Early Childhood Longitudinal Study Min-Jong, Youn Steve Maczuga.

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.