Statement of ProblemKindergarten Readiness Act- 2010Phase in Change of Cut off DateCurrently Dec 2nd.Students can begin school as early as four
years nine months24 month age span in kinderResearch suggests enter when age eligibleAge eligible where?Must study age of entry versus age eligible
Purpose of StudyExamine impact of chronological age on
academic achievement through 4th gr. Support or combat red shirting and examine
possible influences to retentionExamine optimal school age entry in a large
urban school district in southern CaliforniaInvestigate fall entry students in terms of
academic, social and behavior school progress through grade four
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?
Theoretical Framework Inconsistent research resultsYounger 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
Background of StudyPrevious 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).
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
Summary of Literature ReviewInconclusive researchFirst experiences shape educational futureQuestions 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.
MethodologyResearch Design
Quantitative- statistical data analysisLongitudinal correlation study Non-experimental- no control group-data in
natural environmentPre-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
Sampling and Data CollectionConvenience sampling
Large urban school districtOver five years 2005-06 through current year
data available 2009-201029 elementary schools77% free and reduced lunch46.7% ELL10.2% special educationApprox. 12,000 students
Sample and Data CollectionDivided 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
MeasuresIndependent Variables:
Entrance ageGenderCurrent 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 RatesSpecial Education Classification
Data Collection and ProceduresRequest to school districtPermission grantedTechnology 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.
Analytical StrategyInferential 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
Analytical StrategyEach variable re-coded to new variablesGender –male 0; female 1English Learner- ELL 0; EO 1Retention- no 0; yes 1Special education- no 0 ; yes 1Birth date- younger 1; middle 2; older 3Academic 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
Null HypothesisHƟ1: 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.
ResultsCohort One: (2005-2006 thru 2009-2010)Descriptive Statistics
4772 students36.5% younger, 31.4% middle, 31.9% older61.8% EO and 38.2% ELL11% retention students9% special education
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
ELA Chi Square Values of Entrance Age and Benchmark/CST Proficiency by Grade Level
Grade/Benchmark N % young % old χ2 p__Kinder Upper-Case 2585 24.4 17.0 15.45 .00Kinder Lower-Case 2586 33.5 27.5 27.64 .00Kinder High Frequency 2584 52.9 40.3 28.00 .00First Avg. Fluency 2210 52.3 47.3 4.66 .10First Reading Comp. 2988 40.4 31.1 19.39 .00Sec Avg. Fluency 2856 55.8 52.1 2.96 .23Sec Reading Comp. 2956 66.3 54.9 29.59 .00Third Avg. Fluency 2919 57.7 52.3 6.09 .05Third Rdng Comp. 2956 76.5 65.0 33.01 .00Fourth Avg. Fluency 1942 46.7 40.0 5.90 .06Fourth Rdng Comp. 2972 68.5 58.5 22.19 .00Second CST 3015 65.1 55.7 19.03 .00Third CST 2844 72.4 58.2 43.2 .00Fourth CST 2770 49.3 35.9 36.67 .00
% of younger entrants vs. older entrants at risk on benchmark or CST for ELA
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
Math Chi Square Values of Entrance Age and Benchmark/CST Proficiency by Grade Level
Grade/Benchmark N %young %old χ2 pFirst Math 2934 18.2 12.8 11.38 .00Second Math 2944 25.8 22.9 4.15 .13Third Math 2675 64.3 46 17.68 .00Fourth Math 2949 54.6 46.3 13.73 .00Second CST Math 3016 59.4 48.4 25.38 .00Third CST Math 2860 48.5 37.2 25.48 .00Fourth CST Math 2811 43.8 32.5 26.93 .00
% of younger entrants vs. older entrants at risk on benchmark or CST for Math
Cohort 1-Hypotheses 3 and 4Significant 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.
Pattern of CohortsOdds 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.
Grade 05-06 cohort 06-07 cohort 07-08 cohort
K Lower Case 1.28 1.23 1.32
1 Reading Comp 1.18 1.15 1.18
2 Reading Comp 1.25 1.19 1.23
3 Reading Comp 1.31 1.20 N/A
4 Reading Comp 1.20 N/A N/A
2 CST 1.20 1.19 1.25
3 CST 1.38 1.24 N/A
4 CST 1.53 N/A N/A
Odds Ratio for entrance age and ELA performance
Odds Ratio for entrance age and Math performance
Grade 05-06 cohort 06-07 cohort 07-08 cohort
K math benchmark N/A 1.47 1.49
1 math benchmark 1.20 1.37 1.33
2 math benchmark P>.01 1.30 1.29
3 math benchmark 1.40 1.15 N/A
4 math benchmark 1.10 N/A N/A
2 CST 1.22 1.25 1.39
3 CST 1.22 1.12 N/A
4 CST 1.22 N/A N/A
Odds ratio for ELL and ELA and Math performanceLarger 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.
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
ConclusionsFindings 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
DiscussionYounger entrants more likely to score below
proficiencyAge 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
Discussion/RecommendationsEntrance 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.
Significance of StudyUnderstand age gap in kindergartenSupport continued implementation for SB 1381 and
preschool programs- empirical evidence for supportAdd 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
programsConsistency of entrance age across states could
promote educational opportunity equity
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
Thank you!What questions do you have?