This study introduces an LLM-powered Smart Report Assistant grounded in audience analysis and assessment design principles. Using retrieval-augmented generation, the system helps teachers interpret assessment data through personalized and conversational reporting. Results from a usability study indicate promise for supporting score interpretation and data-informed instructional decision-making.

The emerging dominance of AI in the perception of skills-of-the-future makes assessing AI skills necessary to help guide learning. Creating an assessment of AI skills poses some new challenges. We examine those from the point of view of washback, and exemplify using two exploration studies conducted with 9th grade students.