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Student Attendance in September 2020
November 2020
Table of Contents
Executive Summary ....................................................................................................................................................3
Introduction ................................................................................................................................................................4
Terms and Definitions ................................................................................................................................................4
A Few Notes of Caution ..............................................................................................................................................5
Results ........................................................................................................................................................................7
Conclusion ..................................................................................................................................................................9
Executive Summary
To support attendance and engagement of students as they participate in varied school learning models (i.e.,
in-person, hybrid, remote), the Connecticut State Department of Education (CSDE) established a new system
to collect student-level attendance data on a monthly basis. This report presents the findings from an analysis
of the September attendance data. When interpreting these data, readers are cautioned of the following:
• This is a new reporting expectation; in general, data quality improves as collection systems mature.
• A new concept of “remote attendance” is now in use. It expects districts to track attendance on
remote days using synchronous and/or asynchronous methods. This change shifts the onus of
determining and recording attendance, especially in elementary/middle schools, from front-office staff
to classroom teachers.
• Anecdotally, the CSDE has become aware of some variation in district practices for recording student
attendance on remote days, including when it is recorded and whether students can be present
remotely on an otherwise in-person school day. The CSDE recently published additional clarifications
to bring greater consistency to these areas.
• Since there is no similar monthly attendance data in prior years, comparisons of September 2020
attendance are made to the 2019-20 attendance rates that were based on data collected for in-person
school days through mid-March 2020.
The initial analysis of September attendance data indicate the following:
• Among students without high needs (i.e., those who are not English learners, do not have a disability,
and are not from a low-income family), attendance rates in September 2020 exceed 0.95 and are
comparable to their 2019-20 attendance rate. These students comprise approximately 48 percent of
the statewide public school student population.
• Among students with high needs (i.e., those who are English learners, students with disabilities, and/or
from a low income family) attendance rates in September 2020 are substantially lower than they were
in 2019-20. This is particularly pronounced among students who are identified for more than one high-
need factor (e.g., free lunch eligible students who also have a disability).
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CSDE is partnering with the State Education Resource Center (SERC) to build communities of practice and a
system of supports for districts that bring together the latest research, national experts, and promising
practices.
Introduction
In the 2020-21 school year, schools across Connecticut are using one of three learning models, i.e., fully in-
person where all students attend school in-person on all days; hybrid where all students attend school in-
person on some but not all days; or fully remote where all students receive instruction remotely through
technology or other means on all days. Since reopening in late August/early September, many districts have
changed their learning models in the first two months based either on a district schedule (e.g., planned change
in week 4 from hybrid to fully in-person) or on local health conditions (e.g., change from fully in-person to
remote for two weeks due to increased infections and positivity rate in the local community). The school
reopen plans also allow parents to opt their students into full remote learning.
In its resolution that permits remote learning days to count toward the 177 school day requirement, the State
Board of Education affirmed that its authorization for hybrid or remote programming due to unavoidable
emergency is contingent upon school districts providing rigorous learning and engagement opportunities that
are aligned with State standards and Board expectations. The Board also charged the Connecticut State
Department of Education (CSDE) with ensuring fidelity to this expectation by collecting whatever data are
necessary and making that information transparent.
Therefore, the CSDE established two new data collections: a weekly collection regarding a district’s learning
model and enrollment and a monthly student-level attendance data collection to collect the number of days of
membership and attendance for each student each month. This report analyzes attendance information for
the month of September.
Terms and Definitions
How does Connecticut define attendance?
According to State Board of Education policy, “A student is considered to be ‘in attendance’ if present at
his/her assigned school, or an activity sponsored by the school (e.g., field trip), for at least half of the regular
school day.”
How is attendance tracked on remote learning days for state reporting purposes?
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In the 2020-21 school year, a student’s attendance on a given day can be either in-person or remote. The CSDE
developed and disseminated brand new guidance for districts on how to track attendance on remote days for
state reporting. This guidance was disseminated originally on September 4. According to this guidance a
remote student can be considered as being ‘in attendance’ on a particular day if the total time spent on one or
more of the following activities equals at least half the school day: synchronous virtual classes; synchronous
virtual meetings; time logged in electronic systems; and/or assignment submission/completion.
What is attendance rate? How is it calculated?
Attendance rate is the percentage of membership days that meet the definition of “in-attendance.” It can be
calculated for an individual student or a group of students. For example, if student A is enrolled in school for
180 days in a school year (membership) and attends 171 days (attendance), then student A’s attendance rate
is 171 divided by 180 or 95% or 0.95. For a group of students (e.g., districts, school, student group), the
attendance rate is the sum total days of attendance for all students divided by the sum total days of
membership for those students.
What is chronic absenteeism? How does it differ from an attendance rate?
A student with an attendance rate that is at or below 90 percent is said to be chronically absent. The chronic
absenteeism rate for a group of students is the percentage of students with an attendance rate that is at or
below 90 percent. Please see Calculating Student Attendance Quick Reference for a detailed explanation of the
differences between the attendance rate and chronic absenteeism metrics.
A Few Notes of Caution
Please note the following cautionary points when reading this report.
• This is the first time in its history that the CSDE is collecting and reporting attendance data for the first
month of a school year. Normally, the CSDE collects attendance only once annually at the end of the
school year through the June Public School Information System (PSIS) collection. The June PSIS
membership and attendance data are used to report chronic absenteeism rates on EdSight, which are
subsequently included in the Next Generation Accountability System. As with any new data collection,
data quality is expected to improve as the collection system matures and data providers gain greater
understanding of what and how to collect and report accurate data.
• September is a month of significant change in public education systems as districts follow up to
determine the status of returning students, while also enrolling new students who may be entering the
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district. A few districts with higher ongoing family mobility will continue to see fluctuations in their
enrollment; most districts, however, will start to see a stabilization of their student enrollment in the
months ahead. These fluctuations will also impact September’s attendance data.
• A new concept of “remote attendance” has been introduced for the very first time. While the
definition of attendance is unchanged (i.e., presence for at least half a school day), the CSDE’s
guidance on how to track attendance on remote days expects districts to consider synchronous and
asynchronous approaches to determine whether a student is “in attendance.” This has fundamentally
changed who determines attendance, especially in elementary and middle schools. While previously
front-office staff may have assumed some responsibility for tracking and reporting attendance, now
classroom teachers are expected to utilize student participation to determine and record whether a
student is “in attendance.”
• Anecdotal evidence suggests that districts operationalized the state’s remote attendance guidance in
slightly different ways. For example, some districts would record attendance on a remote day by 5 pm
on that day, while others would record attendance on the following day in order to allow students the
opportunity to submit work after school hours and be marked “present.” Another difference is
whether a student who should otherwise be attending school in-person on a given day is allowed the
flexibility to be “present” remotely due to extenuating circumstances; some districts started the school
year by permitting this practice especially for health reasons, while others chose to mark the student
as “absent” even if that student participated remotely and completed work. The CSDE recently
published additional clarifications to bring even greater consistency to these areas.
• With many districts opening in a hybrid format, and around a third of students statewide learning
remotely, access to a device and internet connectivity have become essential school supplies. A
donation from the Partnership for Connecticut brought 60,000 laptops to high school students in the
33 Alliance Districts by July 2020. Additionally, in late July, Governor Lamont launched the Everybody
Learns Initiative which is bringing 82,102 laptops and Chromebooks, 12,774 hotspots, and broadband
cable to students. When reviewing the September attendance in this report, it should be noted that
while the hotspots were delivered in early September, the majority of laptops/Chromebooks are being
delivered in October with installation of broadband cable internet still underway.
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Results
Figure 1 compares the 2019-20 attendance rate to that from September 2020.
Figure 1: 2019-20 Attendance Rate Compared to September 2020 Attendance Rate
Overall, attendance rates in September 2020 were slightly lower than those in the 2019-20 school year. When
the data are disaggregated by student group, it is evident that among students from historically
underperforming groups (e.g., English learners, students with disabilities, free- or reduced-price meal eligible
students, black/African American, Hispanic/Latino, homeless), the attendance rate in September 2020 was
substantially lower than for those same groups in 2019-20. An attendance rate that is 90 percent or less can be
interpreted to mean that on average, that group of students is chronically absent. Students with high needs
are approximately 52 percent of the statewide public school student enrollment.
Conversely among students without high needs (i.e., those who are not English learners, do not have a
disability, and are not from a low-income family), attendance rates in September 2020 exceed 0.95 (or 95
percent) and are comparable to their 2019-20 attendance rate. These students comprise approximately 48
percent of the statewide public school student enrollment.
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To facilitate identification of districts for state support, the CSDE calculated the attendance rate for students
with high needs (i.e., comprised of those who are English learners, students with disabilities, and/or from a low
income family) in all districts. The CSDE then identified districts where attendance rates for students with high
needs in September 2020 was substantially lower than in the 2019-20 school year. Detailed data for all districts
are available on EdSight and can also be downloaded in CSV format. School-level data are also available for
download in CSV format.
The EdSight page also includes an interactive map (see below) that highlights towns based on the difference in
high needs attendance rates for resident students between September 2020 and the 2019-20 school year.
Figure 2: Differences in High Needs Attendance Rate between 2019-20 and September 2020
A further disaggregation of the statewide data reveal that the following student groups exhibit substantially
lower attendance rates in September 2020 as compared to those in the 2019-20 school year (see Table 1):
• English learners;
• Students eligible for free meals; and
• Students with disabilities who are also identified as either English learners or are eligible for free
meals.
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Free meal eligible students who are also an English learner or with a disability or both reflect some of the
lowest attendance rates in September 2020 and those rates are lower than the attendance rate for the
corresponding group during the 2019-20 school year (see Table 1). For instance, among students eligible for
free meals, those who are also identified as English learners and students with disabilities evidence the lowest
attendance rate of .838 which is substantially lower than the attendance rate for the same group of students in
2019-20 of 0.916. Free meal eligible students who are identified as having a disability show a low attendance
rate of .855, while those free meal eligible students who are identified as English learners have an attendance
rate of .871 which is well below the 0.9 attendance rate.
Table 1: Attendance Rate by FRL, EL, and Special Education
English Special Attendance Rate Attendance Rate
FRL Type* Number of Students
Learner Education Sep 2020 2019-20
N No No 237,551 0.968 0.961
N No Yes 32,365 0.943 0.946
N Yes No 10,219 0.895 0.950
N Yes Yes 1,534 0.903 0.946
F No No 125,610 0.900 0.936
F No Yes 31,858 0.855 0.910
F Yes No 19,899 0.871 0.939
F Yes Yes 6,845 0.838 0.916
R No No 23,493 0.942 0.954
R No Yes 4,260 0.912 0.936
R Yes No 2,393 0.916 0.957
R Yes Yes 681 0.894 0.952
*FRL Type – F=Free, R=Reduced, and N=Not eligible for FRL.
Conclusion
This is the first analysis of the new student attendance data collection for the month of September. The results
should be interpreted with caution considering that this is a new data collection where the data include
remote days of attendance and reflect some variation in the implementation of district practices.
The analysis reveals that students from traditionally underperforming groups (i.e., EL, special education, free-
reduced price meal eligibility) had lower attendance in September than during the 2019-20 school year. The
attendance challenges were compounded among students who reflected multiple high need factors (e.g.,
students eligible for free lunch who were also receiving special education). District-level disaggregated data by
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student group along with data visualizations will be used by CSDE staff to identify and support districts where
attendance in September 2020 was substantially lower than in the 2019-20 school year. CSDE is also partnering
with SERC to build communities of practice and a system of supports for districts that bring together the latest
research, national experts, and promising practices.
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