Ashley Comer Amy Doerfler Lyssa Fisher-Rogers Travis Morris Gloria Pagan EDFN 508 July 8, 2009

 Prior to analyzing the Seattle school data, our hypothesis is directional.  Based on current research and personal observations as educators, we are curious to discover whether or not a relationship exists between transience and the academic achievement of students, based on GPA and ITBS math scores.  The null hypothesis states that relocating homes does not affect student achievement, nor does the length of time spent living with a specific area.

In order to discover a correlation we analyzed the following variables form the Seattle middle school data set for sixth grade students relevant to school years 2000 and 2001:  Second Semester GPA for  Iowa Test of Basic Skills (ITBS) for Mathematics, Reading, and Language Arts  Living in the same home as the previous year  Length of time living in Seattle  Gender

 Merriam Webster defines transience as “passing through or by a place with only a brief stay or sojourn.”  Our definition refers to the movement of any students in and out of the given school district.  This same term also applies to students who are living within the same Seattle district but may have changed schools prior or during their sixth grade academic school year.

 Numeric Variable  Mean Score:  Median Score: 42  Mode: 42  Range: 98  Inter-quartile Range: 25  Standard Deviation:  Standard Error of Mean:.906  95% Confidence Interval:

 Numeric Variable  Mean Score:  Median Score: 39  Bi-Modal, 1 and 38  Range: 89  Inter-quartile Range: 27  Standard Deviation:  Standard Error of Mean:.85  95% Confidence Interval:

 Numeric Variable  Mean: 39.7  Median: 40  Mode: 41  Range: 98  Standard Deviation: 19.3  Standard Error of Mean:.89  Inter-quartile Range: 25  95% Confidence Interval: to 41.51

 Numeric Varible  Mean: 2.6  Median: 2.64  Mode: 4  Range: 4  Standard Error of Mean:.036  Standard Deviation:.85  Inter-quartile Range: 1.18  95% Confidence Interval:

 Ordinal Variable  Median: 4 (11-20 Years)  Mode: 4  Range: 4  Inter-quartile Range: 2 1=2 Years or Less 2=3 to 5 Years 3=6 to 10 Years 4=11 to 20 Years 5=More than 20 Years

 Nominal variable  Mode: 1.24  Standard Error of Proportion:.02  95% Confidence Interval:.72 to.80

 We found that concurrent research shows that by and large transient pupils are underperforming compared to non-transient students by as much as 50%. (Demie, 2002)  The sample consisted of 2,403 students, which is considerably larger than the sample we examined from the Seattle Middle School data set.  The researchers studied measures of student background such as name, date of birth, sex, meals status (free/reduced), ethnic background, date of admission or mobility and levels of fluency in English.

 We were interested in the “Pupil Mobility” research table that showed the comparative performance of mobile and non-mobile, or “stable”, students.  This table shows a positive correlation between achievement and the length of time a student spent in the same school. We found similar correlations in the Seattle-based data as stated in the current research.

Correlations GPA 2nd semester th grade math ITBS score GPA 2nd semester 00-01Pearson Correlation ** Sig. (2-tailed).000 N th grade math ITBS scorePearson Correlation.400 ** Sig. (2-tailed).000 N **. Correlation is significant at the 0.01 level (2-tailed).

Dependent Variable:6th grade math ITBS score Source Type III Sum of Squaresdf Mean SquareFSig. Corrected Model a Intercept hmsame gender hmsame * gender Error Total Corrected Total a. R Squared =.017 (Adjusted R Squared =.009) Do you live in the same home as last school year? * gender2 Dependent Variable:6th grade math ITBS score Living in the Same home as Last Yeargender2MeanStd. Error 95% Confidence Interval Lower BoundUpper Bound YesMale Female NoMale Female

Tests of Between-Subjects Effects Dependent Variable: GPA 2nd semester Source Type III Sum of SquaresdfMean SquareFSig. Corrected Model a Intercept hmsame gender hmsame * gender Error Total Corrected Total a. R Squared =.056 (Adjusted R Squared =.049) Do you live in the same home as last school year? * gender2 Dependent Variable: GPA 2nd semester Living in Same Home as Last Yeargender2MeanStd. Error 95% Confidence Interval Lower BoundUpper Bound YesMale Female NoMale Female

Tests of Between-Subjects Effects Dependent Variable: GPA 2nd semester Source Type III Sum of SquaresdfMean SquareFSig. Corrected Model a Intercept famsea gender famsea * gender Error Total Corrected Total a. R Squared =.044 (Adjusted R Squared =.022) Descriptive Statistics Dependent Variable: GPA 2nd semester How long has your family lived in Seattle?gender2MeanStd. DeviationN 2 years of lessMale Female Total to 5 yearsMale Female Total to 10 yearsMale Female Total to 20 yearsMale Female Total More than 20 yearsMale Female Total TotalMale Female Total

Dependent Variable:6th grade math ITBS score Source Type III Sum of SquaresdfMean SquareFSig. Corrected Model a Intercept famsea gender famsea * gender Error Total Corrected Total a. R Squared =.057 (Adjusted R Squared =.032) Descriptive Statistics Dependent Variable:6th grade math ITBS score How long has your family lived in Seattle?gender2MeanStd. DeviationN 2 years of lessMale Female Total to 5 yearsMale Female Total to 10 yearsMale Female Total to 20 yearsMale Female Total More than 20 yearsMale Female Total TotalMale Female Total

 The Seattle Middle School data identifies that a strong relationship exists between the transience of student populations and their academic achievement.  However, utilizing two-way variance analyses, the data indicates that mobility within a school district has a greater main effect than mobility among districts.  In fact, transferring among districts tends to have a converse effect on student population  In-migrant populations perform better both on ITBS math assessments and on the second semester GPA than students whose families have resided longer within the district.