Does showing up move outcomes here?
We set every student’s attendance for the year against their grades. Not a study from somewhere else — our students, this year. The question for the board: how tightly is attendance tied to how a Val Verde student does in class?
We looked at all 18,897 students — no names, no rows, just the pattern they make together.
Source: Aeries SIS export, 2026-06-04 (de-identified). 18,897 students, 26 sites.
A full grade-point spread, end to end, on attendance alone.
Students who attend 95–100% of the time carry a 3.2 GPA. Students below 80% carry a 2.3. The decline is steady at every step down — attendance and grades move together.
Mean GPA by attendance band. Source: Aeries SIS, 2025–26 (de-identified).
As attendance falls, GPA falls and D/F rates climb.
GPA slides from 3.2 to 2.3 across the attendance bands; the share of students with at least one D or F nearly doubles, 15.7% to 35.8%. The steepest drop is below 90% — the line where chronic absence begins.
Mean GPA and D/F rate by attendance band, all students. Source: Aeries SIS, 2025–26 (de-identified).
students is chronically absent — missing 10% or more of the year.
The district’s 91.5% average daily attendance reads fine on its own. It hides the tail: 24.9% of students are chronically absent, and 6.9% are severely absent — below 80%.
Source: Aeries SIS, 2025–26 (de-identified). Chronic = below 90% attendance.
The same district, split by attendance.
A chronically absent student is two-thirds more likely to fail a class and nearly three times as likely to be suspended. Same schools, same teachers — the difference is time in the seat.
Source: Aeries SIS, 2025–26 (de-identified). Chronic = below 90% attendance.
Attendance falls as students move up — chronic absence rises with it.
The pattern is not flat across the system. Attendance is strongest in elementary and weakest in high school, where more than one in four students is chronically absent.
By high school, the habit is set. The window to change it is earlier.
ADA and chronic-absence rate by school level. Source: Aeries SIS, 2025–26 (de-identified).
The gap is real for every group — but the lever differs.
Chronic = below 90%. Source: Aeries SIS, 2025–26 (de-identified). EL coding pending Code-Table confirmation.
Chronic absence concentrates — it is not a districtwide flat line.
The district sits at 24.9%. Most sites cluster near that line — but at the highest-need sites, chronic absence runs to about 61%. The response should follow the concentration, not spread evenly.
Top 12 sites by chronic-absence rate; the full 26-site set is in the dashboard. The two highest — Val Verde High School and Val Verde Academy (alternative settings) — carry high chronic absence by design; read them apart from the comprehensive sites. Source: Aeries SIS, 2025–26 (de-identified).
Four moves the data points to.
An early-warning signal on attendance
Flag students as they approach the 90% line — with tardies counted — so a site can act before the habit sets, not after a semester of D’s.
Academic support for English Learners
ELs attend well but carry the lowest GPA. The lever here is in-class support and language scaffolding, not attendance outreach.
Targeted support at the highest-need sites
A handful of sites carry chronic-absence rates near 60%. Concentrate staffing and outreach where the rate is, rather than thinning it across 26 sites.
Watch RFEP students after reclassification
Reclassified students attend best yet fail at the highest rate. Keep a check-in in place after reclassification so the support doesn’t drop off.
Each move connects to a finding in this deck. Source: Aeries SIS, 2025–26 (de-identified).
Catching it before it starts.
The same data, read forward — who’s at risk in August and October, not June.
of this year’s chronically absent students were chronically absent last year, too.
Last year’s chronic group relapsed at 64% — against a 24% base rate across all students. Most of the risk is knowable before the first bell.
who were chronic before
who relapsed
all students
Prior-year (2024–25) vs. current attendance, joined on surrogate ID. Source: Aeries SIS (de-identified).
Two absences in the first month, and the odds flip.
A student who misses two days in the first four weeks ends the year chronically absent 47% of the time — against 15% for a student with perfect early attendance. The signal is visible by late September.
Year-end chronic-absence rate by first-month (first 20 instructional days) absence count, all students. Source: Aeries SIS, 2025–26 (de-identified).
A short list, most of the catch.
A flag built only from last year’s attendance and this year’s first-month absences watches a small share of students — and catches most of the ones who go on to become chronically absent. Adding early grades and behavior catches more, for a few more students watched.
Prior-year attendance + first-month absences. Nothing else needed.
Adds early D/F and suspensions. More caught, a few more watched.
The work is acting on the list, not finding it. By October a site can name most of the students who will fall behind by June — while there is still a year to change it.
Retrospective validation against 2025–26 outcomes. ABC = Attendance / Behavior / Course. Source: Aeries SIS (de-identified).
Methodology and caveats.
Attendance is the lever —and the cliff is at 90%.
Where we move attendance, outcomes follow. The data tells us where to start: earlier, at the sites that carry the most, and with support matched to each group.