Poverty, Proficiency, and the
Common Core State Standards
2014 Collaborative Conference for Student
Achievement, March 3-5, 2014
Greensboro, North Carolina
Seen on a cup …
Closing the Gap
Improving Minority and
At-Risk Student Achievement
Presenters
Dr. Michael P. Gallagher
michael.gallagher@dpi.nc.gov
Dr. Vinetta Bell
vinetta.bell@dpi.nc.gov
North Carolina
Department of Public Instruction
Division of Accountability Services
Division of Data, Research and Federal Policy
Introduction
• Mind the Gap. The relationship between
poverty and academic proficiency.
• This session examines quantitative and
qualitative links.
• New Standards: Opportunities and
Hazards, gap-wise.
Quantitative Analysis
Michael P. Gallagher, Ph.D.
Mathematics Test Development
Assessment Development Section
Division of Accountability Services
“Just the facts, …” Joe Friday
• Long-term trend: National Assessment of
Educational Progress (NAEP)
• North Carolina 2012-2013 EOG tests:
aligned with Common Core State
Standards (CCSS) at the school level.
• Groups for Comparison: Black / White
and School Lunch Eligible / Not Eligible
Long Term
• Nationally, trends are moving in a good
direction, but quite slowly.
• NAEP long term report (June 2013)
shows reading and math gaps narrowing
and overall scores increasing. Available
at nces.ed.gov/nationsreportcard/
NAEP Long-Term Trend Math
(9-year-old students – White / Black)
White
Black
Gap
1973
225
190
2012
252
226
Change
Up 27
Up 36
35
25
Down 10
NAEP Long-Term Trend Math
(13-year-old students – White / Black)
White
Black
Gap
1973
274
228
2012
293
264
Change
Up 19
Up 36
46
28
Down 18
NAEP Long Term Math
Observations
• Both Black and White students showed
major improvements.
• Black improvement was greater than
White, about one standard deviation.
• Black student improvement is up to about
where White students were in 1973.
NAEP Long-Term Trend Reading
(9-year-old students – White / Black)
White
Black
Gap
1973
214
170
2012
229
206
Change
Up 15
Up 36
44
23
Down 21
NAEP Long-Term Trend Reading
(13-year-old students – White / Black)
1973
2012
Change
White
Black
261
222
270
247
Up 9
Up 25
Gap
39
23
Down 16
NAEP Long Term Reading
Observations
• Black – White gap was cut one-half to
one-third.
• White students saw some improvement,
Black students quite strong improvement.
• Black students in 2012 were a bit below
White student performance in 1973.
Changing Focus to NC
(NAEP state data from 1992)
• In general, NC started out below the
national average, but NC presently is at
or above the U.S. average.
• http://nces.ed.gov/nationsreportcard/states/
NC - NAEP Trend Math
• White and Black Fourth Grade Students –
NC averages, followed by U.S. in
parentheses (…)
White
1992
223 (227)
2013
Change
254 (250) Up 31 (23)
Black
Gap
193 (192)
30 (35)
230 (224) Up 37 (32)
24 (26) Down 6 (9)
More Quant!
……... And a Shift
• We now move from national and state
levels to school levels.
• The categories will be “eligible for free or
reduced-price lunch” and “not eligible.”
Activity
List 3-5 factors that affect how well a school
performs on achievement tests.
Rate each of those factors according to
how strongly they are related to poverty:
0, very little; 1, somewhat; or 2, strongly.
Compare with one person next to you.
Pair-Share Feedback
• Let’s share just a few of your factors that
you think affect how well a school
performs on achievement tests before we
continue.
• Spontaneous responses are appropriate
(the popcorn method).
NC Poverty and Proficiency –
A Guided Tour
Guided, that is, by Common Core State
Standards (CCSS) in the area of
Statistics and Probability.
… Focus will be on the Triangle: Wake,
Johnston, Durham, Orange and Chapel
Hill – Carrboro.
Statistics in CCSA
• The Common Core State Standards
(CCSA), adopted by NC in 2010, include
a statistics component for high school
students.
• This follows emphasis from the National
Council of Teachers of Math. …nctm.org
• An understanding of key statistical
concepts can inform public discussion.
Standard 8.SPA.1
“Construct and interpret scatterplots for
bivariate measurement data to investigate
patterns of association between two
quantities. Describe patterns such as
clustering, outliers, positive or negative
association, linear association, and
nonlinear association.”
Two Variables and
a Scatterplot
• What does a close relationship look like?
• The correlation coefficient, r, measures the
strength and direction of a relationship.
• r close to 0 means no or weak relationship; r
close to +1 or -1 means a strong relationship.
Who’s on First? (r = 0.31)
Let’s look at Poverty and
Achievement by school.
• Poverty will be indicated by the percent of
students on free or reduced-price lunch
(frl).
• Achievement will be indicated by the
Ready Performance Composite on the
assessments from 2012-2013.
r = 0.92
r = 0.96
r = 0.79
High Schools in the Triangle
90.0
y = -0.8704x + 81.196
R² = 0.6182
Ready Peerformance Composite 2013
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
0
10
20
30
40
50
Free Reduced Lunch Percent
60
70
80
Cluster of Standards:
Interpret Linear Models
•HSS-ID.C.8 “Compute (using technology)
and interpret the correlation coefficient of a
linear fit.”
•HSS-ID.C.9 “Distinguish between
correlation and causation.”
• The correlations between poverty and
performance composite are very strong at
both the elementary school (0.92) and
middle school (0.96) levels.
• But, what about causality?
Correlation and Causation
• If one variable causes another, that
implies they are correlated.
Causality
Correlation. Yes!
• But if two variables are correlated, they
may or may not be causally related.
Correlation
Causality. Maybe.
Correlation & Causality
Some Questions to Explore
• Who’s on first? i.e., which variable causes
which?
• Is there a third variable causing both?
• Are there multiple factors wrapped up into
one variable?
Standard HSS-ID.B.6b
“Informally assess the fit of a function by
plotting and analyzing residuals.”
Residuals. In other words, how far above
or below the regression line are the data
points? What can it tell us if a particular
school is well above or below the line?
Residuals – any large ones?
• One school at 53% Free and ReducedPrice Lunch (frl) and 59.5 performance
level composite (plc) with a residual of 14.
(Predicted plc = 45.0)
• Another school at 87% frl and 34.4 plc.
with a residual of 11. (Predicted plc =
23.2)
Standard HSS-ID.C.7
• Interpret the slope (rate of change) and
the intercept (constant term) of a linear
model in the context of the data.
• Here is the linear model for elementary:
Performance Composite = 79 – 0.64 x %FRL
Interpreting the Elementary
Model
• Intercept or constant term = 79 … So if
there are no FRL students, the
performance composite predicted would
be 79.
• Slope = minus 0.64 … So for each
increase of 10% in FRL, the predicted
performance composite drops 6.4%.
Middle School Model
Performance Composite = 81 – 0.74 x %FRL
• Intercept … pretty close to elementary.
• Slope … steeper: performance drops
more quickly as %FRL increases.
Transition from Quantitative to
Qualitative Analysis
•Back to thinking about causality. Research
is being done using quantitative methods to
explore the factors associated with poverty
that may impact academic performance.
•Fantuzzo et al., for example, use a strong
correlation model to get closer.
Risk Factors
• Study by John Fantuzzo et al. Academic
achievement of African-American boys: A
city-wide, community-based investigation
of risk and resilience. Journal of School
Psychology, 50 (2012)
The Fantuzzo Study
• Third graders in Philadelphia in 20052006. Cumulative Risk Experience from
birth to grade 3. Sum of 6 factors:
1. Child Maltreatment
2. Low Maternal Education
3. Homelessness
Fantuzzo … continued
4. Inadequate Prenatal Care
5. Preterm / Low Birth Weight
6. Lead Exposure
The magnitude of the risk gap between
Black and White is about the magnitude of
the achievement gap. (p.572)
The Fantuzzo Finding
• “… [W]ithin a population of young AfricanAmerican boys in a large urban school
district, school attendance and task
engagement have the ability to greatly
influence the relations between early risk
experiences – beyond poverty – and early
academic achievement.” (p. 574)
Implications
• Poverty affects school attendance.
• Poverty affects task engagement.
• Poverty influences the relationship between early
risk experiences and early academic achievement.
• Early academic achievement influences later
academic success and the global preparedness of
College Career Ready (CCR) students.
Adverse Childhood
Experiences (ACE) Study
On your own …. The Adverse Childhood
Experiences (ACE) Study is one of the
largest investigations ever conducted to
assess associations between childhood
maltreatment and later-life health and
well-being. cdc.gov/ace/
Transition to Qualitative
Analysis
Let’s look now at the relationship between
poverty and a qualitative analysis of student
performance.
Qualitative Analysis
Vinetta Bell, Ed.D., NBCT
Research Associate
Division of Data, Research and Federal
Policy
Office of the State Superintendent, NCDPI
Did you know?
The combined number of children living in
poverty constitutes the largest school district in
the United States.
Source: Layton, Lyndsey (2013). “Study: Poor Children are Now the Majority in
American Public Schools in South, West.” Published Wednesday, October 16, 2013,
by The Washington Post.
TABLE 1 : Overview of Childhood Poverty and Disadvantage in
the United States (Table is from Coley et al., 2013.)
•
All children in poverty
22%
•
Black children in poverty
28%
•
Hispanic children in poverty
25%
•
Children in extreme poverty
4%
•
Households with children who are food insecure
21%
•
Children with unstable parent employment
32%
Source: Coley, Richard J., & Baker, Bruce (2013). Poverty and Education: Finding the Way Forward. Educational
Testing Service (ETS), p. 7. www.ets.org/research (pdf, 60 pp.)
Indicator 7
Family Characteristics of 5- to 17-Year-Olds
In 2011, higher percentages of Black (37 percent), Hispanic (34
percent), American Indian/Alaska Native (33 percent), Native
Hawaiian/Pacific Islander (32 percent) children, and children
of two or more races (20 percent) were living in families below
the poverty threshold than were White (12 percent) and Asian
(14 percent) children.
Source: Aud, Susan et al. (2012). The Condition of Education 2012. ies,
National Center for Education Statistics, and U.S. Department of Education.
May 2012, p. 28. (pdf, 378 pp.)
Poverty’s Influence Upon
Gifted Impoverished Students
•
Low expectations,
•
poverty,
•
weaker family supports, and
•
poor urban schools
make it especially difficult
for high fliers among the disadvantaged
to reach their natural altitude in school.
Source: Andy Smarick (2013). Closing America’s High-achievement Gap (p. 34, see also footnote 12), originally published in Lilia M.
Ruban and Sally M. Reis, “Identification and Assessment of Gifted Students with Learning Disabilities.” Theory into Practice, Spring 2005,
pp. 115-124, jstor.org.proxygw.wrlc.org/stable/pdfplus/3497030.pdf
Why is poverty so pervasive?
• The Investment Model
• The Family Stress Model
The Investment Model
•
Claim #1: Families that live above the poverty line have adequate and increasingly abundant funds and
other resources to invest in their children’s formal and informal education, which accounts for much of
their children’s academic achievements.
•
Claim #2: Families that are poor do not have the funds and other resources to invest in their children’s
formal and informal education, which accounts for much of their children’s academic struggles.
•
Conclusion: Poverty exacerbates the academic achievement and social-emotional-mental development
of children living in families that have insufficient funds and resources.
Source: Cooper, Kerris, and Stewart, Kitty (2013). Does Money Affect Children’s Outcomes? A Systemic
Review. JRF (Joseph Rountree Foundation). www.jrf.org.uk Summary (pdf, 4 pp.) Full Report (pdf, 82 pp.)
(See pp. 39-44 of full report.)
The Family Stress Model
•
Claim #1: Families that have sufficient funds and other resources to live above the level of basic survival
live less stressful lives, which allows their children to concentrate on their academic studies without
worrying about basic survival needs or the resulting stress.
•
Claim #2: Families that have insufficient funds and other resources frequently face basic survival needs
that produce increasingly stressful living conditions and fractured relationships, which deny their children
the ability to concentrate on their academic studies because of worrying about basic survival needs and
the resulting stress of such living conditions.
•
Conclusion: Children who live in poverty frequently do not succeed academically because they are too
focused upon their basic survival needs and the resulting stress that impacts families living in
impoverished conditions.
Source: Cooper, Kerris, and Stewart, Kitty (2013). Does Money Affect Children’s Outcomes? A Systemic
Review. JRF (Joseph Rountree Foundation). www.jrf.org.uk Summary (pdf, 4 pp.) Full Report (pdf, 82 pp.)
(See pp. 39-44 of full report.)
Prevailing Views About Poverty’s
Impact upon Education
•
View #1: The eradication of poverty will solve all or most educational problems, including the persistent
achievement gap and other inequities in society; therefore, poverty must be eliminated in our society first
before complete success in school is possible for all children, especially for children living in poverty.
•
View #2: We must work simultaneously to eradicate poverty and to close the achievement gaps in
society because the entrenched effects of poverty defy easy resolution or even full identification.
•
One of Many Conclusions: Our economic-political-educational responses to the impact of poverty upon
the schooling process and on students’ academic achievement are related to and dependent upon our view
of poverty and its impact upon students and the schooling process.
Sources: See list of references provided for this presentation for examples of scholars and other thinkers and
writers associated with different views about poverty and its impact upon education and the schooling process.
Some Contributing Factors to
Poverty’s Impact upon Children
•
Single parent homes
•
Other family compositions (e.g., absence of father in the home, grandparents as parents, extended
families)
•
Limited parental education (including low wage earners)
•
Unreliable and possibly misappropriated benefits
•
Impoverished communities (e.g., safety and grocery issues)
•
Family’s frequent mobility (e.g., housing and homelessness)
•
Domestic abuse, drugs, gangs, and other forms of abuse
•
Mother’s mental health (a recent research focus)
•
Societal attitudes toward poverty and the poor (e.g., Puritan ethic that influences a voter’s attitude toward
the poor)
How does poverty affect
curriculum and standards?
• Poverty consumes everyone’s attention.
• Struggling students who read below
grade level are already behind
academically when more rigorous
standards are introduced.
Transition to the Common
Core State Standards (CCSS)
Let’s look now at the impact of the Common
Core State Standards Initiative (CCSSI)
upon students, especially upon students
who live in impoverished circumstances.
Common Core State Standards
(CCSS) Initiative
• The Standards for Mathematical Practice
• The Standards for English Language Arts [ELA] and
Literacy in History/Social Studies, Science, and
Technical Subjects
http://www.corestandards.org
http://www.ncpublicschools.org/acre/standards/
Common Core State Standards
(CCSS): Increased Rigor
• K-12 CCSS in mathematics require
students to think critically about their
process as they perform more
challenging mathematical functions.
• K-12 CCSS in ELA and Literacy require
students to read progressively complex
imagined and informational texts.
CCSS: The Expectations of
More Rigorous Standards
• Students who are struggling under the weight of
poverty and low academic performance are
now faced with mastering 21st century globally
competitive rigorous standards.
• Teachers must engage students at their current
academic levels and stretch them to meet
(preferably to master) more rigorous standards.
Common Core and Poverty –
Opportunities
• Student, parents, and teachers know
early on what performance is on-track for
College and Career Ready (CCR).
• Common Core State Standards get at
very important learning. For an example,
remember the statistics we discussed.
Common Core and Poverty –
Dangers
• Motivation: More students are getting a
negative message on their performance.
Messaging is critical so that students do
not decide that they can’t learn.
• Bad grades for many schools: If staff is
working hard and smart, then how do we
avoid more harm than good?
Closure
• Poverty undoubtedly affects student
performance in negative ways.
• The total elimination of poverty might be
impossible or improbable, but the negative
effects of poverty can be diminished.
• The increased rigorous expectations of
standards upon all students cannot be ignored.
Questions/Comments
Contact Information
•
Dr. Michael P. Gallagher
Mathematics Consultant, NCDPI
michael.gallagher@dpi.nc.gov
919.807.3777
•
Dr. Vinetta Bell
Research Associate, NCDPI
vinetta.bell@dpi.nc.gov
919.807.3800
Poverty, Proficiency, and the Common Core State Standards
2014 Collaborative Conference for Student Achievement
March 3-5, 2014
Greensboro, North Carolina
michael.gallagher@dpi.nc.gov
vinetta.bell@dpi.nc.gov
Links and Articles

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NAEP long term report (June 2013) all the way from 1972. National level. Graphs
provide a visual way to follow the ethnicity gap across about forty years.
nces.ed.gov/nationsreportcard
NAEP state level data from the early 1990s. Includes a poverty breakout.
nces.ed.gov/nationsreportcard/states
School or LEA level information for North Carolina
ncpublicschools.org/accountability/reporting/
click on READY Accountability Model Results;
then use the pull-down menus to select LEA and school;
point to the top of the Performance Composite bar graph for pass rate;
click on “Federal AMO …” to find number economically disadvantaged.
For further analysis: data for North Carolina. Some data skills are needed.
ncpublicschools.org/accountability/reporting/datasets
Common Core State Standards for Mathematics.
corestandards.org/math
Standards referenced in this presentation are from the High School domain:
“Interpreting Categorical and Quantitative Data.”
Also, we model the relationship between poverty and achievement, following
Number 4 in the “Standards for Mathematical Practices.”
Adverse Childhood Experiences (ACE) The Centers for Disease Control and Prevention
(CDC) tracks more than 17,000 participants for the relationship between child risk
factors and adult physical and mental health.
cdc.gov/ace/
Risk Factors. John Fantuzzo, et al. Academic Achievement of African-American boys: A
city-wide, community-based investigation of risk and resilience. Journal of School
Psychology. 50 (2012)
Selected References for Poverty:
Poverty, Proficiency, and the Common Core State Standards (presentation)
Co-Presenters: Dr. Michael P. Gallagher and Dr. Vinetta Bell, NCDPI 2014 Collaborative Conference March 3-5, 2014
Selected References for Poverty Presentation
2014 Collaborative Conference
March 3-5, 2014
Poverty, Proficiency, and the Common Core State Standards
Co-Presenters:
Dr. Michael P. Gallagher and Dr. Vinetta Bell
North Carolina Department of Public Instruction
Note: These references represent some of the texts that address the issue of poverty as it relates to education
and the schooling process. Available links to a source as well as the text type and total number of pages are
included. Copyright prevents distribution of these texts by the co-presenters.
(1) Almy, Sarah, and Theokas, Christina (2010). Not Prepared for Class: High-Poverty Schools Continue to
Have Fewer In-Field Teachers. The Education Trust. November 2010. (pdf, 6 pp.)
(2) Aud, Susan et al. (2012). The Condition of Education 2012. ies. National Center for Education Statistics, and
U.S. Department of Education. May 2012. (pdf, 378 pp.)
(3) Baker, Bruce D. (2013). “Petrilli’s Hammer & Poverty Has Nothing to do with PISA Argument.” Posted
online on December 4, 2013, School Finance 101. Retrieved December 6, 2013, from
http://schoolfinance101.wordpress.com/2013/12/04/petrillis-hammer-the-poverty-has-nothing-to-do-withpisa-argument/ (WORD, 9 pp.)
(4) Barton, Paul E., & Coley, Richard J. (2010). The Black-White Achievement Gap: When Progress Stopped.
Educational Testing Service (ETS). July 2010. www.ets.org/research/pic (pdf, 42 pp.)
(5) Blank, Rolf K. (2011). Closing the Achievement Gap for Economically Disadvantaged Students? Analyzing
Change Since No Child Left Behind Using State Assessments and the National Assessment of Educational
Progress. Council of Chief State School Officers (CCSSO). April 2011. www.ccsso.org
(pdf, 26 pp.)
(6) Brooks-Gunn, Jeanne, & Duncan, Greg J. (1997). The Effects of Poverty on Children. The Future of
Children. Children and Poverty, Vol. 7, No. 2, Summer/Fall 1997. (pdf, 17 pp.)
(7) Castro, Quassan (2014). “Twelve Tips All Educators Must Know About Educating African
American and Latino Students.” Published online on January 6, 2014, in Huffington Post, Black
Voices. Retrieved Monday, January 6, 2014, from http://www.huffingtonpost.com/quassancastro/twelve-tips-all-educators_b_4533419.html
(WORD, 4 pp.)
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Selected References for Poverty:
Poverty, Proficiency, and the Common Core State Standards (presentation)
Co-Presenters: Dr. Michael P. Gallagher and Dr. Vinetta Bell, NCDPI 2014 Collaborative Conference March 3-5, 2014
(8) Centers for Disease Control and Prevention (2013).
http://www.cdc.gov/violenceprevention/childmatreatment/consequences.pdf
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Child Maltreatment Consequences
Data and Statistics
Major Findings
Pyramid
Related Links
(9) Child Welfare Information Gateway. Children’s Bureau/ACYF/ACF/HHS (2013). Long-Term
Consequences of Child Abuse and Neglect. Fact Sheet.
https://www.childwelfare.gov
https://www.childwelfare.gov/pubs/factsheets/long_term_consequences.cfm
(10 pp.)
(10)
Children’s Defense Fund (2010). America’s Children. (pdf, 185 pp.)
(11)
Children’s Defense Fund (2008). Child Poverty in America. (pdf, 6 pp.)
Christensen, Rob (2013). “Commentary: Christensen: The Fall and Rise of NC Poverty”
Retrieved Sunday, November 10, 2013, from WRAL.com
http://www.newsobserver.com/2013/11/09/3355851/christensen-the-fall-and-rise.html
(WORD, 2 pp.)
(12)
(13)
Clotfelter, Charles T., Ladd, Helen F., & Vigdor, Jacob L. (2013). Racial and Economic Diversity in
North Carolina’s Schools: An Update. Duke [University] Sanford School of Public Policy. Sanford
Working Papers Series. January 16, 2013. (pdf, 45 pp.)
(14)
Coley, Richard J., & Baker, Bruce (2013). Poverty and Education: Finding the Way Forward.
Educational Testing Service (ETS). The ETS Center for Research on Human Capital and Education. July
2013. www.ets.org/research
(pdf, 60 pp.)
(15)
Conley, D.T. et al. (2011). Lining up: The relationship between the Common Core State Standards and
five sets of comparison standards. (pdf, 86 pp.)
(16)
Cooper, Kerris, and Stewart, Kitty (2013). Does Money Affect Children’s Outcomes? A Systemic Review.
JRF (Joseph Rountree Foundation). www.jrf.org.uk Summary (pdf, 4 pp.) Full Report (pdf, 82 pp.)
(17)
Edelman, Marian Wright, and Engler, John (2013). Meet the Class of 2025: Investing in the Education
of Young Children—Money Well Spent. Scholastic. (pdf, 10 pp.)
(18)
Ellen, Ingrid Gould et al. (2012). Do Federally Assisted Households Have Access to High Performing
Public Schools? Poverty & Race Research Action Council (PRRAC). Civil Rights Research. November
2012. (pdf, 24 pp.)
(19)
Feaste, N.S. et al. (2002). A Comparison of Initiatives: 1960s to 1990s – Closing Educational
Achievement Gaps. (pdf, 27 pp.)
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Selected References for Poverty:
Poverty, Proficiency, and the Common Core State Standards (presentation)
Co-Presenters: Dr. Michael P. Gallagher and Dr. Vinetta Bell, NCDPI 2014 Collaborative Conference March 3-5, 2014
(20)
Finder, Alan (2005). As Test Scores Jump, Raleigh Credits Integration by Income. New York Times
online. (WORD, 5 pp.)
(21)
Greenstone, Michael et al. (2012). A Dozen Economic Facts About K-12 Education. The Hamilton
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(22)
Hansen, Michael (2013). Right-sizing the Classroom: Making the Best of Great Teachers. (pdf, 36 pp.)
(23)
Hartman, C. et al. (2002). “High classroom turnover: How children get left behind.” (WORD, 5 pp.)
(24)
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(25)
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(26)
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(27)
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(28)
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(29)
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(30)
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(31)
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(32)
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(33)
Layton, Lyndsey (2013). “Study: Poor Children are Now the Majority in American Public Schools in
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October 17, 2013, from http://www.washingtonpost.com/local/education/study-poor-children-are-now-themajority-in-american-public-schools-in-south-west/2013/10/16/34eb4984-35bb-11e3-8a0e4e2cf80831fc_story.html
(WORD, 4 pp.)
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Selected References for Poverty:
Poverty, Proficiency, and the Common Core State Standards (presentation)
Co-Presenters: Dr. Michael P. Gallagher and Dr. Vinetta Bell, NCDPI 2014 Collaborative Conference March 3-5, 2014
(34)
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