Statement of Problem

1. The Impact of Kindergarten Entrance Age on Academic Achievement: A Longitudinal StudySara NajarroPrincipal Stanton Elementary SchoolGlendora Unified School District

2. Statement of Problem • Kindergarten Readiness Act- 2010 • Phase in Change of Cut off Date • Currently Dec 2nd. • Students can begin school as early as four years nine months • 24 month age span in kinder • Research suggests enter when age eligible • Age eligible where? • Must study age of entry versus age eligible

3. Purpose of Study • Examine impact of chronological age on academic achievement through 4th gr. • Support or combat red shirting and examine possible influences to retention • Examine optimal school age entry in a large urban school district in southern California • Investigate fall entry students in terms of academic, social and behavior school progress through grade four

4. Research Questions • How does entry age of kindergarten students impact student achievement scores in reading and math, retention rates and placement into special education programs? • Do students who begin kindergarten at age four years nine months (who do not turn five until they have been in kindergarten) have lower achievement scores on reading and math benchmark assessments in grade two, three or four? • Are younger entrants more likely to be retained in kindergarten or later? • Do younger entrants have a higher probability of being classified as special education?

5. Theoretical Framework • Inconsistent research results • Younger entrants not perform as well as older in kinder and first (Apollini, McClure, Vaughan & Vaughan, 1997). • ECLS-K found almost all kindergarten students were 5-5.8 when they began only 9% not yet 5. (2001) • National Institute of Child Health and Human Development (2007) examined entry age and academic and social achievement found age of entry impacts small

6. Background of Study • Previous research focus on summer vs. winter • Small performance gap did not last past 5th grade (Oshima and Domaleski, 2006) • Warder (1999)-literacy and birth date- 64% older students at grade level, younger decreased in test scores • Lincove and Painter (2006) young children more likely to repeat a grade. • Gender accounts for small part in variation of skills (ECLS-K data, Crosser, 1991).

7. Literature Review • Summary of Literature Review Includes: • Understanding kindergarten policies • Entrance age and cutoff dates • California Kindergarten specifics • School readiness • Language Acquisition skills related to academic success • Developmental levels • Prior school experiences • Readiness skills • Academic Red-Shirting and Retention • Special Education and age of entry • Entrance Age and Achievement studies-multiple opinions

8. Summary of Literature Review • Inconclusive research • First experiences shape educational future • Questions that are still unanswered include: • Is there an optimal school entry age? • Will children who are older outperform their younger counterparts? • Necessary research in this area of school entry age and achievement in a large urban school district to support decisions.

9. Methodology • Research Design • Quantitative- statistical data analysis • Longitudinal correlation study • Non-experimental- no control group-data in natural environment • Pre-existing data base- large urban school district • Secondary source of data collection • Explanatory in nature in that its primary purpose is to explain the phenomenon of age of entry related to academic achievement

10. Sampling and Data Collection • Convenience sampling • Large urban school district • Over five years 2005-06 through current year data available 2009-2010 • 29 elementary schools • 77% free and reduced lunch • 46.7% ELL • 10.2% special education • Approx. 12,000 students

11. Sample and Data Collection • Divided into three cohorts • Cohort 1 enrolled in 2005-2006 through 2009-2010 (K-4) • Cohort 2 enrolled in 2006-2007 through 2009-2010 (K-3) • Cohort 3 enrolled in 2007-2008 through 2009-2010 (K-2) • Younger Entrants- August, September, October, November, December 1st and 2nd • Older Entrants- December 3rd and on, January, February, and March • Middle Entrants- April, May, June, and July

12. Measures • Independent Variables: • Entrance age • Gender • Current EL level • Dependent Variables: • Kindergarten through fourth grade ELA benchmark scores (fluency and reading comprehension); Math benchmark (overall percentage); 2-4 grade California State Assessment scores in ELA and Math • Retention Rates • Special Education Classification

13. Data Collection and Procedures • Request to school district • Permission granted • Technology provided data set-from Zangle and Oars- demographics, birth date, school entry date, gender, ethnicity, El level, academic achievement scores on benchmark, CST scores, retention information and special education enrollment data. • No identifying information was provided for confidentiality • IRB request from APU for expedited review and approved.

14. Analytical Strategy • Inferential Statistics: • Logistic Regression- • significant predictors for each criterion variable • Chi Square – • Chi Square and odds ratio examined to reveal nature of relationship between categorical variables

15. Analytical Strategy Each variable re-coded to new variables • Gender –male 0; female 1 • English Learner- ELL 0; EO 1 • Retention- no 0; yes 1 • Special education- no 0 ; yes 1 • Birth date- younger 1; middle 2; older 3 • Academic achievement- benchmark at risk 0 and at benchmark 1 K-4; CST below proficiency 0 and proficient and above 1 grades 2-4. • Employed in same manner for each cohort

16. Null Hypothesis • HƟ1: There is no difference in CST and benchmark scores in ELA of students in grades K, 1, 2, 3, and 4 based on students' entrance age, gender, and ELL level. • HƟ2: There is no difference in CST and benchmark scores in Math of students in grades K, 1, 2, 3, and 4 based on students' entrance age, gender, and ELL level. • HƟ3: There is no difference in retention rates of students in grades K, 1, 2, 3, and 4 based on students' entrance age. • HƟ4: There is no difference in special education classification of students in grades K, 1, 2, 3, and 4 based on students' entrance age.

17. Results • Cohort One: (2005-2006 thru 2009-2010) • Descriptive Statistics • 4772 students • 36.5% younger, 31.4% middle, 31.9% older • 61.8% EO and 38.2% ELL • 11% retention students • 9% special education

18. Cohort One- Hypothesis 1 • Significant relationship between entrance age and academic performance defined by reading comprehension 1-4 • Not a significant relationship with reading fluency in all grades • Significant relationship between entrance age and upper and lower case letter naming fluency and high frequency words in kindergarten. • Significant relationship between entrance age and academic performance on ELA-CST grades 2-4 • Grade 2 66.3% of younger entrants were at risk while 54.9% older entrants at risk • Grade 3 76.5% of the younger entrants at risk 65% older at risk– 72.4% of younger entrants below statewide proficiency; 58.2% older entrants • Older entrants in kindergarten 1.6 times more likely to meet benchmark standards • Older entrants in grade 4 were 2.3 times more likely to score proficient 4th gr. CST ELA. • ELL a factor; Gender not a significant factor

19. ELA Chi Square Values of Entrance Age and Benchmark/CST Proficiency by Grade Level Grade/Benchmark N % young % old χ2p__ Kinder Upper-Case 2585 24.4 17.0 15.45 .00 Kinder Lower-Case 2586 33.5 27.5 27.64 .00 Kinder High Frequency 2584 52.9 40.3 28.00 .00 First Avg. Fluency 2210 52.3 47.3 4.66 .10 First Reading Comp. 2988 40.4 31.1 19.39 .00 Sec Avg. Fluency 2856 55.8 52.1 2.96 .23 Sec Reading Comp. 2956 66.3 54.9 29.59 .00 Third Avg. Fluency 2919 57.7 52.3 6.09 .05 Third Rdng Comp. 2956 76.5 65.0 33.01 .00 Fourth Avg. Fluency 1942 46.7 40.0 5.90 .06 Fourth Rdng Comp. 2972 68.5 58.5 22.19 .00 Second CST 3015 65.1 55.7 19.03 .00 Third CST 2844 72.4 58.2 43.2 .00 Fourth CST 2770 49.3 35.9 36.67 .00

20. % of younger entrants vs. older entrants at risk on benchmark or CST for ELA

21. Cohort 1- Hypothesis 2 • Significant relationship between entrance age and academic performance as defined by math benchmark in first, third and fourth grade. Not second grade • Significant relationship between entrance age and academic performance on Math-CST grades 2-4 • Grade 3 64.3% of younger entrants at risk with 46% older entrants at risk • Grade 2 CST 59.4% of younger entrants were below proficiency with 48.4% older entrants below proficiency. • Older entrants 2 times more likely to pass third grade math benchmark. • Grades 2,3, and 4 older entrants 1.5 times more likely to score proficient on CST • Gender not significant; ELL a factor

22. Math Chi Square Values of Entrance Age and Benchmark/CST Proficiency by Grade Level • Grade/Benchmark N %young %old χ2p • First Math 2934 18.2 12.8 11.38 .00 • Second Math 2944 25.8 22.9 4.15 .13 • Third Math 2675 64.3 46 17.68 .00 • Fourth Math 2949 54.6 46.3 13.73 .00 • Second CST Math 3016 59.4 48.4 25.38 .00 • Third CST Math 2860 48.5 37.2 25.48 .00 • Fourth CST Math 2811 43.8 32.5 26.93 .00

23. % of younger entrants vs. older entrants at risk on benchmark or CST for Math

24. Cohort 1-Hypotheses 3 and 4 • Significant relationship between entrance age and retention rates. 13.8% younger entrants more likely to be retained—7.9% of older entrants • No significant relationship between entrance age and special education qualification.

25. Pattern of Cohorts • Odds ratio of cohort one described how older entrants have a higher likelihood of being successful on grade level benchmarks and CST • Cohort two and three odds ratio presented similar results. • Confirmed the model • Entrance age, and ELL were a significant model in predicting performance proficiency in ELA and Math over time and multiple assessments.

26. Odds Ratio for entrance age and ELA performance

27. Odds Ratio for entrance age and Math performance

28. Odds ratio for ELL and ELA and Math performance • Larger than entrance age-indicative of the current achievement gap between ELL and EO • Impact of ELL stronger for language arts assessment than math. • For each cohort the likelihood of proficient performance for older entrants repeats for each cohort and increases as the students move through the grade levels.

29. Summary of Findings • Entrance age and ELL has a significant impact on the area of academic achievement in reading comprehension benchmark, math benchmark and proficiency on CST ELA and Math. • Two areas not impacted by entrance age • Average end of year fluency • Second grade math for cohort one • Gender was not found to be a contributing factor to the model • Entrance age and retention rates were significant in all three cohorts • Entrance age and special education not significant in all three cohorts

30. Conclusions • Findings suggest that younger entrants (in this study-fall entrants) have a higher likelihood of being at-risk as measured by benchmark and CST • Students should turn five prior to starting school (Younger entrants not yet five upon starting school) • Unlike past research did not find entrance age impact became less significant over time (de Cos, 1997 & Lin, Freeman, & Chu, 2009), • Supports previous inconsistencies regarding gender impacts

31. Discussion • Younger entrants more likely to score below proficiency • Age impact lasts over time • Younger entrants higher likelihood to be below grade level standards over time • Age becomes a risk factor • ELL younger entrant more likely to score below proficiency than an EO younger entrant. • ELL strong factor along with entrance age

32. Discussion/Recommendations • Entrance age and ELL proficiency significantly impact academic achievement scores in reading and math. • Students who begin school prior to turning five, the younger entrants, are more likely to be at risk on benchmark assessments and state assessments. • The younger entrants are more likely to be retained in kindergarten through 4th grade. • The younger entrants do not have a higher probability of being classified as special education students. • Beginning school after turning five would be considered a significant factor in determining school success.

33. Significance of Study • Understand age gap in kindergarten • Support continued implementation for SB 1381 and preschool programs- empirical evidence for support • Add research data when developing and adopting common kindergarten standards • Data in determining school entry and decisions in regards to retention and at-risk younger students. • Guide decisions in regards to transitional pre-k/k programs • Consistency of entrance age across states could promote educational opportunity equity

34. Recommendation for Further Research • Additional research with students from various SES, preschool or no preschool attendance and more diverse populations • Draw samples from various school districts • i.e. suburban school district • Additional grade levels and/or subject areas • Path model using a Structural Equation Model could be used to determine the impact of school entrance age on academic achievement through a moderating variable such as earlier academic achievement. • As law is implemented compare two groups those students who entered when cut off was December 2nd and those entering kindergarten with cut off September 1st

35. Thank you! • What questions do you have?