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How Does Transience Affect Academic Performance?

How Does Transience Affect Academic Performance?. Ashley Comer Amy Doerfler Lyssa Fisher-Rogers Travis Morris Gloria Pagan EDFN 508 July 8 , 2009. Our Research Question. Prior to analyzing the Seattle school data, our hypothesis is directional.

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How Does Transience Affect Academic Performance?

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  1. How Does Transience Affect Academic Performance? Ashley Comer Amy Doerfler Lyssa Fisher-Rogers Travis Morris Gloria Pagan EDFN 508 July 8, 2009

  2. Our Research Question • 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.

  3. The Variables 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 2000- 2001 • 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

  4. Definition of Transience • 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.

  5. 6thGrade Language ITBS Score • Numeric Variable • Mean Score: 41.23 • Median Score: 42 • Mode: 42 • Range: 98 • Inter-quartile Range: 25 • Standard Deviation: 19.78 • Standard Error of Mean: .906 • 95% Confidence Interval: 41.23-43.042

  6. 6th Grade Reading ITBS Score • Numeric Variable • Mean Score: 39.19 • Median Score: 39 • Bi-Modal, 1 and 38 • Range: 89 • Inter-quartile Range: 27 • Standard Deviation: 18.632 • Standard Error of Mean: .85 • 95% Confidence Interval: 37.49-40.89

  7. 6thGrade Math ITBS Score • 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: 37.95 to 41.51

  8. 2nd Semester GPA 00-01 • 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: 2.53-2.68

  9. How Long Has Your Family Lived in Seattle? • 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

  10. Do You Live in the Same Home as Last Year? • Nominal variable • Mode: 1.24 • Standard Error of Proportion: .02 • 95% Confidence Interval: .72 to .80

  11. Current Research • 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.

  12. Current Research, Cont. • 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.

  13. Narrowing our Focus…

  14. Living in the Same Home as Last School Year: Two-Way ANOVA (Math)

  15. Living in the Same Home as Last School Year: Two-Way ANOVA (Math)

  16. Living in the Same Home as Last School Year: Two-Way ANOVA (GPA)

  17. Living in the Same Home as Last School Year: Two-Way ANOVA (GPA)

  18. How long has your family lived in the same home: Two-way ANOVA (GPA)

  19. How long has your family lived in the same home: Two-way ANOVA (GPA)

  20. How long has your family lived in the same home: Two-way ANOVA (Math)

  21. How long has your family lived in the same home: Two-way ANOVA (Math)

  22. In conclusion… • 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.

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