QUESTIONS FOR ANALYZING CHRONIC ABSENCE IN YOUR DISTRICT
1. Is chronic absence getting better or worse in the district?
What we saw:
• We start out by looking at Tab A, which shows chronic absence by grade, by year. Across all grades K-5, chronic absence is generally getting better. With the exception of Grade 5, for which chronic absence this past year was the same as it was in 2009-10, chronic absence levels this past year were the lowest they have been in three years.
2. What does chronic absence look like across grade levels?
What we saw:
• Continue referring to Tab A. Although this district is generally on the right track, attendance could still be improved, particularly in the early grades. Chronic absence levels are the highest in Kindergarten, followed by 1st grade—a typical pattern seen in many elementary school districts.
• In 2011-12, there was a slight increase in chronic absence in 5th grade from the previous year. This district may want to consider potential opportunities to better support its 5th grade students, particularly before the important transition to middle school.
• In addition to showing trends, Tab A (titled “By grade by year” in the DATT spreadsheet) enables you to look at the progress of a cohort of students. For example, those students who were in Kindergarten in 2009-10 were in 1st grade in 2010-11 and in 2nd grade in 2011-12. You can observe the chronic absence levels of these students in the first bar graph as the pale pink bar for Kindergarten, the medium pink bar for 1st grade, and the dark pink bar for 2nd grade. This cohort went from 21% chronic absenteeism to 13% the following year to 8% the following year, showing stead progress over time. Compare this with the cohort of students who were in 1st grade in 2009-10. They went from having 13% chronic absence in year one to a still relatively high 12% chronic absence in year two, illustrating a different pattern of attendance than the student cohort of one year younger.
3. Is satisfactory attendance getting better or worse?
What we saw:
• Continue referring to Tab A. Satisfactory attendance in this district is improving. Across all grades, the percentage of students with satisfactory attendance increased year over year (with the exception of Kindergarten, which stayed level at 52% from 2010-11 to 2011-12).
4. Is chronic absence evenly distributed or concentrated in certain schools? Are there schools that are most troubled? Are there positive outliers?
What we saw:
• Here we refer to Tab B, the school summary. Chronic absence is not evenly distributed across schools. The level of chronic absenteeism (moderate and severe combined) varies widely across schools in this district, ranging from 1% up to 24%.
• The majority of the schools (14 out of 19) have chronic absence rates of 10% or below, but the remaining five stand out for their high levels of chronic absenteeism. Schools 12 and 14 have total chronic absence rates of 12%, schools 7 and 8 have total chronic absence rates of 14%, and school 10 has a staggering chronic absence rate of 24%-- amounting to 158 of its students. Only 51% of the students at school 10 have satisfactory attendance.
• There are a number of schools with total chronic absence rates that are impressively low. School 19 has a chronic absence rate of only 1%, or a total of three of its students. A full 87% of its students have satisfactory attendance.
5. What do we know about the schools where chronic absence levels are particularly high or particularly low?
What we saw:
• Continue referring to Tab B. School 10 is one of the larger elementary schools in the district, with 666 students. It also has high levels of poverty, with 91% of its students receiving free or reduced price lunch. Contrastingly, school 19 has only 285 students and has relatively low levels of poverty, with 46% of its students receiving free or reduced price lunch.
• While the above statistics may coincide with what we might expect of the schools with the highest and lowest levels of chronic absence, a number of other schools in the district do not follow these patterns, indicating that they deserve a closer look. For example, school 13 has high levels of poverty with 94% of its students receiving free or reduced price lunch; however, only 6% of its students are chronically absent. It is worth looking into the practices and programs in place at this school to learn how they are managing to keep their chronic absenteeism so low. Alternatively, some of the schools with the highest levels of chronic absenteeism are relatively small. Schools 8 and 14 have 228 and 265 students respectively, but have chronic absence levels comparable to schools three times their size. Perhaps there are identifiable opportunities for them to improve their attendance, given that the sizes of their student populations are relatively manageable.
• Understanding the underlying dynamics driving each school’s chronic absence numbers will require much more information than is captured in the DATT, but
looking at summary statistics can give an indication of which outliers demand attention.
6. Are certain sub-populations of students most affected by chronic absence?
What we saw:
• Now turn to Tab C, which breaks down chronic absence by race/ethnicity. In this district, Hispanic/Latino, African-American, and White students are all significantly affected by chronic absenteeism. The proportion of Hispanic/Latino students who are chronically absent is greater than that of the other groups, with 13% chronically absent compared to 9% and 8% of African-American and White students, respectively.
• Note that in this case study, we discuss racial/ethnic subgroups of students and students with and without special needs (below). The DATT also produces reports on chronic absence broken out by gender, by eligibility for free or reduced price lunch, and by English learner status. The data for all of these sub-populations of students should be similarly analyzed.
7. What does looking at both percentages and absolute numbers of students tell us about these sub-populations?
What we saw:
• Continue referring to Tab C. A first look at the percentages of each sub-population that have moderate or severe chronic absence might suggest that the group most affected by chronic absenteeism is American Indian/Alaskan Native students, 14% of whom are chronically absent. However, it is important to remember that for small sub-populations of students, looking at percentages can give a skewed perspective of the magnitude of the problem. Because there are only 37 American Indian/Alaskan Native students in the entire district, 14% represents only 5 chronically absent students.
• Additionally, while the proportion of Hispanic/Latino students who are chronically absent is greater than that of White students, looking at the number of students shows that a slightly greater absolute number of White students are affected by chronic absenteeism (299 compared to 284). Over 40% of all chronically absent students in the district are White (299/697 = .43). This district should direct attention toward its large groups of both White students and Hispanic/Latino students who are affected by chronic absenteeism.
8. Do attendance patterns differ for students with and without special needs?
What we saw:
• Turn to Tab D. Students with IEPs are more likely to be chronically absent than students without IEPs. 13% of students with IEPs have moderate or severe chronic absence, compared to 9% of students without IEPs. An additional 27% of
students with IEPs have at risk attendance, compared to 22% of students without IEPs. Given that there are a large number of students with special needs in this district (1463), 13% chronically absent represents a significant group of students (193).
• Greater rates of absence among students with IEPs are fairly typical across school districts.
9. What is the attendance status of individual children in the district?
What we saw:
• Finally, refer to Tab E. The DATT produces a comprehensive list of students in the district as well as their absence status (severe chronic, moderate chronic, at risk, and satisfactory). You can filter the list using the autofilter built into the tool to show only students with severe or moderate chronic absence to identify those who need support and targets for intervention. Tab E shows these filtered results.
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Is there anything else you see emerging from the data?
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