How to Measure What Matters
Most districts already have more useful data than they realize. The challenge is not collecting more, it is framing what you already have as evidence of student progress across all three time horizons.
Start with What You Already Have
Before adding any new data collection, it is worth taking stock of what already exists in your district. Most student information systems contain attendance records, discipline data, course completion rates, credit attainment, and graduation data. Most Maine districts are already administering DRA assessments and NWEA MAP testing. State assessment data includes student growth percentiles. None of this requires anything new.
The gap is usually not in data collection. It is in how the data gets used. Attendance data that sits in a report nobody reads is not a measure. It becomes a measure when someone is looking at it regularly, connecting it to a specific risk the district identified, and asking what it is telling them.
This training walks through what is available across all three time horizons, organized by how much effort it takes to collect and use.
Early Indicators: Year One
Early indicators are the measures most likely to show movement before academic data does. They tend to be behavioral and relational, and many of them already live in systems districts use every day.
Chronic absenteeism rate. Students missing 10 percent or more of school days. Most SIS platforms can generate this report. Track it by subgroup and watch it over time.
Daily attendance rate. Overall and by subgroup. A small shift in attendance across a large group of students can signal that something is changing, for better or worse.
Tardiness patterns. Often in the SIS but rarely pulled as a standalone indicator. Persistent tardiness can signal disengagement or barriers outside school that attendance alone does not capture.
Discipline referral counts and types. Track total referrals, but also pay attention to the ratio of office referrals to classroom-handled incidents. A high ratio of office referrals may indicate something about staff capacity or student relationships, not just student behavior.
Extracurricular and activity participation. Often tracked for eligibility purposes but rarely used as an outcome measure. Students who are connected to school through activities tend to show stronger engagement and attendance over time.
Scheduled counselor contact. School counselors maintain appointment schedules. Tracking which students have had at least one scheduled contact with a counselor in a given period is a low-burden measure that captures something meaningful about connection to support. It is worth noting that informal contacts, a student stopping a counselor in the hallway, or a brief conversation at recess, are valuable but not reliably trackable and should not be the basis of a formal measure.
Intervention participation rates. If a district is investing in an intervention, tracking whether students are actually showing up to it is a basic early indicator of whether the investment has a chance of working. Many districts fund interventions and never track attendance within them.
Student wellness screeners. Tools like the Panorama Student Success Survey or similar instruments can capture student perceptions of belonging, engagement, and social-emotional wellbeing. These are not measures to implement lightly. They require staff time to administer, a clear plan for how results will be reviewed and acted on, and honest communication with students and families about how data will be used. A screener that gets administered and then filed away is worse than not administering it at all.
Trusted adult identification. Some districts ask students to identify at least one trusted adult in the building as part of a broader advisory or check-in structure. This can be a meaningful early indicator of connection, but it requires a structured process and follow-through when students cannot name anyone.
Intermediate Outcomes: Years Two to Three
Intermediate outcomes tell you whether students are making meaningful progress over time. Most of this data already exists in Maine districts. The work is pulling it consistently and framing it as evidence of progress rather than just reporting.
Course completion rates by grade level. Are students finishing the courses they enroll in? Track this over time and by subgroup.
Credit attainment on track for graduation. Are students accumulating credits at the pace needed to graduate on time? This is one of the strongest predictors of graduation available to districts.
Failed course rates by subgroup. A course failure is a significant event with long-term consequences. Tracking rates over time tells you whether interventions are making a difference before it shows up in graduation data.
Retention rates. Grade retention is both an outcome measure and a risk factor for future dropout. Track it over time.
Year over year reduction in discipline referrals. Intermediate reduction in referrals, sustained over two to three years, suggests something structural is changing rather than just a good year.
Out of school suspension rates. Also reported federally. Track by subgroup and over time.
Intra-district subgroup gap trends. Rather than comparing to statewide benchmarks, track whether the gap between student subgroups within your own district is narrowing over time. Use whatever data your district already collects. A gap that is closing, even slowly, is meaningful evidence that investments are working.
DRA score growth. Maine districts already administer Developmental Reading Assessments. Growth from one administration to the next, and from one year to the next, is a meaningful intermediate outcome for early literacy investments. This requires nothing new, only that someone is tracking the growth rather than just the score.
NWEA MAP growth. Maine districts that administer MAP testing have access to RIT score growth data within and across years. Growth percentiles tell you how much a student grew relative to students at a similar starting point nationally. A district serving students with significant academic challenges may show strong growth even when absolute scores remain below average.
Student growth percentiles from state assessments. Maine’s state assessment data includes growth measures. These are available to districts but are not always pulled and used systematically alongside proficiency data.
Long-Term Outcomes: Beyond School
Long-term outcomes are the hardest to measure systematically because most of them become visible years after students leave the district. That does not mean they should be ignored. It means districts need to be honest about what they can track and creative about how they tell the story.
Four-year graduation rate. Reported to the state. Track over time and by subgroup. Note that in smaller Maine districts, subgroup cell sizes can limit reliable reporting at the subgroup level.
Five-year graduation rate. Also reported. Some students who do not graduate in four years complete in five. Tracking both gives a more complete picture.
Dropout rate. Track over time and pay attention to when in a student’s career dropouts are occurring. Early dropout patterns often trace back to risk factors that were visible years earlier.
CTE credential attainment. Maine has a strong CTE system. Students who complete a CTE program and earn an industry credential have a documented postsecondary pathway. This is a meaningful long-term outcome that many Maine districts can already track.
College enrollment through the National Student Clearinghouse. Maine districts can access college enrollment and persistence data through the National Student Clearinghouse. Access and use of this data varies by district. It is worth knowing whether your district has a process for pulling this data and whether anyone is reviewing it.
Graduate success stories. Colleges do this well. They understand that what moves people is not aggregate data but a face, a name, and a story. Districts can do the same thing. Intentional outreach to graduates a few years out, asking what prepared them and what did not, serves two purposes. It gives the district qualitative evidence about long-term outcomes, and it generates stories that can be shared with the community in newsletters, board presentations, and on the district website. A graduate who came back to work in the community, or who was the first in their family to complete a postsecondary program, answers the community’s return on investment question in a way no statistic can.
The most honest thing a district can say about long-term outcomes is this: we cannot always measure them precisely, but we can set them as targets, track the proxies we have access to, and tell the stories that bring them to life. That combination is more credible than either pretending you have data you do not, or staying silent about outcomes altogether.
Look at the three tiers across all three time horizons. Which measures is your district already pulling and using consistently? Which ones exist in your systems but nobody is looking at? Which ones are you not capturing at all? Where is the biggest gap between what you are measuring and what would actually tell you whether your investments are working?