Superintendent outlines new annual data cycle and flags issues with AI reading screener

The superintendent and staff updated trustees on a proposed cycle for sharing assessment and screening data and described implementation issues with the state’s newly adopted reading assessment.

Speaker 1 (Superintendent) introduced a monthly progress report on district initiatives and a proposed annual data cycle: September longitudinal trends and goal setting, October fall reading data, winter growth measures, and a June annual review. Staff recommended splitting deeper dives by grade bands (K–3, 4–8, 9–12) to improve clarity for the public and the board.

Megan (presenter) outlined use of a universal screener given three times per year and subsequent diagnostic assessments to tailor interventions. She described the district’s first experience with Amira (AI assessment after Amira purchased Istation), noting that kindergarten students and non‑English speakers sometimes had voice‑recognition issues and some responses routed to human review for scoring. “It was a great first opportunity,” she said, while cautioning the board that results differed from prior fall reading patterns and that comparability across years will be a challenge while the state and vendor refine the tool.

Board members endorsed bringing a K–3 focused data session to an upcoming meeting for deeper review and asked staff to include contextual explanations so the community can understand changes in measures over time.

Next steps: staff will provide repeated K–3 data in December and propose how to compare new assessment results with historical measures.