Using AI to Strengthen IEP Workflows for Special Education Teachers Top 3 Key Takeaways AI reduces IEP workload by automating data collection and analysis, progress monitoring, reporting, and draft writing. Good data needs to feed AI for it to accurately support teachers in developing accurate IEPs and goals for each student. AI-powered platforms
How to Write a Strong IEP Plan Using Real Data Top 3 Key Takeaways High-quality IEPs begin with accurate, student-specific data, not guesswork. LGL’s adaptive diagnostics provide precise present levels to anchor goals. Using the full range of DORA and ADAM sub-tests helps educators write goals that truly match student needs, especially when
Common IEP Mistakes Top 3 Key Takeaways IEP goals often fail when they are vague, not measurable, or not aligned to true present levels of performance (PLAAFPs). High-quality diagnostic data—such as the data produced by DORA and ADAM—helps educators write accurate, standards-aligned, skill-specific goals. Ongoing data monitoring ensures that instruction stays responsive and
How to Create an Effective Individualized Education Program (IEP) Top 3 Key Takeaways Effective IEPs begin with high-quality diagnostic data that clearly defines a student’s present levels of performance (PLAAFP). Tools like DORA and ADAM provide granular, skill-level insights that strengthen goal-setting. Goals must be measurable, standards-aligned, and instructionally meaningful, allowing teachers to
How to Prepare Students for Real Life: The Framework Schools Are Turning to Top 3 Key Takeaways Preparing students for real life requires intentional instruction in daily living, communication, digital safety, career readiness, and self-management, not just academic achievement. LCE 2.0 provides a comprehensive, updated framework that supports the development of independence and
AI in IEPs—When the Real Ethical Question is Before the AI Top 3 Key Takeaways: The real ethical crisis in IEP development isn’t AI—it’s the systemic conditions teachers face long before AI enters the picture.Special educators are often required to build legally compliant, data-rich IEPs using tools that were never designed for students
The AI Debate: Finding Our Common Ground in K-12 Special Education By Richard Capone, CEO of Let's Go Learn https://asteriskmag.substack.com/p/common-ground-between-ai-2027-and?publication_id=2291516&post_id=178644398&triggerShare=true&isFreemail=true&r=1pg6hh&triedRedirect=true I've been following the current AI debate closely. It’s fascinating, and a little unnerving, to watch two camps take such divergent views on the technology's future. One side sees the dawn of a
Empowering Student Transitions with LCE 2.0: Let’s Go Learn’s Next Generation Life Skills Curriculum Top 3 Key Takeaways LCE 2.0 bridges academic learning and real-world transition skills to prepare students for life after high school. Personalized, data-driven instruction empowers educators to meet each student's unique transition goals. Let’s Go Learn’s LCE 2.0 aligns
AI in Special Education 1. Personalized Learning Pathways When paired with diagnostics and teacher input, AI can help teachers identify the exact sub-skills a student needs next. For example, if a student struggles with Numbers and Operations in math, AI can flag which building blocks—such as place value or fractions—should be the focus.
3 Key Takeaways There’s no one-size-fits-all homeschool curriculum — choose based on your child’s needs, your teaching style, and your goals for learning. Start with diagnostic assessments to understand exactly where your child is in reading and math — this helps prevent learning gaps and wasted time. Mix and match tools that work
