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ED163 - AI in Assessment and Feedback

Grading decisions carry weight. They determine who advances, who’s workplace-ready, who passes licensing exams. Your professional reputation depends on assessment quality, yet crushing volume makes thorough evaluation unsustainable. You’re working weekends to provide feedback that arrives too late. You’re worried about consistency when fatigue sets in. And valuable assessment data revealing what students actually need sits unexamined because there’s no time to analyze patterns.

This course explores where AI supports assessment work without compromising professional judgment about student competency. You’ll learn to analyze patterns informing instruction, maintain consistent standards across submissions, and provide developmental feedback efficiently. By the end, you’ll have practical strategies for managing assessment volume while preserving the expertise-driven decisions that make grading meaningful.

IMPORTANT:
This course assumes foundational knowledge of AI concepts, the Tell-Team-Trust framework for interaction, the three pillars of AI literacy, and ethical AI practices. It is strongly recommended that you complete ED160: AI Literacy Foundations for CTE Educators and ED161: AI Ethics, Bias, and Responsible Use before enrolling in this course.