Student Mobility and Stability in CT

Transcription

1 Student Mobility and Stability in CT A Report by Christine Mwaturura, Research Assistant, Partnership for Strong Communities Definitions Contrary to what many people assume, the mobility rate and the stability rate do not add up to 100%. The following definitions will illustrate why this is. While there are varied definitions of student mobility, in this memo I shall use the definition that I found to be most common in my readings. Student mobility rate: the number of students who leave or enter a school (or in the case of a district, the district), for reasons other than those that are due to the design of the school program e.g. matriculating between elementary, middle school and high school; graduating from high school, in one academic year as a percentage of the total enrollment for that academic year. This is also known as the joiners plus leavers (JPL) formula. (Entires t + Withdrawals t ) *Total Enrollment t x 100 Student stability rate: the number of students who are enrolled at a school for an entire academic year as a percentage of total enrollment for that academic year. Students Enrolled for Entire Academic Year t Total Enrollment t t = academic year t x 100 It is therefore possible for a school to have a high stability rate and also have a high mobility rate. Say for instance that we have a school with a total enrollment of 100 students and that 90 of those students stay enrolled in the school for the entire year, therefore the stability rate is 90%. So during the course of that year there were 10 spaces that at sometime became vacant. 10 vacant spaces means that there had to be 10 withdrawals, and if those 10 spaces were filled again that would be 10 new entries: so the mobility rate would be 20%. If those 10 seats were subsequently vacated again and then filled again, the mobility rate would be 40%, and so on and so forth. From this example you can see that the mobility rate gives an indication of how frequently spaces are vacated and filled, whereas the stability rate does not reflect this. 100% stability rate (which is not the mobility rate) tells us the percentage of the student population that is mobile. *NB- I found that the denominator: total enrollment, is not strictly defined. In some calculations the enrollment numbers at the beginning of the school year are used; in other instances, e.g. the New London school district, the average enrollment numbers over the course of the year are used in their calculations. Why Mobility Matters Many studies have been done exploring how mobility affects achievement, and many have found that highly transient students tend to do worse in school, have a higher likelihood to be retained in a grade and are more likely to not graduate; Rumberger s study (as cited in Lovell & Isaacs, 2008) found that school and residential changes can reduce the chances that a student will graduate by more than 50 percent. (p.1) Rumberger and Russell s, and the General Accounting Office s studies (as cited in Lovell & Isaacs, 2008) found that students who had transferred schools at least twice were half as likely to be proficient in reading as their stable peers [M]obile third grade students [were] nearly twice as likely to perform below grade level in math [in comparison with their stable peers]. (p.1) Behavioral problems are also associated with mobile students. Mobile students are more likely to either exhibit violent behavior or are more withdrawn than stable students. Rumberger s study (as cited in Lovell & Isaacs,

2 2008) found that students who change elementary schools several times are 20% more likely to exhibit violent behavior in high school. (p.1) Mobility also affects stable students. When a new student joins a class, valuable lesson time is usually lost when teachers have to integrate the new student so much that, as Kerbow s study found (as cited in Rhodes, 2005), in highly mobile schools lessons often do not progress beyond elemental levels of knowledge or skill even stable students in highly mobile elementary schools are the equivalent of one entire year behind their peers in more stable schools by the end of the sixth grade. (p.3) Another factor which exacerbates this problem is that low-performing urban schools often have a lot of pressure to improve scores on state required tests that a lot of class time is taken up by review and preparation for the test rather than covering new material. (Rhodes, 2005, p.3) The Situation in CT Currently, CT school districts track and report student stability rates for elementary and middle school students to the CT State Department of Education (SDE) in the district Strategic School Profiles: [t]he % of students [above entry grade] enrolled on October 1 who were also enrolled in the school the previous year [not including students who enrolled in the middle of the school year] Elementary and middle school students only are reported. (SDE, n.d., Student Data section para. 11) Of the 14 school districts that I focused on, many did not track mobility rates for their own records (others were too busy or were short of staff to look into it). Given that school districts already have a multitude of requirements to report to the state, have limited funding, staff and resources- it is understandable why most do not take up this practice of tracking mobility rates in their districts. Because the information from the state is limiting, I contacted Jack Dougherty: Professor and Director of the Educational Studies Program at Trinity College, and Dr. Marc Porter Magee: the Director of Communication and Research at ConnCAN, to find out if they had any data on student mobility rates in CT. They have also experienced the same difficulties that I had in trying to get this data. To meaningfully interpret the stability rate, Prof. Dougherty suggested that I subtract the stability rate from 100% and use that number as a benchmark for the minimum mobility rate i.e. mobility rate ( stability rate). Also, as is mentioned in Table s and 4 Year Average ( to ) Stability Rates for CT School Districts (Focus Group) Stability Rate (%) 4 Year Avrg. (03-04 to 06-07) Stability Rate (%) 4 Yr. Avrg. Stability Rate District Bridgeport Danbury Hartford Meriden Middletown New Britain New Haven New London Norwalk Norwich Stamford Torrington Waterbury Windham Notes- Table created from data in the SDE Strategic School Profiles: District Data 2

3 Rhodes article (2005), stability rates are sometimes interpreted such that [a] high mobility school is one in which 20% or more of the students are mobile [i.e. 100% stability rate 20%]. Schools with 30% or more of such students are considered very high mobility schools. (p.1) Of the districts that I focused on, Waterbury had the lowest stability rate in (70.5%) as well as the lowest 4 year average (69%). Torrington had the highest stability rate (90.8%) in as well as the highest 4 year average (90.1%). Table 2 Values for for and 4 Year Average, by DRG and by District 4 Yr. Avrg. District DRG Torrington G Middletown G Norwalk H Danbury H Stamford H Meriden H Norwich H Bridgeport I New London I Windham I Hartford I New Britain I New Haven I Waterbury I Figure 1 The value of 100% - for and the 4 year average, generally increases as DRG goes from group G to I indicating that poorer districts suffer from more instability. 100% - s for and 4 Yr. Avrg. by District and by DRG % Yr. Avrg. Stability Rate 0 G - Torrington G - Middletown H - Norwalk H - Danbury H - Stamford H - Meriden H - Norwich I - Bridgeport London I - Windham I - Hartford Britain Haven I - Waterbury District and DRG 3

4 Using the aforementioned interpretation of the stability rate, in the school year, 5 of the 14 school districts (Hartford, Meriden, New Britain, New Haven and Norwich) fell into the high mobility district category. Windham came very close to falling into this category as well ( stability rate = 18.2%). In the same year Waterbury fell into the very high mobility district category. The 4 year average stability rates show that 5 of the 14 districts (Hartford, Meriden, New Britain, New haven and Windham) can be classified as high mobility districts. New London ( stability rate = 18.6%) and Norwich ( stability rate = 19.4%) come very close to also being classified as high mobility districts. Waterbury is considered a very high mobility district. Poorer school districts disproportionately experience lower stability rates. We can see this by comparing the districts using the District Reference Groups (DRGs). The SDE developed the DRGs to group school districts, into 9 groups, with similar characteristics based on socioeconomic status (SES) indicators e.g. median family income, and indicators of need e.g. % of children living in single parent homes. The groups are labeled from A-I with group A characterized as the most affluent districts and group I as the poorest districts. (Prowda, 2006, p.2). Looking at the 100% - 4 year average value, all districts in DRG I (except for Bridgeport) can be classified as high mobility districts; Waterbury is classified as a very high mobility district. 2 out of 5 districts in DRG H (Meriden and Norwich) can be classified as high mobility districts. Other Data Azcoitia s and Kerbow s studies (as cited in Rhodes, 2005) found that highly mobile parents tend to make decisions to move their children within a circuit of closely located schools, often within a limited geographical area of poverty. (p. 4) Data for Bridgeport and Norwich give the numbers of students who transferred schools within the same district. Mulford: Supervisor of Pupil Services and Student Assignments; number of students who transferred schools at least once within the Bridgeport district ,690 (17.4% of total # of students enrolled in Bridgeport district) ,571 (16.4%) ,701 (16.6%) ,665 (16.4%) Norwich data was provided by Donna Viola: Student Database Administrator; number of students who transferred schools at least once within the Norwich district (13.3% of total # of students enrolled in Norwich district) (10.8%) (11.6%) (12%) New London data was provided by Alison Burdick: District Data Facilitator. The New London Mobility Report has information on the elementary schools. The report stated that the most realistic account of mobility is after the Sept. 1 st Sept. 15 th enrollment of new students. And that outside of the first 2 weeks of school, January maintained the highest mobility rate in 3 out of [the 4 elementary schools.] Mobility rate for elementary schools in (after Sept. 1 st Sept. 15 th period) = (Entries + Withdrawals) = Enrollment ( ) 1,406.5 x 100 = 32.91% Bridgeport data was provided by Michael 4

5 The report on the high school, Who is at New London High School? (February 2007) reports that 89 new students started attending New London High School since the first day of school in Sept. 2006, that 152 had withdrawn during the same time period, and that there were 768 students enrolled. Therefore mobility rate = 31.38%. According to Rhodes (2005), in recent studies done in England a mobility rate, using a JPL formula, above 20% is considered high mobility and a rate which is above 30% is considered very high mobility (p.7). So by these terms New London elementary schools and the New London High School would all be considered very high mobility schools. Concluding Remarks 42% of high mobility cases are linked to factors involving problems with the schools. Most cases of mobility, 58%, are related to residential moves (Kerbow [as cited in Rhodes, 2005, p.1] ). Solving housing related issues, therefore, can mitigate the mobility problem. Pockets of poverty which keep mobile students traveling in circuits of low-performing schools need to be dissolved- this could be achieved by creating more affordable housing in other areas to allow low income families to live else where. Getting rid of these poverty pockets could also create more pleasant/ safer neighborhoods which in turn could lessen the incentive for families to move else where. A general increase in the affordable housing stock would mean that more families would be able to stay in their homes and not have to move because of housing costs. References Connecticut State Department of Education. (n.d.). Terms and definitions: Strategic school profiles to Retrieved July 30, 2008, from public/cedar/profiles/ssp_help/terms_93-07.pdf Lovell, P., & Isaacs, J. (2008). The impact of the mortgage crisis on children. First Focus. Prowda, P. (2006). Research bulletin: District reference groups, Retrieved July 29, 2008, from public/cedar/databulletins/ db_drg_06_2006.pdf Rhodes, V. (2005). Kids on the move: The effects of student mobility on NCLB school accountability ratings. Penn Graduate School of Education Perspective in Urban Education, 3(3),