USBE training walks districts through analyzing end‑of‑year Acadience assessment data and setting growth goals

Theresa McIntyre, an elementary language‑arts assessment specialist with the Utah State Board of Education, led a virtual training for district assessment staff on analyzing end‑of‑year Acadience reading and math data, how to interpret platform reports, and how to translate findings into goals and next‑year actions.

McIntyre opened by asking participants to open the participant notebook and their district dataset platform (MCAS, ALO, ADM, or MClass). "Today, you are learning how to analyze your end of year Acadience data and really to look at that effectiveness and growth data," she said, and instructed teams to identify areas of strength, potential underlying causes of low progress, and practical steps for the next school year.

Why it matters: McIntyre said the state growth goal for the year is that 60% of students achieve typical or better growth, rising to 65% next year. Districts use cohort 'pathways of progress' (students with the same beginning‑year composite score) to compute that percentage. In the training she ran through how to compute numerator and denominator, and gave an example where 191 of 238 students had typical or better progress, yielding an 80% pathways result.

Key guidance and examples: McIntyre summarized Acadience effectiveness guidelines: "95 to 100 percent of students who are at or above benchmark should still be there from that core instruction," and coaches and assessment directors should expect 80–100% of students below benchmark to reach at/above benchmark with appropriate strategic supports. She illustrated with a kindergarten correlation report example: of 14 students who began the year well below benchmark, six remained well below, six moved to below, one moved to at benchmark, and one moved to above benchmark. McIntyre said students who remain well below in kindergarten warrant immediate review of attendance, instruction, and intervention supports.

Practical steps: The session walked participants through three analytic tasks—effectiveness of instruction, pathways of progress, and composite score comparisons—asking teams to (1) identify what the data show, (2) consider likely underlying causes (instructional models, scheduling, staffing, assessment or progress‑monitoring practices, or professional development gaps), and (3) draft goals for the next year targeted to tier 1, 2, or 3 supports. McIntyre recommended selecting headcount rather than percent when the district needs to see actual student lists, and she demonstrated how correlation reports can reveal individual student names and trajectories.

Materials and follow‑up: McIntyre shared a participant notebook with step‑by‑step instructions (notebook pages were referenced throughout the session) and dropped slides and resource links into the chat. She asked participants to complete a short form so she could record relicensing credits and enter them into the state system, Midas, and offered follow‑up help from USBE’s early literacy and math teams. "If you have questions about your data … I'm happy to answer those or refer you to our early literacy team," she said.

The session closed with time for participants to continue working through their data and an invitation to contact USBE staff for further assistance. The training did not include formal policy changes or votes; it provided procedural guidance and hands‑on analytic practice to help districts interpret and act on assessment results.