This paper discusses the search for a “magic metric” in education: an index/number that would be generally accepted as the most efficient descriptor of school’s performance in a district.
Celio, M. B. (2013). Seeking the Magic Metric: Using Evidence to Identify and Track School System Quality. In Performance Feedback: Using Data to Improve Educator Performance (Vol. 3, pp. 97-118). Oakland, CA: The Wing Institute.
Response to Intervention is a framework for determining the intensity of services that are necessary for a student to benefit from instruction. This paper addresses some of the misconceptions about RtI.
Detrich, R., States, J., & Keyworth, R. (2008). Response to Intervention: What it Is and What it Is Not. Journal of Evidence-based Practices for Schools, 9(2), 60-83.
This paper discusses the search for a “magic metric” in education: an index/number that would be generally accepted as the most efficient descriptor of school’s performance in a district.
Celio, MB. (2011). Seeking the Magic Metric: Using Evidence to Identify and Track School System Progress [Powerpoint Slides]. Retrieved from 2011-wing-presentation-mary-beth-celio.
This paper discusses the importance of systematizing data-based decision making at all levels of school operation.
States, J. (2009). In God We Trust; All Others Must Bring Data [Powerpoint Slides]. Retrieved from 2009-wing-presentation-jack-states.
This study was guided by a reduced version of the Self-System Process Model developed by Connell. This paper report the optimal and risk thresholds for the Student Performance and Commitment Index (SPCI) and engagement, and then data on how much engagement matters for later success in school are presented.
Klem, A. M., & Connell, J. P. (2004). Relationships matter: Linking teacher support to student engagement and achievement. Journal of school health, 74(7), 262-273.
This overview examines the best available evidence from a wide range of descriptive and correlational analyses executed by various state and city education departments, research groups, and academic researchers. Fortunately, the data paint an unequivocal picture. The results are overwhelmingly consistent across levels of analysis (school, students), units of measurement (achievement tests, graduation rates, dropout rates), areas of focus (reading, math, social indicators), units of education (grades, schools), and students of all demographics. Additionally, each analysis shows a linear relationship between absences and performance; the greater the number of absences, the worse the performance.
Alexander, K. L., Entwisle, D. R., & Olson, L. S. (2001). Schools, achievement, and inequality: A seasonal perspective. Educational Evaluation and Policy Analysis, 23(2), 171–191.
Allison, M. A., Attisha, E., & AAP Council on School Health. (2019). The link between school attendance and good health. Pediatrics, 143(2). e20183648
Anguiano, M., Eastin D., Fine, M, Lockyer, B., Robles, D., Santana, M.,…Wong, K. (2015). Los Angeles Unified School District Report of the Independent Financial Review Panel. Los Angeles, CA: Los Angeles Unified School District.
Applied Survey Research. (2011). Attendance in early elementary grades: Associations with student characteristics, school readiness, and third grade outcomes. San Francisco, CA: Attendance Works.
Ashby, C. M. (2010). K–12 education: Many challenges arise in educating students who change schools frequently.Report to Congressional Requesters (GAO-11-40). Washington, DC: Government Accountability Office.
Attendance Works. (2018).3 tiers of intervention.Retrieved from https://www.attendanceworks.org/chronic-absence/addressing-chronic-absence/3-tiers-of-intervention/
Attendance Works and Everyone Graduates Center. (2017). Portraits of change: Aligning school and community resources to reduce chronic absence.Retrieved from https://www.attendanceworks.org/portraits-of-change/
Balfanz, R., & Byrnes, V. (2012). The importance of being in school: A report on absenteeism in the nation’s public schools. Baltimore, MD: Johns Hopkins University Center for Social Organization of Schools.
Balfanz, R., & Byrnes, V. (2013). Meeting the challenge of combating chronic absenteeism: Impact of the NYC mayor’s interagency task force on chronic absenteeism and school attendance and its implications for other cities. Baltimore, MD: Johns Hopkins School of Education.
Balfanz, R., Durham, R., & Plank, S. (2008). Lost days: Patterns and levels of chronic absenteeism among Baltimore City public school students 1999-00 to 2005-06. Baltimore, MD: Baltimore Education Research Consortium.
Balfanz, R., Herzog, L., & Mac Iver, D. J. (2007). Preventing student disengagement and keeping students on the graduation path in urban middle-grades schools: Early identification and effective interventions. Educational Psychologist, 42(4), 223–235.
Baltimore Education Research Consortium. (2011). Destination graduation: Sixth grade early warning indicators for Baltimore city schools. Their prevalence and impact. Baltimore, MD: Author.
Bauer, L., Liu, P., Whitmore Schanzenbach, D., & Shambaugh, J. (2018). Reducing chronic absenteeism under the every student succeeds act. The Hamilton Project. Washington, DC: Brookings Institute. Retrieved from http://www.hamiltonproject.org/assets/files/reducing_chronic_absenteeism_under_the_every_student_succeeds_act.pdf
Buehler, M. H., Tapogna, J., Chang, H. N., & ECO Northwest, Ltd. (2012). Why being in school matters: Chronic absenteeism in Oregon Public Schools. Attendance Works.
Burkam, D. T., Ready, D. D., Lee, V. E., & LoGerfo, L. (2004). Social-class differences in summer learning between kindergarten and first grade: Model specification and estimation. Sociology of Education, 77(1), 1–31.
Chang, H. N., Bauer, L., & Byrnes, V. (2018). Data matters: Using chronic absence to accelerate action for student success.Attendance Worksand Everyone Graduates Center.
Chang, H. N., & Romero, M. (2008). Present, engaged, and accounted for: The critical importance of addressing chronic absence in the early grades.New York, NY: National Center for Children in Poverty.
Chen, C., & Stevenson, H. W. (1995). Motivation and mathematics achievement: A comparative study of Asian‐American, Caucasian‐American, and East Asian high school students. Child Development, 66(4), 1215–1234.
Chingos, M., & Blagg, K. (2017). Making sense of state school funding policy.Washington, DC: Urban Institute.
Coelho, R., Fischer, S., McKnight, F., Matteson, S., & Schwartz, T. (2015). The effects of early chronic absenteeism on third-grade academic achievement measures.Madison, WI: Robert M. La Follette School of Public Affairs, University of Wisconsin.
Connell, J. P., Spencer, M. B., & Aber, J. L. (1994). Educational risk and resilience in African‐American youth: Context, self, action, and outcomes in school. Child Development, 65(2), 493–506.
da Costa Nunez, R., Erb-Downward, J., & Shaw-Amoah, A. (2015). Empty seats: The epidemic of absenteeism among homeless elementary students. New York, NY: Institute for Children, Poverty & Homelessness. Retrieved from https://www.attendanceworks.org/wp-content/uploads/2017/12/ICPH-Policy-Report_Empty-Seats_Chronic-Absenteeism.pdf
Digest of Education Statistics. (2017). Homeless students enrolled in public elementary and secondary schools, by grade, primary nighttime residence, and selected student characteristics: 2009-10 through 2015–16.Table 204.75a.Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Downey, D. B., von Hippel, P. T., & Broh, B. A. (2004). Are schools the great equalizer? Cognitive inequality during the summer months and the school year. American Sociological Review, 69(5), 613–635.
Durán-Narucki, V. (2008). School building condition, school attendance, and academic achievement in New York City public schools: A mediation model. Journal of environmental psychology, 28(3), 278–286.
Epstein, J. L. & Sheldon, S. B. 2002. Present and accounted for: Improving student attendance through family and community involvement. Journal of Educational Research 95(5): 308–318.
Fantuzzo, J. W., LeBoeuf, W. A., Chen, C. C., Rouse, H. L., & Culhane, D. P. (2012). The unique and combined effects of homelessness and school mobility on the educational outcomes of young children. Educational Researcher, 41(9), 393–402.
Fiester, L. (2010). Early warning! Why reading by the end of third grade matters.Kids Count special report. Baltimore, MD: Annie E. Casey Foundation.
GAO, (1994) Elementary school children: Many change schools frequently, harming their education,GAO/HEHS-94-45 (Washington, D.C.: Feb. 4, 1994).
Ginsburg, A., Jordan, P., & Chang, H. (2014). Absences Add Up: How School Attendance Influences Student Success. Attendance Works.
Gottfried, M. A. (2010). Evaluating the relationship between student attendance and achievement in urban elementary and middle schools: An instrumental variables approach. American Educational Research Journal, 47(2), 434–465.
Gottfried, M. A. (2014). Chronic absenteeism and its effects on students’ academic and socio-emotional outcomes. Journal of Education for Students Placed at Risk (JESPAR), 19(2), 53–75.
Gottfried, M. A. (2015). Chronic absenteeism in the classroom context: Effects on achievement. Urban Education,54(1), 3–34.
Gottfried, M. A. & Hutt, E.L. (Eds.). (2019). Absent from school: Understanding and addressing student absenteeism.Cambridge, MA: Harvard Education Press.
Harris, Kamala. (2016). In School + On Track 2016.Sacramento, CA: Office of the Attorney General, State of California Department of Justice.
Henderson, T., Hill, C., & Norton, K. (2014). The connection between missing school and health: A review of chronic absenteeism and student health in Oregon.Portland, OR: Upstream Public Health.
Hernandez, D. (2011). Double jeopardy: How third-grade reading skills and poverty influence high school graduation.Baltimore, MD: Annie E. Casey Foundation.
Hess, F. M., & McShane, M. Q. (2018), Bush-Obama school reform: Lessons learned.Cambridge, MA: Harvard Education Press.
Johnson, G. M. (2005). Student alienation, academic achievement, and WebCT use. Journal of Educational Technology & Society, 8(2), 179–189.
Kearney, C. A. (2016). Managing school absenteeism at multiple tiers: An evidence-based and practical guide for professionals. New York City, NY: Oxford University Press.
Kearney, C. A., & Graczyk, P. (2014). A response to intervention model to promote school attendance and decrease school absenteeism. Child & Youth Care Forum,43(1), 1–25.
Lawrence, E. M., Rogers, R. G., & Zajacova, A. (2016). Educational attainment and mortality in the United States: Effects of degrees, years of schooling, and certification. Population Research and Policy Review, 35(4), 501–525.
London, R, A., Sanchez, M., & Castrechini, S. (2016). The dynamics of chronic absence and student achievement. Education Policy Analysis Archives, 24(112), 1–27.
Losen, D. J., & Whitaker, A. (2018). 11 million days lost: Race, discipline, and safety at U.S. public schools. A joint report by the Center for Civil Rights Remedies of UCLA’s Civil Rights Project and the American Civil Liberties Union of Southern California.
Mac Iver, M. A., & Messel, M. (2012). Predicting high school outcomes in the Baltimore city public schools.The Senior Urban Education Research Fellowship Series. Volume VII. Washington, DC: Council of the Great City Schools.
NAEP Data Explorer, 2015 and 2017 mathematics and reading assessments. Washington, DC: U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP). Retrieved from https://nces.ed.gov/nationsreportcard/naepdata/
NAEP Data Explorer, 2015 and 2017 reading and mathematics scale scores of 4th, 8th, and 12th graders and percentage absent from school, by selected characteristics and number of days absent in the last month. Table 227.50. Washington, DC: U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP). Retrieved from https://www2.ed.gov/datastory/chronicabsenteeism.html#one
National Forum on Education Statistics. (2009). Every school day counts: The forum guide to collecting and using attendance data (NFES 2009–804). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Nowicki,J. M. (2018). K–12 Education: Discipline disparities for Black students,boys, and students with disabilities. Report to Congressional Requesters. GAO-18-258. Washington, DC: Government Accountability Office.
Olsen, L. S. (2014). Why September matters: Improving student attendance.Policy brief. Baltimore, MD: Baltimore Education Research Consortium.
Office for Civil Rights. (2016). 2013–2014 civil rights data collection: A first look.
Railsback J. (2004). Increasing student attendance: Strategies from research and practice.Northwest Regional Educational Laboratory. Portland, OR.
Ready, D. D. (2010). Socioeconomic disadvantage, school attendance, and early cognitive development: The differential effects of school exposure. Sociology of Education 83(4): 271–286.
Robertson, A. A., & Walker, C. S. (2018). Predictors of justice system involvement: Maltreatment and education. Child Abuse & Neglect, 76, 408–415.
Robinson, C. D., Lee, M. G., Dearing, E., & Rogers, T. (2018). Reducing student absenteeism in the early grades by targeting parental beliefs. American Educational Research Journal, 55(6), 1163–1192.
Rogers, T., & Feller, A. (2018). Reducing student absences at scale by targeting parents’ misbeliefs. Nature Human Behaviour, 2(5), 335.
Romero, M., & Lee, Y. (2007). A national portrait of chronic absenteeism in the early grades.New York, NY: National Center for Children in Poverty, the Mailman School of Public Health at Columbia University.
Rumberger, R. W. (2015). Student mobility: Causes, consequences, and solutions. Boulder, CO: National Education Policy Center, University of Colorado.
Snell L., Smith, G. A., Koteskey, T., Joffe, M., & Bui, T. (2018). A 2018 evaluation of LAUSD’s fiscal outlook: Revisiting the findings of the 2015 Independent Financial Review Panel.Los Angeles, CA: Los Angeles Unified School District.
Telfair, J., & Shelton, T. L. (2012). Educational attainment as a social determinant of health. North Carolina Medical Journal, 73(5), 358–365.
Tourangeau, K., Nord, C., Lê, T., Sorongon, A. G., & Najarian, M. (2009). Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K): Combined User's Manual for the ECLS-K Eighth-Grade and K-8 Full Sample Data Files and Electronic Codebooks. NCES 2009-004. National Center for Education Statistics.
U.S. Department of Education. (2008). A uniform, comparable graduation rate: How the final regulations for Title I hold schools, districts, and states accountable for improving graduation rates. Retrieved from https://www2.ed.gov/policy/elsec/reg/proposal/uniform-grad-rate.html
U.S. Department of Education, Office for Civil Rights, 2013–2014 Civil Rights Data Collection. A First Look; Key Data Highlights on Equity and Opportunity Gaps in Our Nation’s Public Schools.Retrieved from https://www2.ed.gov/about/offices/list/ocr/docs/2013-14-first-look.pdf
U.S. Department of Education, Office for Civil Rights, 2015–2016 Civil Rights Data Collection. Chronic absenteeism in the nation’s schools: A hidden educational crisis. Retrieved from https://www2.ed.gov/datastory/chronicabsenteeism.html#one
Utah Education Policy Center [UEPC]. (2012). Research brief: Chronic absenteeism.Retrieved from https://www.schools.utah.gov/file/31291767-087c-4edb-8042-87f272507c1d
This article discuss about study that measures the effect of offering healthier public school lunches on end of year academic test scores for public school students in California. This study focus on school-specific differences in lunch quality over-time. The study shows increasing the nutritional quality of school meals appears to be promising, cost-effective way to improve student learning.
Anderson. M. L., Gallagher, J., Ritchie. E. R. (2017). How the Quality of School Lunch Affects Students' Academic Performance. Brookings Institution. Retrieved from https://www.brookings.edu/blog/brown-center-chalkboard/2017/05/03/how-the-quality-of-school-lunch-affects-students-academic-performance/
This article presents the results of longitudinal retrospective analyses on suspensions, achievement, and long-term enrollment status of students in a large, urban school district. Findings indicated that suspended students had substantially lower presuspension achievement than did students in the comparison group, gained considerably less academically throughout 3 years with suspensions, and had high drop-out rates.
Arcia, E. (2006). Achievement and enrollment status of suspended students: Outcomes in a large, multicultural school district. Education and Urban Society, 38(3), 359-369.
This article reviews the decision rules for curriculum based reading scores. It concluded the rules were most often based on expert opinion.
Ardoin, S. P., Christ, T. J., Morena, L. S., Cormier, D. C., & Klingbeil, D. A. (2013). A systematic review and summarization of the recommendations and research surrounding Curriculum-Based Measurement of oral reading fluency (CBM-R) decision rules. Journal of School Psychology, 51(1), 1-18.
This NCES study explores public schools' demographic composition, in particular, the proportion of Black students enrolled in schools (also referred to "Black student density" in schools) and its relation to the Black-White achievement gap. This study, the first of it's kind, used the 2011 NAEP grade 8 mathematics assessment data. Among the results highlighted in the report, the study indicates that the achievement gap between Black and White students remains whether schools fall in the highest density category or the lowest density category.
Bohrnstedt, G., Kitmitto, S., Ogut, B., Sherman, D., and Chan, D. (2015). School Composition and the Black–White Achievement Gap (NCES 2015-018). U.S. Department of Education, Washington, DC: National Center for Education Statistics. Retrieved from http://nces.ed.gov/pubsearch.
This research aim to find a strong connection between standards-based reform and student outcomes by studied the most recent NAEP data. Their findings believe that states should remain dedicated to standards-based reform. The Common Core is the most recent major policy initiative to advance the broader standards-based reform approach and states should continue their commitment to the Common Core’s full implementation and aligned assessments.
Boser, U., & Brown, C. (2016). Lessons from State Performance on NAEP: Why Some High-Poverty Students Score Better than Others. Center for American Progress.
This paper advances the discussion of the achievements differences between the higher and lower social-class groups were increasing, particularly between children in the highest income group and everyone else issue by analyzing trends in the influence of race/ethnicity, social class, and gender on students’ academic performance in the United States. This paper also explores the ways in which English language ability relates to Hispanics’ and Asian Americans’ academic performance over time (Nores and Barnett 2014).
Carnoy, M., & García, E. (2017). Five Key Trends in US Student Performance: Progress by Blacks and Hispanics, the Takeoff of Asians, the Stall of Non-English Speakers, the Persistence of Socioeconomic Gaps, and the Damaging Effect of Highly Segregated Schools. Economic Policy Institute.
This report provides a first look at students' persistence, retention, and attainment over 6 years, showing the rates at which students had completed postsecondary credentials, the rates at which they had persisted through or left postsecondary education without earning any credential as of spring 2017, and the rates at which they remained in the first institution in which they were enrolled. Postsecondary graduation rates in public institutions have stayed virtually the same for seven years, with 57% of students graduating in 2011 and 59% in 2017. Private non-profit institutions remained at 65-66% graduation for the first six years, increasing by 8 percentage points in 2017. Private for-profit institutions fared the worst, decreasing consistently from 42% in 2011 to 14% in 2017.
Chen, X., Elliott, B.G., Kinney, S.K., Cooney, D., Pretlow, J., Bryan, M., Wu, J., Ramirez, N.A., and Campbell, T. (2019). Persistence, Retention, and Attainment of 2011–12 First-Time Beginning Postsecondary Students as of Spring 2017 (First Look) (NCES 2019-401). U.S. Department of Education. Washington, DC: National Center for Education Statistics.
Daly, I. I. I., Edward J, Martens, B. K., Barnett, D., Witt, J. C., & Olson, S. C. (2007). Varying Intervention Delivery in Response to Intervention: Confronting and Resolving Challenges With Measurement, Instruction, and Intensity. School Psychology Review, 36(4), 562-581.
This study describe the schools, students, and programs in the for-profit higher education sector, it's phenomenal recent growth, and it's relationship to the federal and state governments. The study find that for-profit institutions educate a larger fraction of minority, disadvantaged, and older students, and they have greater success at reatining students in their first year and fetting them to complete short programs at the certificate and AA levels. But they also find that the for-profit students end-up with higher unemployment and "idleness" rates and lower earning six years after entering programs than do comparable students from other schools. and they have far greater student debt burdens and default rates on their student loans.
Deming, David J., Claudia Goldin, and Lawrence F. Katz. 2012. "The For-Profit Postsecondary School Sector: Nimble Critters or Agile Predators?" Journal of Economic Perspectives, 26 (1): 139-64.
Curriculum-based measurement is a type of formative assessment. It is used to screen for students who are not progressing and to identify how well students are responding to interventions.
Deno, S. L. (2003). Developments in Curriculum-Based Measurement. Journal of Special Education, 37(3), 184-192.
This article reviews the advantages of curriculum-based measurement as part of a data-based problem solving model.
Deno, S. L., & Fuchs, L. S. (1987). Developing Curriculum-Based Measurement Systems For Data Based Special Education Problem Solving. Focus on Exceptional Children, 19(8), 1-16.
Education Cities and GreatSchools have together launched the Education Equality Index in an attempt to answer "how does the U.S. fare in our effort to provide equal opportunity to all children?" question. The Education Equality Index is the first national comparative measure of the achievement gap between children growing up in low-income communities and their more advantaged peers.
Education Equality in America Comparing the Achievement Gap Across School and Cities. (2016, March). Education Equality Index. Retrieved from http://www.educationequalityindex.org/wp-content/uploads/2016/02/Education-Equality-in-America-v1-4.pdf
This article describes using formative assessemnt as a foundational tool in a data-based problem solving approach to solving social behavior problems.
Ervin, R. A., Schaughency, E., Matthews, A., Goodman, S. D., & McGlinchey, M. T. (2007). Primary and secondary prevention of behavior difficulties: Developing a data-informed problem-solving model to guide decision making at a school-wide level. Psychology in the Schools, 44(1), 7-18.
This research examines the impact of longer school days on student achievement. This study attempts to fill in gaps in the evidence-base on this topic. Although this study finds positive outcomes for additional reading instruction, it is important to note that for achieving maximum results it is important to pair evidence-based reading instruction practices with the additional instruction time in order to achieve maximum results.
Figlio, D., Holden, K. L., & Ozek, U. (2018). Do students benefit from longer school days? Regression discontinuity evidence from Florida’s additional hour of literacy instruction. Economics of Education Review, 67, 171-183.
This paper reports the results of a study that investigated the reading differences between students who were low achieving, both with and without the label of learning disabilities (LD).
Fuchs, D., Fuchs, L. S., Mathes, P. G., Lipsey, M. W., & Roberts, P. H. (2001). Is" Learning Disabilities" Just a Fancy Term for Low Achievement?: A Meta-Analysis of Reading Differences Between Low Achievers with and Without the Label. Executive Summary. ERIC Clearinghouse.
This article compares and contrasts mastery level measures (grades) with curriculum-based measurement (global outcome measure).
Fuchs, L. S., & Deno, S. L. (1991). Paradigmatic distinctions between instructionally relevant measurement models. Exceptional Children, 57(6), 488-500.
In this meta-analysis of studies that utilize formative assessment the authors report an effective size of .7.
Fuchs, L. S., & Fuchs, D. (1986). Effects of Systematic Formative Evaluation: A Meta-Analysis. Exceptional Children, 53(3), 199-208.
Curriculum-based measurement is recommended as an assessment method to identify students that require special education services.
Fuchs, L. S., & Fuchs, D. (1997). Use of curriculum-based measurement in identifying students with disabilities. Focus on Exceptional Children, 1.
This study examines the effect of formative assessment on teachers’ instructional planning.
Fuchs, L. S., Fuchs, D., & Stecker, P. M. (1989). Effects of Curriculum-Based Measurement on Teachers’ Instructional Planning. Journal of Learning Disabilities, 22(1).
TIMSS is designed to align broadly with mathematics and science curricula in the participating countries. This report focuses on the performance of U.S. students relative to that of their peers in other countries in 2007, and on changes in mathematics and science achievement since 1995. This report also describes additional details about the achievement of U.S. student subpopulations. All differences described in this report are statistically significant at the .05 level. No statistical adjustments to account for multiple comparisons were used.
Gonzales, P., Williams, T., Jocelyn, L., Roey, S., Kastberg, D., & Brenwald, S. (2008). Highlights from TIMSS 2007: Mathematics and Science Achievement of US Fourth-and Eighth-Grade Students in an International Context. NCES 2009-001. National Center for Education Statistics.
The authors contrast the functions of high stakes testing with prevention-based assessment. The authors also show the value of using formative assesment to estimate performance on high stakes tests.
Good, R.H., III., Simmons, D. C., & Kame’enui, E. J. (2001). The Importance and Decision-Making Utility of a Continuum of Fluency-Based Indicators of Foundational Reading Skills for Third-Grade High-Stakes Outcomes. Scientific Studies of Reading, 5(3), 257-288.
Curriculum based measures were used to to evaluate student progress across multiple years following the introduction of selected evidence-based practices.
Greenwood, C. R., Tapia, Y., Abbott, M., & Walton, C. (2003). A Building-Based Case Study of Evidence-Based Literacy Practices: Implementation, Reading Behavior, and Growth in Reading Fluency, K--4. Journal of Special Education, 37(2), 95.
This report is the first chapter of the 2018 Brown Center Report on American Education. This section explore trends in math, reading, and civics performance from the late 1990s through the most recent year in which results are available (2017 in math and reading, 2014 in civics). It show trends in nationwide performance and in test score gaps by race (white-black), ethnicity (white-Hispanic), and family income (based on eligibility for free or reduced-price lunch [FRL]). In doing so, this report examine test score trajectories from the beginning to the end of the No Child Left Behind era (NCLB). The 2017 results, in particular, reflect a boundary in the timeline of education policy, demarcating the end of NCLB and the beginning of the Every Student Succeeds Act (ESSA).
Hansen, M., Levesque, E., Valant, J., & Quintero, D. (2018). The 2018 Brown Center Report on American Education: How Well are American Students Learning. Washington, DC: The Brookings Institution.
The Coleman Report was mandated by the Civil Rights Act of 1964. The act gave the US Office of Education two years to produce a report that was expected to describe the inequality of educational opportunities in elementary and secondary education across the United States.
Hanushek, E. A. (2016). What matters for student achievement. Education Next, 16(2), 18-26.
This new research addresses a number of critical questions: Are a teacher’s cognitive skills a good predictor of teacher quality? This study examines the student achievement of 36 developed countries in the context of teacher cognitive skills. This study finds substantial differences in teacher cognitive skills across countries that are strongly related to student performance.
Hanushek, E. A., Piopiunik, M., & Wiederhold, S. (2014). The value of smarter teachers: International evidence on teacher cognitive skills and student performance (No. w20727). National Bureau of Economic Research.
In 2017, the percentages of eighth-grade students who performed at or above the Proficient level were higher for several student groups in comparison to 2015. For example, the percentages of Black and Hispanic eighth-grade students who performed at or above the Proficient level on the reading assessment were higher in 2017 compared to 2015. The percentages of students who performed at or above Proficient were also higher for male and female students, students attending public schools, as well as for eighth-graders attending schools in suburban locations. Compared to 2015, there were no significant changes in the percentages of students performing at or above the Basic level for any reported student group.
Higher percentage of Black and Hispanic eighth-grade students at or above Proficient in reading compared to 2015. (2017). Nations Report Card. Retrieved from https://www.nationsreportcard.gov/reading_2017/nation/achievement/?grade=8
In the last 20 years, international surveys assessing learning in reading, mathematics and science have been headline news because they put countries in rank order according to performance. The three most well known surveys are TIMSS, PISA and PIRLS. The survey offer information about international performances for the use of others in order to drive up education standards everywhere. They also emphasise that their aim is to facilitate dissemination of ideas on which features of education systems lead to the best performances.
International surveys TIMSS, PISA, PIRLS. (2017). Cambridge Assessment international Education. Retrieved from https://www.cambridgeinternational.org/Images/271193-international-surveys-pisa-timss-pirls.pdf
This article show evidence of ACT scores drop on 2016. ACT officials attribute the drop to the increasing percentage of high school seniors who have taken the test. Generally, when a larger share of students take a test - in some cases encouraged by state requirements more than the students necessarily being college ready - scores go down.
Jaschnik, S. (2016, August). ACT Scores Drop as More Take Test. Inside Higher Ed. Retrieved from https://www.insidehighered.com/news/2016/08/24/average-act-scores-drop-more-people-take-test
PISA measures the performance of 15-year-old students in science, reading, and mathematics literacy every 3 years. PISA uses the term "literacy" in each subject area to indicate how well students are able to apply their knowledge and skills to problems in a real-life context.
Kastberg, D., Chan, J. Y., & Murray, G. (2016). Performance of US 15-Year-Old Students in Science, Reading, and Mathematics Literacy in an International Context: First Look at PISA 2015. NCES 2017-048. National Center for Education Statistics.
This is the twelfth edition of the Brown Center Report. Part I examines the latest data from state, national, or international assessments. This year the focus is on the latest results from the Progress in International Reading Literacy Study (PIRLS) and Trends in International Math and Science Study (TIMSS) released in December, 2012. Part II explores a perennial theme in education studies—the topics that never seem to go away in terms of research and debate. This year it’s on the controversial topics of tracking and ability grouping. Part III is on a prominent policy or program. This year’s analysis is on the national push for eighth graders to take algebra and other high school math courses.
Loveless, T. (2013). How well are American students learning? With sections on the latest international tests, tracking and ability grouping, and advanced math in 8th grade. The 2013 Brown Center Report on American Education. Retrieved from https://www.brookings.edu/wp-content/uploads/2016/06/2013-brown-center-report-web-3.pdf
This Brown Center Report (BCR) on American Education is the sixth and final edition in the third volume and the 16th issue overall. The series began in 2000. As in the past, the report comprises three studies. Also in keeping with tradition, the first section features recent results from state, national, or international assessments; the second section investigates a thematic topic in education, either by collecting new data or by analyzing existing empirical evidence in a novel way; and the third section looks at one or more education policies.
Loveless, T. (2017). How Well Are American Students Learning? With Sections on the Latest International test Scores, Foreign Exchange Students, and School Suspensions. The 2-17 Brown Center Report on American Education. Retrieved from https://www.brookings.edu/wp-content/uploads/2017/03/2017-brown-center-report-on-american-education.pdf
The evidence in this paper suggest that schools can improve student learning by encouraging teachers and students to set their sights high.
Lumsden, L. S. (1997). Expectations for students.
This article describe about the drop down of SAT score in 2016.
Mulhere, K. (2016, September). SAT Scores Take a Dip. Money. Retrieved from http://money.com/money/4508286/average-sat-scores-class-2016/
This report attempts to summarize the most important and interesting trends emerging from TIMSS across the past two decades. The report is organized from macro to micro perspectives. The first chapter provides an overview of student achievement worldwide. The second and third chapters explore curriculum and instruction. The fourth and fifth chapters narrow the focus to two topics of interest among policymakers.
Mullis, I. V., Martin, M. O., & Loveless, T. (20). years of TIMSS: International trends in mathematics and science achievement, curriculum, and instruction. TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College and International Association for the Evaluation of Educational Achievement (IEA).
This report examines the educational progress and challenges students face in the United States by race/ethnicity. This report shows that, over time, students in the racial/ethnic groups of White, Black, Hispanic, Asian, Native Hawaiian or Other Pacific Islander, American Indian/Alaska Native, and Two or more races have completed high school and continued their education in college in increasing numbers. Despite these gains, the rate of progress has varied among these racial/ethnic groups and differences by race/ethnicity persist in terms of increases in attainment and progress on key indicators of educational performance.
Musu-Gillette, L., Robinson, J., McFarland, J., KewalRamani, A., Zhang, A., & Wilkinson-Flicker, S. (2016). Status and Trends in the Education of Racial and Ethnic Groups 2016. NCES 2016-007. National Center for Education Statistics.
With an unprecedented data set, Stanford researchers review more than 200 million test scores to spotlight communities with the nation’s worst academic achievement gaps. The research also revealed that nearly all U.S. school districts with substantial minority populations have large achievement gaps between their white and black and white and Hispanic students.
Rabinovitz, J. (2016). Local education inequities across US revealed in new Stanford data set. Retrieved from Stanford News website http://news. stanford. edu/2016/04/29/local-education-inequities-across-us-revealed-newstanford-data-set.
In this paper, we analyze racial differences in the math section of the general SAT test, using publicly available College Board population data for all of the nearly 1.7 million college-bound seniors in 2015 who took the SAT. The evidence for a stubborn race gap on this test does meanwhile provide a snapshot into the extraordinary magnitude of racial inequality in contemporary American society. Standardized tests are often seen as mechanisms for meritocracy, ensuring fairness in terms of access. But test scores reflect accumulated advantages and disadvantages in each day of life up the one on which the test is taken. Race gaps on the SAT hold up a mirror to racial inequities in society as a whole. Equalizing educational opportunities and human capital acquisition earlier is the only way to ensure fairer outcomes.
Reeves, R. V., Halikias, D. (2017). Race Gap in SAT scores highlight inequality and Hinder Upward Mobility. Brookings. Retrieved from https://www.brookings.edu/research/race-gaps-in-sat-scores-highlight-inequality-and-hinder-upward-mobility/
This article show the evidence for a race gap on the SAT math score and some big issues at stake including: the value of the SAT itself; the case for broader policies to take into account socioeconomic background in college admissions; the obsession with four-year college degrees; and the danger of college as a “bottleneck” in the American opportunity structure.
Reeves, Richard. (2017, February). Race Gap in SAT Math Score are as big as Ever. Brown Center Chalkboard. Retrieved from https://www.brookings.edu/blog/brown-center-chalkboard/2017/02/01/race-gaps-in-sat-math-scores-are-as-big-as-ever/
This table allows you to compare a student’s SAT® scores with the performance of other 2012 college-bound seniors who took the test some time in high school. Please keep in mind that relationships between test scores and other factors are complex and interdependent. Other factors do not directly affect test performance; rather, they are associated with educational experiences both on tests and in schoolwork.
SAT® Percentile Ranks for 2012 College-Bound Seniors: Critical Reading, Mathematics and Writing Percentile Ranks by Gender and Ethnic Groups. (2012). The College Board. Retrieved from http://secure-media.collegeboard.org/digitalServices/pdf/research/SAT-Percentile-Ranks-by-Gender-Ethnicity-2012.pdf
This article provides an overview of contextual factors across the levels of an educational system that influence implementation.
Schaughency, E., & Ervin, R. (2006). Building Capacity to Implement and Sustain Effective Practices to Better Serve Children. School Psychology Review, 35(2), 155-166. Retrieved from http://eric.ed.gov/?id=EJ788242
This paper highlight the important of effective feedback to help educators grow and allow students to improve. . This paper identify a definition of effective feedback and the key attributes of effective feedback.
Schimmer, T. (2018). The Nonnegotiable Attributes of Effective Feedback. Retrieved from https://fs24.formsite.com/edweek/form509/fill?7=EDWEEKBOX
In this paper, student-level indicators of opportunity to learn (OTL) included in the 2012 Programme for International Student Assessment are used to explore the joint relationship of OTL and socioeconomic status (SES) to student mathematics literacy. This paper suggest that in most countries, the organization and policies defining content exposure may exacerbate educational inequalities.
Schmidt, W. H., Burroughs, N. A., Zoido, P., & Houang, R. T. (2015). The role of schooling in perpetuating educational inequality: An international perspective. Educational Researcher, 44(7), 371-386.
Schoenwald, S. K., & Hoagwood, K. (2001). Effectiveness, transportability, and dissemination of interventions: What matters when?. Psychiatric services, 52(9), 1190-1197.
This article pointing some findings about achievement gap within school.
Sparks, S. D. (2015). Studies Probe How Schools Widen Achievement Gaps. Education Week. Retrieved from https://www.edweek.org/ew/articles/2015/10/07/schools-help-widen-academic-gaps-studies-find.html
Response to Intervention depends on regular, routine monitoring of student progress. This paper describes a multi-component approach to monitoring progress.
Stecker, P. M., Fuchs, D., & Fuchs, L. S. (2008). Progress Monitoring as Essential Practice Within Response to Intervention. Rural Special Education Quarterly, 27(4), 10-17.
This article reviews the efficacy of curriculum-based measurement as a methodology for enhancing student achievement in reading and math. Variables that contribute to the benefit of curriculum-based measurement are discussed.
Stecker, P. M., Fuchs, L. S., & Fuchs, D. (2005). Using Curriculum-Based Measurement to Improve Student Achievement: Review of Research. Psychology in the Schools, 42(8), 795-819.
The authors propose a model for using curriculum-based measurement to monitor and improve student achievement.
Stecker, P. M., Lembke, E. S., & Foegen, A. (2008). Using Progress-Monitoring Data to Improve Instructional Decision Making. Preventing School Failure, 52(2), 48-58.
The purpose of this document is to provide background information that will be useful in interpreting the 2007 results from the Trends in International Mathematics and Science Study (TIMSS) by comparing its design, features, framework, and items with those of the U.S. National Assessment of Educational Progress and another international assessment in which the United States participates, the Program for International Student Assessment (PISA). The report found, because there are differences in the features, frameworks and items of the national and international assessments, direct comparisons among the assessments are not useful. Rather the results from different studies should be thought of as different lenses through which to view and better understand U.S. student performance.
Stephens, M., and Coleman, M. (2007). Comparing TIMSS with NAEP and PISA in Mathematics and Science. U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from
This document provide background information that will be useful in interpreting the results from two key international assessments that are being released in November and December 2007 and in comparing these results with recent findings from the U.S. National Assessment of Educational Progress in similar subjects. In sum, there appears to be an advantage in capitalizing on the complementary information presented in national and international assessments. NAEP measures in detail the reading, mathematics and science knowledge of U.S. students as a whole, and can also provide trend information for individual states, different geographic regions, and demographic population groups. International assessments like PIRLS and PISA add value by providing a method for comparing our performance in the United States to the performance of students in other nations. However, their differences need to be recognized when interpreting results.
Stephens, M., Coleman, M. (2007). Comparing PIRLS and PISA with NAEP in Reading, Mathematics, and Science (Working Paper). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https://nces.ed.gov/surveys/PISA/pdf/comppaper12082004.pdf
This meta-analysis examines the impact of team-based learning strategies on achievement and student engagement. The study finds that team-based strategies were found to have a positive impact on grades, test performance, and engagement.
Swanson, E., McCulley, L. V., Osman, D. J., Scammacca Lewis, N., & Solis, M. (2017). The effect of team-based learning on content knowledge: A meta-analysis. Active Learning in Higher Education, 1469787417731201.
This report compares the performance of U.S. students with their peers around the world and also examines how the reading literacy of U.S. 4th-grade students has changed since the first administration of PIRLS in 2001- 2006. Results are presented by two student characteristics (sex and race/ethnicity) and by one measure of school poverty (percent of students in the school eligible for free or reduced price lunch). All differences described in this report are statistically significant at the .05 level. No statistical adjustments to account for multiple comparisons were used.
Thompson, S., Provasnik, S., Kastberg, D., Ferraro, D., Lemanski, N., Roey, S., & Jenkins, F. (2012). Highlights from PIRLS 2011: Reading Achievement of US Fourth-Grade Students in an International Context. NCES 2013-010. National Center for Education Statistics. Retrieved from https://files.eric.ed.gov/fulltext/ED537758.pdf
This article show different approach that researcher took to answer questions on social gradient in education between the countries. Comparing some of these results highlights weak service delivery in many developing countries. Even where resources may be similar, social gradients are steep in some, indicating much worse educational outcomes for the poor. And public resources are often extremely poorly converted into learning. The differential ability of schools and school systems to convert resources into learning outcomes remains a major impediment to improving educational outcomes, and indeed life chances, for the poor.
Van Der Berg, S. (2015). How does the rich-poor learning gap vary across countries?. Brookings Institution. Retrieved from https://www.brookings.edu/blog/future-development/2015/03/09/how-does-the-rich-poor-learning-gap-vary-across-countries/
Results of this meta‐analysis research, testing for a moderator effect, show that support for the overjustification effect occurs only when intrinsic motivation is operationalized as task behaviour during a free‐time measure.
Wiersma, U. (1992). The effects of extrinsic rewards in intrinsic motivation: A meta-analysis.
The author makes the case that rapid assessment can identify struggling students who can then be provided intensive instruction so their performance on high stakes tests is improved.
Yeh, S. S. (2006). Can Rapid Assessment Moderate the Consequences of High-Stakes Testing. Education & Urban Society, 39(1), 91-112.
The author reports data suggesting that the systematic use of formative assessment can reduce the pressure on teachers that they experience with high stakes testing.
Yeh, S. S. (2006). High-stakes testing: Can rapid assessment reduce the pressure?. Teachers College Record, 108(4).
This study compares the effect size and return on investment for rapid assessment, between, increased spending, voucher programs, charter schools, and increased accountability.
Yeh, S. S. (2007). The cost-effectiveness of five policies for improving student achievement. American Journal of Evaluation, 28(4), 416-436.
The author compares the effectiness of comprehensive school reform relative to rapid progress monitoring. Progress monitoring results in much greater benefit than comprehensive school reform.
Yeh, S. S. (2008). The Cost-Effectiveness of Comprehensive School Reform and Rapid Assessment. Education Policy Analysis Archives, 16(13), 1-32.
The authors examine the effectiveness of replacing low performing teachers relative to using formative assessment as a means of increasing student outcomes.
Yeh, S. S., & Ritter, J. (2009). The Cost-Effectiveness of Replacing the Bottom Quartile of Novice Teachers Through Value-Added Teacher Assessment. Journal of Education Finance, 34(4), 426-451.
This study employed a meta-analysis method to combine the results of experimental studies on the effect of teaching learning strategies on students’ academic achievement. This study indicated that the learning strategies had 26.8% positive effect on students’ academic achievement.
YILDIRIM, I., CIRAK-KURT, S., & SEN, S. (2019). The Effect of Teaching” Learning Strategies” on Academic Achievement: A Meta-Analysis Study. Eurasian Journal of Educational Research (EJER), (79).
The Technical Assistance Center on PBIS provides support states, districts and schools to establish, scale-up and sustain the PBIS framework.