how does transience affect academic performance?
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How Does Transience Affect Academic Performance?
Ashley ComerAmy Doerfler
Lyssa Fisher-RogersTravis MorrisGloria Pagan
EDFN 508July 8, 2009
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.
The VariablesIn order to discover a correlation we analyzed thefollowing 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
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.
6th Grade 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
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
6th Grade 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
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
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 Less2=3 to 5 Years3=6 to 10 Years4=11 to 20 Years5=More than 20 Years
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
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.
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.
Narrowing our Focus…Correlations
GPA 2nd
semester 00-01
6th grade math
ITBS score
GPA 2nd semester 00-01 Pearson Correlation 1.000 .400**
Sig. (2-tailed) .000
N 552.000 432
6th grade math ITBS score Pearson Correlation .400** 1.000
Sig. (2-tailed) .000
N 432 472.000
**. Correlation is significant at the 0.01 level (2-tailed).
Living in the Same Home as Last School Year: Two-Way ANOVA (Math)
Dependent Variable:6th grade math
ITBS score
Source
Type III
Sum of
Squares df
Mean
Square F Sig.
Corrected Model 2275.205a 3 758.402 2.130 .096
Intercept365473.796 1
365473.79
6
1026.68
1.000
hmsame 1965.711 1 1965.711 5.522 .019
gender2 75.599 1 75.599 .212 .645
hmsame *
gender2213.572 1 213.572 .600 .439
Error 128507.326 361 355.976
Total 762853.000 365
Corrected Total 130782.532 364
a. R Squared = .017 (Adjusted R Squared = .009)3. 7. 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 Year gender2 Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
Yes Male 43.186 1.567 40.105 46.267
Female 42.405 1.551 39.356 45.455
No Male 35.410 3.021 29.469 41.352
Female 38.485 3.284 32.026 44.944
Living in the Same Home as Last School Year: Two-Way ANOVA (GPA)
Tests of Between-Subjects Effects
Dependent Variable: GPA 2nd semester 00-01
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 14.070a 3 4.690 8.167 .000
Intercept 2087.377 1 2087.377 3634.860 .000
hmsame 2.027 1 2.027 3.530 .061
gender2 4.781 1 4.781 8.325 .004
hmsame * gender2 1.309 1 1.309 2.279 .132
Error 237.746 414 .574
Total 3260.977 418
Corrected Total 251.816 417
a. R Squared = .056 (Adjusted R Squared = .049)
3. 7. Do you live in the same home as last school year? * gender2
Dependent Variable: GPA 2nd semester 00-01
Living in Same Home as
Last Year gender2 Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
Yes Male 2.916 .060 2.797 3.035
Female 2.531 .059 2.414 2.648
No Male 2.619 .105 2.413 2.826
Female 2.499 .112 2.279 2.718
How long has your family lived in the same home: Two-way ANOVA (GPA)
Tests of Between-Subjects Effects
Dependent Variable: GPA 2nd semester 00-01
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 10.526a 9 1.170 1.983 .040
Intercept 2345.961 1 2345.961 3978.141 .000
famsea 1.664 4 .416 .705 .589
gender2 8.113 1 8.113 13.758 .000
famsea * gender2 1.236 4 .309 .524 .718
Error 230.578 391 .590
Total 3111.713 401
Corrected Total 241.103 400
a. R Squared = .044 (Adjusted R Squared = .022)
Descriptive Statistics
Dependent Variable: GPA 2nd semester 00-01
How long has your
family lived in
Seattle? gender2 Mean Std. Deviation N
2 years of less Male 3.0630 .89161 20
Female 2.4700 .74318 17
Total 2.7905 .86879 37
3 to 5 years Male 2.8939 .73124 23
Female 2.5881 .72982 27
Total 2.7288 .73918 50
6 to 10 years Male 2.6490 .89161 42
Female 2.4880 .70442 40
Total 2.5705 .80490 82
11 to 20 years Male 2.8295 .79700 62
Female 2.5852 .69628 62
Total 2.7073 .75532 124
More than 20 years Male 2.7849 .76996 57
Female 2.5094 .74241 51
Total 2.6548 .76610 108
Total Male 2.8100 .81246 204
Female 2.5363 .71284 197
Total 2.6756 .77638 401
How long has your family lived in the same home: Two-way ANOVA (Math)
Dependent Variable:6th grade math ITBS score
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 6776.526a 9 752.947 2.273 .018
Intercept 381954.217 1 381954.217 1152.820 .000
famsea 5806.539 4 1451.635 4.381 .002
gender2 53.443 1 53.443 .161 .688
famsea * gender2 867.879 4 216.970 .655 .624
Error 112649.328 340 331.322
Total 724207.000 350
Corrected Total 119425.854 349
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? gender2 Mean Std. Deviation N
2 years of less Male 43.5556 12.92392 9
Female 46.5000 20.28820 10
Total 45.1053 16.80243 19
3 to 5 years Male 33.8095 20.02903 21
Female 27.5789 17.63619 19
Total 30.8500 18.95278 40
6 to 10 years Male 42.9744 16.30868 39
Female 46.0000 16.57475 37
Total 44.4474 16.39951 76
11 to 20 years Male 42.5636 13.49727 55
Female 43.3220 20.27351 59
Total 42.9561 17.26749 114
More than 20 years Male 39.4364 19.64006 55
Female 43.7826 20.80803 46
Total 41.4158 20.19568 101
Total Male 40.7151 17.04002 179
Female 42.4620 19.92257 171
Total 41.5686 18.49850 350
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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