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Large databases vs. individual analysis: Two complimentary approaches in the study of education and learning

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Title: 1 Author: E. A-J Last modified by: E. A-J Created Date: 7/2/2008 6:20:38 AM Document presentation format: – PowerPoint PPT presentation

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Title: Large databases vs. individual analysis: Two complimentary approaches in the study of education and learning


1
Large databases vs. individual analysis Two
complimentary approaches in the study of
education and learning Esther
Adi-Japha School of Education, Bar-Ilan
University, Ramat-Gan, Israel.

2
Studying Effects of Early Education and Care on
Child Developmental Outcomes
  • Experimental studies random assignment model
    programs
  • Quasi-experimental studies treatment
    comparison groups large-scale publicly funded
    interventions
  • - Experimental Quasi experimental low
    income, at risk families
  • Correlational studies naturally occurring
    variations

3
Experimental studies
4
Quasi-experimental studies
5
Correlational studies
6
The NICHD Study of Early Child Care and Youth
Development
  • Large sample (n 1364) from 10 sites
  • Quality, amount, and type of child care measured
    from birth to kindergarten
  • Mothers and fathers observed and interviewed
  • Home observations
  • Cognitive, language, and social development
    assessed
  • Children studied from birth to age 18 years
    (began 1991)

7
Studying Effects of Early Education and Care on
Child Developmental Outcomes
Political/Policy issues What can children
benefit from high quality child care? Is child
care a risk factor for diminished cognitive and
social child outcomes?
8
Fundamentals of high-quality care
  • A high adult-child ratio
  • Small size group
  • Post-secondary training/education
  • Positive caregiver-child relationship
  • Well defined spaces
  • Well structured, well planned curricula

9
Age Staffchild ratio Maximum group size In
Canada (Province of Ontario) Under 18
months 13 10 18-23 months 15 15 2-5
years 18 16 In the United States, states
may set ratios and maximum group sizes, although
many do not set standards for group size.
Pennsylvania, for example Rec 6 and 15
months 13-4 6-8 24 months 14-5 8-10 3
years 16-7 18-21 14 5
years 18 24 16 7 years 112 24
10
On the NICHD SECCYD higher child care quality
predicted
  • Higher cognitive skills at 15, 24, 36, and 54
    months and in first grade
  • Higher academic skills at 36 and 54 months
  • Higher language skills at 36 54 months
  • Reduced behavior problems
  • Effects of child care quality were larger for
    children of low-income families. (derived EHS)

11
  • -Controlling for
  • site,
  • child ethnicity,
  • child gender,
  • maternal education,
  • mean income-to-needs ratio between 6 months and
    assessment age,
  • parenting quality between 6 months and assessment
    age,
  • partner status.
  • -Implementing complicated imputation scheme (MI)

12
Conclusion Positive effects for high quality
child care But what about the effect of other
aspects of child care e.g., quantity and type of
child care?
13
Quantity of care
  • Repeated separation from mother
  • Might affect infant and toddler attachment to
    mother, social and cognitive development
  • Long repeated separations,
  • Might increase stress and lead to behavior
    problems (unfriendly assertiveness, noncompliance
    and aggression)

14
Hours of Care
15
Type of care
  • Highly structured, school-like rather than
    home-like environment
  • Might lack in emotional support
  • Unstructured, home-like environment
  • Might lack in cognitive and social stimulation

16
NICHD SECCYD Results of 15 - 54 months
Exclusive maternal care did not predict
child outcomes, Higher quality child care was
related to advanced cognitive, language, and
preacademic outcomes at every age and better
socioemotional and peer outcomes at some ages.
More childcare hours predicted more behavior
problems and conflict, according to care
providers. More center-care time was related
to higher cognitive and language scores and more
problem and fewer prosocial behaviors, according
to care providers.
17
  • -Controlling for
  • site,
  • child ethnicity,
  • child gender,
  • maternal education,
  • mean income-to-needs ratio between 6 months and
    assessment age,
  • parenting quality between 6 and assessment age,
  • partner status.
  • -Implementing complicated imputation scheme (MI)
  • NICHD SECCYD, 2006, American Psychologist

18
Long term durable effects 6th grade
  • Higher quality care predicted higher vocabulary
    scores
  • More exposure to center care predicted more
    teacher-reported externalizing problems.
  • Controlling for preschool time invariant
    covariates included site, child ethnicity, child
    gender, maternal education, mean income-to-needs
    ratio between 6 and 54 months, parenting
    intercept, and slope from 6 to 54 months,
    maternal depressive symptoms intercept and slope
    from 6 to 54 months. The concurrent time-varying
    covariates from 54 months through sixth grade
    included income to-needs ratio, parenting,
    maternal depression observed school classroom
    quality, and hours per week of after-school care
    (set to 0 for 54 months).
  • Belsky et al., NICHD SECCYD, 2007, child
    development.

19
What are child care effect sizes - Overall,
modest to moderate Child care quality Modest
effects on all cognitive outcomes (.08 lt rp lt
.12) Modest to moderate on many socialemotional
outcomes (.08 lt rp lt .12) Long term effects on
academic scores (6th grade) Quantity of
care Negligible effect on cognitive
outcomes Modest negative effects on many
socialemotional outcomes (.09 lt rp lt .14) No
long term effects. Center care hours Modest
effects on all cognitive outcomes Modest negative
effects on many socialemotional
outcomes Negative long term effects on
social-emotional measures. Parenting Moderate-to
-large associations with all cognitive outcomes
(.17 lt rp lt .34 .40 lt d lt 1.23), many of
socialemotional outcomes (.08 lt rp lt .23 .33 lt
d lt .83) Parenting effects are a twice to three
times larger than the corresponding child care
effects
20
Are child care effects independent of parenting
quality? In contrast to previous (less
controlled) studies, the NICHD SECCYD did not
find support for 1. The differential prediction
hypothesis. 2. The compensation/lost-resources
hypothesis.
But what about non-linear associations ? The
role of secondary analysis!
21
Research Question Is there a difference between
high-quality and low-quality parenting
outcomes that depends on quantity of care? Is
such a difference non-linear?
22
Study Variables Quantity of care - Predominantly
maternal care 0-10 hr/week on average 0-36
months - Medium amount of child care 10-32
hr/week on average 0-36 months - Higher amounts
of child care Parenting quality low-quality
and high-quality parenting above and below
median Outcomes Cognitive outcomes at 36 months
Prof. Pnina Klien
23
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24
  • -Controlling for
  • child ethnicity,
  • child gender,
  • maternal education,
  • mean income-to-needs ratio between 6 months and
    assessment age,
  • parenting quality between 6 and assessment age,
  • partner status.
  • -Implementing complicated imputation scheme (MI)
  • - Results remained with different cut-offs, and
    with childcare hours as a continuous variable.

25
Conclusions
  • There is an optimum of child care hours, in which
    the association between parenting quality and
    outcomes is maximal associations do not decrease
    linearly with the amount of child care.
  • Sharing databases is highly important for
    studying in-depth the results, highlighting
    un-expected effects.

26
Can individual differences be studied using large
databases? - well, probably not
From the NICHD SECCYD data contract
C. To avoid inadvertent disclosure of persons,
families, households, or care providers
information 2. In no case should the total
figure for a row or column of a cross-tabulation
be fewer than three. 3. In no case should a
quantity figure be based upon fewer than three
cases. 4. In no case should a quantity figure be
published if one case contributes more than 60
percent of the amount. 5. In no case should data
on an identifiable case, nor any of the kinds of
data listed in preceding items 1-3, be derivable
through subtraction or other calculation from the
combination of tables released.
27
  • Why should we study individuals data?
  • Group data may mask abrupt changes in the
    individuals course of development.
  • These changes may/may-not-be at different times
    for different individuals.
  • I shall Illustrate this point using a procedural
    learning task

28
What is procedural learning?
  • Procedural learning refers to the acquisition of
    new behaviors through a process of repetitive
    practice (e.g., writing, driving, playing a
    musical instrument etc..).
  • Laboratory- motor learning tasks are often used
    as a model for procedural learning.

29
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30
Motor learning
Brashes- Krug, Shadmehr Bizzi, Nature, 1996
Karni et al., PNAS, 1998
Sosnik et al., Exp. Brain Res. 2004
31
Three stages in motor learning
  • Fast learning gains (in speed and accuracy)
    accrued throughout the training session.
  • Memory consolidation gains that appear in the
    hours or days after termination of training.
  • Retention/Slow learning retention/further
    improvement that appear some weeks following
    termination of practice.

32
23
21
19
Three stages in motor learning
17
15
Performance ( seq./30sec)
13
11
9
7
5
3
1
0.8
9 year-olds
12 year-olds
0.6
17 year-olds
errors
0.4
0.2
0
training session
24 h
48 h
6 wks
33
Interference
  • Brashes- Krug, Shadmehr Bizzi, Nature, 1996

34
25
no interference
20
interference
15
Performance ( seq./30sec)
10
5
9 yrs
12 yrs
17 yrs
0
1
errors
0.5
0
init
end
24hr post
Dorfberger, Adi-Japha, Karni, 2007, Plos one
35
Changes may/may-not-be at different times for
different individuals
Consolidation gains - 24 hours after termination
of training - sleep dependent.
36
What happened within the training session?
37
Var(moving window(Data - Power-law). Three
phases (a) Low var. (b) High var. (c) Low
var. Performance gt Power-law extrapolation(1st
Low var.) Adi-Japha et al., 2008, JEP LMC
38
Two performance phases within the training session
  • Within/between sequence errors
  • Latency to respond

39
  • Final conclusions
  • For the benefit of all, (large) databases need to
    be shared
  • Large educational databases are limited do not
    allow the study individual behaviors

40
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