early childhood longitudinal study min-jong, youn steve maczuga
TRANSCRIPT
EarlyChildhood
Longitudinal Study
Min-Jong, YounSteve Maczuga
ECLS Program
• ECLS-B birth cohort: birth thru K
• ECLS-K kindergarten cohort: K thru 8th grade
ECLS-K
• Information on young children• Data collections: K-8th grade• More attention to parents and the
family (e.g., non-parental care, out of school experiences, parental in-volvement)
• Information on children’s cognitive/socioemotional status/health condi-tion
Strengths of the ECLS-K De-sign
• Children’s assessment at the start of school
• Fall and spring assessment in kinder-garten and first grade
• Several time points• Assessments not limited to children’s
academic achievement• Information on multiple environments
and from multiple sources
Focus Area
• School readiness• Transitions into kindergarten and ele-
mentary school and from elementary to middle school
• Relationship between early school ex-periences and later school performance
• Growth in cognitive, social, and physi-cal development from childhood through adolescence
Core Data Collection
• Assessments• Student questionnaires• Parent interviews• Teacher questionnaires (A:classroom
instruction/B:views on school)• School administrator questionnaires• Student records abstracts• School facilities checklist
ECLS-K ComponentsChild Parent Teacher School
Cognitive Parent and child demo-
graphics
Teacher back-ground
School demo-graphics
Socioemotional status
Child and fam-ily health
Classroom en-vironment
School climate
Physical Family charac-teristics
School climate School pro-grams
Psychomotor Parent-child in-teractions
Student profile Educational goals and ob-
jectives
Data Collection
Kinder-garten
First Grade Third Grade
Fifth grade
Eighth Grade
Fall 1998 Fall 1999(30%)
Spring 1999 Spring 2000(refreshed)
Spring 2002 Spring 2004
Spring 2007
Sample Sizes Over TimeData Collec-tion
Direct Child Assessment
Parent Inter-view
Fall K 19,173 18,097
Spring K 19,967 18,950
Fall First 5,291(30%) 5.071
Spring First 16,727 15,626
Spring Third 14,470 13,489
Spring Fifth 11,346 10,996
Spring Eighth 9,296 8,755
SampleSpring K Spring 1st Spring 3rd Spring 5th
Mean num-ber of chil-dren per school
13 8 5 5
Mean num-ber of chil-dren per teacher
6 3 2 2
*Based on reports from the children’s reading teach-ers
Sample Characteristics
• Nationally representative of kinder-gartens, Kindergarteners, and Kinder-garten teachers
• Nationally representative of first-graders• Not-representative of 3rd, 5th, and 8th
graders• Oversampling of private schools and
private school children/Asian/Pacific is-landers
ECLS-K Assessment
• Cognitive
• Socioemotional
• Physical
The Assessment
• Cognitive: Reading (K-8)Math (K-8)General Knowledge (K-1)Science(3,5,8)
* All assessment are recalibrated using IRT
Reading AssessmentK-8 K-5 K-3 K -1 Level1: Letter recognition
Level2:Beginning sounds
Level3: Ending sounds
Level4: Sight words
Level5:Words in context
Level6:Literal inference
Level7:Extrapolation
Level8:Evaluation
Level9:Evaluating Non-fiction
Level10:Evaluating complex syn-tax
Math AssessmentK-8 K-3 K-1 Level1:Number and shape
Level2:Relative size
Level3:Ordinality, sequence
Level4: Addition and subtraction
Level5:Multiplicaiton and division
Level6:Place value
Level7:Rate and measurement
Level8:Fractions
Level9:Area and Volume
Language Minority Children
• Those who fail English oral language developmental scale(OLDS) do not take Reading and General knowledge tests
• But they take Spanish Mathematics, Psychomotor, Height, and Weight
Identifying Language Minority Chil-dren
1)Students show home language was not English
2)Teachers were asked about child’s language use in and out of the class-room
3)Children were administered the Oral Language Development Scale(OLDS)
Indirect Assessment
Academic Rating Scale(ARS) -Teacher report on children’s cogni-
tive knowledge and skills
Social Rating Scale(SRS) -Teacher and parent report on chil-
dren’s social skills
Indirect Assessment
Socioemotional• Social skills• Approaches to Learning• Externalizing and Internalizing prob-
lem• Self-Control• Self-Concept (3,5,8)
Physical and Motor Specifications
• Physical: Height/Weight/Body Mass Index(BMI)
• Motor (Fall kindergarten only) -Fine Motor: -Copy basic figures/con-
structs wooden blocks -Gross Motor: Balance on each foot,
Hop on one foot, Skip, Walk back-ward
Practical Issues
• Naming variable
• Change of school
• Weighting
Naming of Variables
Level of variable(assessment, parent, student, teacher, school)
+Round of data collection (1-6)
ExamplesC1R3MSCL C2R3MSCLC4R3RSCLC6R3RSCLWKSESL/W1SESL/W3SESL/W5SESLP2HEMPLS4TEST
ECLS-K variable naming Code Variable Exp
A/B Teacher questionnaire
C Child assessment Combined with R:extrapolation
K School facility check list
P Parent interview
R Child demographic e.g., region
S School administrator question-naire
T Teacher questionnaire student scores
Timing
Round of data explanation
1 = fall kindergarten2 = spring kinder-garten3 = fall first grade4 = spring first grade5 = spring third grade6 = spring fifth grade
Number is used to indi-cate in which round of data collection the vari-able was obtained
K=kindergarten1=first grade3=third grade5=fifth grade
Variables beginning with “W”(e.g., wksesl)
Composite variables
• Users may not have all necessary data to create composite
e.g.,
Child characteristicsChild care informationParent characteristicsHousehold characteristicsClassroom characteristicsSchool characteristics
Race, gender, BMI, SESSES=education, household, and income (40% imputed)
Example
• C1R3MSCL • C2R3MSCL• C4R3RSCL• C6R3RSCL• WKSESL/W1SESL/W3SESL/W5SESL• P2HEMPL• S4TEST
Changed schools or teach-ers
• Variables that identify children who changed schools or teachers
Example:R4R2SCHG=changed schools between
rounds 2and 4R4R2TCHG=changed teachers between
round 2 and 4
-Drop cases-
Missing data values
-1 not applicable, including legitimate skips-7 Refused-8 Don’t know -9 Not Ascertained(blank) System missing
*Be cautious with “-1” which may not be missing
What is the Difference Between Weighted and Unweighted Data
• With unweighted data, each case is counted equally.
• Unweighted data represent only those in the sample who provide data.
• With weighted data, each case is counted relative to its representation in the population.
• Weights allow analyses that represent the target population.
How are Weights Used?
• Dataset with 5 cases. • Value 4 2 1 5 2• Weight 1 2 4 1 2• Sample mean (4+2+1+5+2) = 2.8• Weighted mean (4*1) + (2*2) + (1*4)
+ (5*1) + (2*2)/sum of weights = (4 + 4 + 4 + 5 + 4)/10 = 2.1
Weighting
1)Level of Analysis: child, teacher, or school
2)Round of data: cross-sectional or longitudinal(Choose time period: e.g., k thru 3rd grade)
3)Source of data: Child assessment, parent interview, and/or teacher questionnaires
Weighting
The first letter element in a weight variable name indicates the level of analyses
• School level analyses: “S”
• Teacher level analyses: “B”
• Child level analyses (cross-sectional/longitudinal): “C”
• Except base year child level analyses (longitudinal): “BY” –e.g., BYCOMW0=Child assessment data from fall-AND spring-kindergarten in conjunction with one or more rounds of parent and/or teacher base year data
Data round
The second element in a weight variable name in-dicates the round of data
Cross sectional data indicates with single number: 123456
Longitudinal analyses include two or more num-bers
“45”for round 4 and 5“124” for rounds 1,2, and 4“1_6F” ‘for rounds 1,2,3,4,5,6 (F=full sample)“1_5S” for rounds 1,2,4,5 (S=subsample)
Source of the Data
• Child assessments (alone or in conjunction with any combination of a limited set of child charac-teristics, e.g., age, sex, race/ethnicity) have a “C”
• Parent Interview: “P”
• Child/parent/teacher have a “CPT”
• In 5th grade “CPT” is followed by either “R”,”M”,”S” for teachers
Examples:
C23PWO
C- for the child-level analysis
23-for analysis of data from rounds 2 and 3
P for analysis of parent interview data
Example
• C6CPTM0“C” for child-level analysis“6 for analysis of data from round 6“CPTM” for analysis of child, parent,
and math teacher
Example
C1_6FC0Round 1, 2, 4,5, and 6 assessment
data
C1_6FP0
Strength of ECLS-K
1)Rich information on children and family
2)Health condition
3)Frequent time points
4)Assessment
Help
Order free CDhttp://www.edpubs.gov/ProductCatalog.aspx?KeyWordSearch=&TypeofSearch=exact&searchterm=ECLS-K
Chapter 7 in the ECLS-K, 5th Grade User’s Guide has Tables 7-15 and 7-16 that describe the differences in the public and restricted datasets. The User’s Guide can be found online at: http://sodapop.pop.psu.edu/codebooks/ecls/k5userpart2.pdf
Weighting: ECLS-K report chapter 9Assessment: ECLS-K report chapter 3
Help
• Here’s a short explanation from the NCES: http://nces.ed.gov/ecls/kinderfaq.asp?faq=1
• Weightinghttp://help.pop.psu.edu/data-collections/early-childhood-longitudinal-study-ecls/Working%20with%20the%20ECLS-K%20Data.ppt/view
Weighting and Complex Sample Design Help Pages
• http://help.pop.psu.edu/help-by-statistical-method/weighting/working-with-sampling-weights
• On the above page, the last two links are specific to the ECLS datasets and contain code examples and descriptions of complex sample design.