Not exact matches
Two - year data averaging: using two school years» worth of data on the racial / ethnic
subgroup for that grade level,
so drawing on two cohorts of
students.
So we know that Latinx
students, black
students and then some
subgroups within the Asian American population, are not fairing as well, they are just not completing at the same rate as their white counterparts.»
Instead, schools and
students are selected randomly to participate
so that enough
students take the NAEP test for it to produce usable data for the all
students group and for particular
subgroups, like Black, Hispanic, and low - income kids.
For the first time, the law required schools to test all children annually in grades 3 through 8 and at least once in high school and report results by
subgroups — including race, English learners and
students with disabilities —
so it was clear how every
student was faring.
With waivers
so far, if a
subgroup of
students in a waiver state performed poorly, schools weren't forced to intervene.
So the state has a stake in ensuring that 95 percent of all
students and all
subgroups are tested beyond simply ensuring the validity of the test results.
All states, both waived and unwaived, must report the number and percentage of
students in each
subgroup, how many pass the reading / language arts and mathematics tests, the number who graduate high school with a standard diploma, and
so on.
While minorities and
subgroups showed improvements,
so did white
students and those not from wealthier backgrounds,
so the gaps remained at close to the same levels.
The multicolored chart also includes an «equity report» showing which
student subgroups, based on racial and ethnic background, income levels, and
so on, are lagging behind.
At every level of aggregation we lose insight into what is actually going on with
students,
so rather than being valid and actionable, a combined
subgroup seems to blur what the data means.
It will also include what Venessa Keesler calls the «crown jewel» of the dashboard: suspension and expulsion data for all
students — separated by
subgroup —
so parents can see if there are any discipline disparities.
Most state web sites do a poor job of comprehensively visualizing multiple years of
student data for multiple
subgroups so that trends can be easily seen.
One positive aspect that came out of NCLB was that it highlighted achievement gaps among
subgroups of
students, and ESSA will continue to do
so.
Three studies have examined these effects
so far and found positive effects on educational attainment for at least one
subgroup of
students.
NCLB requires states to publish and disaggregate data by
subgroups so we know which
students are being well served and which ones are not.
The Fifth Indicator must be measurable to the extent that it can be disaggregated by
student subgroups, tiered
so states can identify differences between high and low performing schools, and linked somehow to
student achievement.