In this episode, I reflect on how AI is pushing educators to rethink assessment and what it truly means to measure student understanding. I share a recent experience where I used AI to help create part of an assessment and quickly noticed issues with patterns, answer structures, and predictability that weakened the quality of the assessment itself.

I unpack the idea that while AI can support assessment creation, it cannot replace thoughtful human judgment. Good assessment design still requires alignment, clarity, reflection, and intentionality. I also connect this to earlier experiences I had modifying curriculum assessments to better reflect what students had actually learned in class instead of simply following packaged materials exactly as written.

This connects directly to what educators are facing right now because AI is changing how students access information and produce responses. Polished answers do not always reflect genuine understanding, which means teachers must think more carefully about how learning is measured. Authentic thinking, reasoning, discussion, and visible understanding are becoming increasingly important.

At the end of the day, I believe this moment is less about panic and more about reflection. AI is forcing education to ask deeper questions about assessment, learning, and authenticity. Teachers still play the critical role in determining what meaningful understanding looks like and how it should be measured thoughtfully and responsibly.

• AI and assessment design
• Human judgment in assessment
• Patterns weakening multiple choice
• Alignment between teaching and testing
• Authentic understanding vs. polished output
• Reflective assessment practices

• AI can support but not replace assessment judgment
• Good assessment requires intentional design
• Polished answers do not guarantee understanding
• Alignment matters in effective assessment
• Teachers must rethink how learning is measured