliam, 1998: Landmark research showing timely, specific feedback dramatically improves outcomes — the evidence base for AI-powered real-time analytics
Equity in Ed-Tech — Reich & Ito, 2017: Documents how technology amplifies existing inequities unless designed explicitly for marginalized learners

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Presenters

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Product Marketing
Wayground (Formerly Quizizz)

Session specifications

Topic:

Artificial Intelligence

Grade level:

PK-12

Audience:

District-Level Leadership, School Level Leadership, Teacher

Attendee devices:

Devices not needed

Subject area:

Multi-Language Learners, Other: Please specify

ISTE Standards:

For Education Leaders: Equity and Citizenship Advocate
For Educators: Designer, Analyst

Transformational Learning Principles:

Ensure Opportunity, Elevate Reflection

Disclosure:

The submitter of this session has been supported by a company whose product is being included in the session