does timing of retention make a difference

8/14/2019 Does Timing of Retention Make a Difference

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School Psychology Review,2006, Volume 35, No. 1, pp. 134-141

RESEARCH BRIEEDoes the Timing of Grade Retention Make a Difference?Examining the Effects of Early Versus Later Retention

Benjamin SilberglittSt. Croix River Education District

Shane R. JimersonUniversity of California Santa Barbara

Matthew K. Burns and James J. AppletonUniversity of Minnesota

Abstract. Research examining the effectiveness of grade retention has providedoverwhelming and seemingly irrefutahle evidence that grade retention is anineffective and potentially harmful practice. However, proponents of grade re-tention often advocate that retention in the early elementary grades (e.g., kinder-garten, first and second grade) is the justified exception. This longitudinal studyexamined the reading growth trajectories of students (n = 49) from first througheighth grade. Hierarchical linear modeling analytic procedures provided novelinsights regarding the relative reading growth trajectories among retained stu-dents, comparing those students retained in kindergarten through second gradewith those students retained in Grades 3-6. The results revealed that the growthtrajectories of students retained early (Grades K-2) were comparable to thoseretained later (Grades 3-5). These findings failed to support the efficacy ofretention at an earlier grade in elementary school.

Grade retention, defined as requiring a quently used and controversial interventionstudent to remain at his or her current grade (Jimerson. Pletcher, Graydon, Schnurr, Nick-level the following school year despite spend- erson, & Kindert, 2006). Approximately 2.4ing a full school year at that given grade million children, or 5-10% of the school-aged(Jackson, 1975), remains a relatively fre- population, have been retained each year


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Effect of Early Versus Later Grade Retention

(Dawson, 1998), but meta-analytic researchhas consistently revealed small to moderatemean effect sizes that favored the academicand socioemotional development of promotedcomparison groups over groups of retainedchildren (Holmes. 1989; Holmes & M atthews,1984; Jimerson, 2001).Longitudinal research also has failed todemonstrate an overall positive effect forgrade retention as an intervention. Short-termgains in mathematics skills have been noted,but higher absenteeism and lower social-emotional rankings among retained children ascompared to a group of promoted childrenhave also been found (Jimerson, Carlson,Rotert, Egeland, & Sroufe, 1997). Moreover,grade retention has been linked to increasedrisk for dropping out of school to the extentthat early grade retention has been "one of themost powerful predictors of later school with-drawal" (Jimerson, Anderson, & Whipple,2002, p. 452 ). iGenerally speaking, research has notsupported retention and suggested negative ef-

fects, so why are students retained? Graderetention seems to hold an intuitive appealdespite a lack of empirical support. It alsoseems intuitively advantageous to retain achild earlier (e.g., by second grade) rather thanlater (e.g., third grade or later). Students arepurportedly retained in early elementarygrades to prevent future failure, and are re-tained in high school to prevent graduation bystudetits who lack the basic skills necessaryfor post-high school success (Martinez &Vandergrift, 1991). Thus, retention before sec-ond grade is viewed as an early intervention ora preventative measure. Graue and DiPema(2000) found that delayed entry into kinder-garten led to academic skills consistent withpeers, and early-retained students were moreadvanced than students who were retained in alater grade. These data supported early reten-tion as prevention hypothesis, but a review ofthe literature did not reveal any studies thatexamined timing of retention, rather than re-

grade) linked to better short- and long-termoutcomes relative to retention in later grades(third through fifth)?

MethodParticipants

Participants were 49 students, from fivedistricts in rural and suburban Minnesota, di-vided into two groups. The participatingschool districts did not have any recorded pol-icy or standard procedure for student reten-tions or retention decisions. The participatingstudents were all of the retained studentswithin those districts with complete data forGrades K-8. Students were assigned to one oftwo groups based on grade of retention,with 27 students who were early retained(Grades K-2) and 22 who were later retained(Grades 3-5 ). The students included 17 (35%)females and 32 (65%) males. The ethnicity ofthe total sample was 6.1% African Ameri-can, 2.0% Asian, 85.7% Caucasian, and 6.1%Native American. For the total sample, 29(59%) students were eligible for free or re-duced price lunch for at least 1 school yearduring the study: 16 (59%) from the early-retained group and 13 (59% ) from the later-retained group. Finally, 2 (4%) students wereretained in kindergarten, 19 (39%) in firstgrade, 6 (12%) in second grade, 9 (18%) inthird grade, 8 (16%) in fourth grade, and 5(10%) in fifth grade.Procedures

The school districts that the students at-tended administered curriculum-based mea-sures for reading assessment every fall, winter,and spring for Grades I- 8, with the exceptionof fall for first grade . AU administrations wereconducted by trained school personnel usingstandardized procedures (Shinn, 1989). In to-tal, there were 23 data points possible for eachparticipant, but missing data were possible forsome participants. Data were compiled over


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School Psychology Review, 2006, Volume 35, No. 1

grades by 2003-2004, or participants werealready in a later grade in 1996-1997). Theproportion of waves completed across the en-tire sample was 47%.Measures

The Reading-Curriculum Based Mea-surement (R-CB M ) m easure consisted of threel-min reading passages for each benchmarkassessment (fall, winter, spring). Passageswere standardized at grade-appropriate diffi-culty as suggested by Howe and Shinn (2002),and were curriculum independent, grade-levelappropriate, and of equal difficulty withineach grade level. Student data consisted of themedian number of words read correctly acrossthe three passages for each assessment. Read-ing was assessed because most academic re-ferrals to school psychologists were for read-ing deficits (Bramlett, Murphy, Johnson,Wallingsford, & Hall, 2002), and reading isclearly an important skill for subsequentknowledge acquisition. Because of the numberof students being assessed within the districtassessment plan and the simplicity of the mea-sure to administer and score, interrater reli-ability was not systematically collected duringthese district-wide data collection efforts. Pastresearch on R-CBM has demonstrated test-retest reliability of 0.92 and interrater reliabil-ity of 0.99 (Marston, 1989).Analysis

Research methodologies frequently usedto examine change in variables for individualshave not allowed for explicit modeling of in-dividual differences in growth, which can bestbe addressed with hierarchical linear modeling(HLM; Bryk & Raudenbush, 1992). Thus, R-CBM growth rates across Grades 1-8 for stu-dents retained in early grades (K-2) werecompared to those retained in later grades(3-5). The 23 total waves of data were used toconduct an HLM analysis using a randomeffects covariance structure.

LMMs are useful for analyzing longitudinaldata, where the assumption of independencebetween measurements cannot be met, be-cause the measurem ents are nested within stu-dents, and in this case, students are nestedwithin the early-retained and later-retainedgroups. The random effects structure allowsindividual students to vary on ail parametersbeing estimated, while still providing group-level estimates more appropriate than thosegenerated by traditional regression models. Inthis analysis, the Level I equation modelsindividual growth over time. For each individ-ual ( at time j , the Level I equation is asfollows:

, V , y = + (1 )In the Level 1 equation, qu adraticgrowth is modeled for each student, with c,yrepresenting error. The Level 2 equations thenmodel group differences in each of these betavalues. In these equations, g refers to group

membership (early retained or later retained),and b is the error term. Level 2 equations areas follows:o. = Po + +

+ Psg, +

(2 )(3 )(4 )

LMMs also allow for missing data, acommon occurrence when conducting longi-tudinal studies over a large time span. In thisstudy, data were assumed to be missing atrandom. LMMs also assume independence be-tween subjects, an assumption that can be ad-dressed by sampling randomly from the pop-ulation. Although this sample is admittedly asmall sample from a single region of the coun-try, we have assumed this premise has beenmet for the sake of these analyses, and recog-nize the limitations of our sample. A final


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ResultsThe variance-covariance matrix re-

vealed increasing variance across the waves ofthe study, with decay. As the amount of timebetween R-CBM measurements increased, thedegree of covariance between the scores onthose measurements decreased. In addition, ahigher amount of variance was found for R-CBM scores from higher grade levels. Level 1analysis generated an individual slope (includ-ing linear and quadratic components) and in-tercept for each participant. Correlation be-tween the quadratic slope parameter estimatesand the intercept estimates across participantswas 0.23, indicating that the growth curvesof retained students with a higher initial level

of performance had a slight tendency to havea more negative quadratic bend. Correlationbetween the linear slope parameter estimatesand intercept estimates across participantswas 0.62, indicating a moderate to strong pos-itive correlation between beginning level ofperformance and the linear slope of growthamong retained students.

Level 2 analysis included a single dum-my-coded variable identifying group member-ship in the early (0) versus later (1) retentiongroups. Regression lines were drawn usingthese mean parameter estimates, as shown inFigure 1. Actual parameter estimates and re-sults of significance tests are shown in TablesI and 2. In each table, parameter estimates and

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20 -1 1 1 r -T 1 I 1 r


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Table 1Significance Tests of the Differences in Parameter Estimates forEarly'Retained (K-2) Versus Later-Retained (3-5) GroupsParameter ParameterEstimate SE

InterceptLinear slopeQuadratic .slopeLater-retained intercept^Later-retained linear slope"Later-retained quadratic slope*

24.8526.295- 0 . 0 2 3

-25 .4453.909

-0 .181

3.0281.2550.0585.1841.8320.082

4128.5

4.91-2.21


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Table 2Significance Tes t s of the Differences in the Linear Growth Component forEarly'Retained (K-2) Versus Later-Retained (3-5) Groups

ParameterParameterEstimate SE df

InterceptLinear slopeLater-retained intercept"Later-retained linear slope"

25.0306.051-14 .8670.756

3.1800.5904.9620.828 29.9 0.91 0.3684

"Parameter estimates for the later-retained group represent the difference between this group and the early-retainedgroup. The f tests examine the significance of these differences.

group. Although the differences in the linearcomponent of the slope for the two groups werenot statistically significant, they do appear tooffset the statistically significant difference inthe quadratic component. In effect, the practicaldifference In slope between these two groups isnegligible.1 '

. - DiscussionGrowth curves for the early- and later-retained students (Grades K-2 and 3-5, re-spectively) were modeled and compared usingHLM procedures. Reading data from tbe firstyear of the grade in which the student wasretained were removed before the growthcurves were modeled. The average readingscore in the winter of first grade (i.e., inter-cept) was significantly bigher for the grouptbat was retained earlier. This is somewbatunexpected, given that one would anticipate alower level of performance in the early gradesto be more likely to lead to a decision to retainimmediately. These data could support tbe rel-atively long-held belief that retention deci-sions are often made with teacher judgmentand otber subjective factors rather than aca-demic data (Cadigan, Entwisle, Alexander, &Pallas. 1988; Gloeckler, 1986).

larger negative bend in the growtb curve, andtbe early-retained group's growtb rate contin-ued in a linear fasbion. Tbis trend in tbegrowth curve suggested that students retainedlater had a more rapid deceleration of growtbcompared to the more consistent progress rateof the early-retained students. Rather than per-ceive this as a benefit for early retentions, it ispossible that these data are a result of a greaternegative effect from later retentions. Researchhas consistently found a negative socioemo-tional impact from grade retention (Holmes,1989; Holmes & Matthews. 1984; Jimerson,2001). It is possible that this effect is strongerfor students w bo are older, and m ore emotion-ally mature, at the time of retention. However,this is only one possible explanation of thisfinding, and previous researcb literature wasseemingly void of comparisons between ef-fects of early and later grade retention. Tbus,tbese data sbould be interpreted carefully, andreplication is needed before confident interpre-tations can be made.

Limitations and Suggestions for FutureResearchThe current study has presented datathat may be of interest to botb researcbers and


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group, with little assurance of equal child vari-ables prior to being retained. Therefore, repli-cation thai accounts for child-centered vari-ables (e.g., socioeconomic status, IQ, prere-tention skill level) is recommended for furtherinsights regarding tbe nature of growth forstudents retained earlier versus later in theireducational careers. Another limitation of thecurrent study is the lack of examination ofstudent perspectives of retention and the effectof risk factors upon student developmentaltrajectories (e.g., socioemotional outcomes).Myriad factors influence tbe development ofretained students (Jimerson et a l, 1997; Jimer-son, 2001; Jimerson et al., 2002). and includ-ing estimates of tbese variables would im-prove the study. Future retention researchcould also encompass a more comprebensivearray of tbe risk and protective factors imping-ing on the developmental trajectories of re-tained students. Furthermore, despite diversityof age, income (47% free and reduced lunch),and location (rural and suburban), tbis samplewas racially homogenous ( > 9 1 % White). Thegeneralizability of these data could be en-banced by including more diverse racial andcultural groups. Finally, tbe current study usedreading as the dependent variable, which is themost frequent academic deficit area. However,analyses examining other academic skills(e.g., mathematics) and outcomes throughhigh school would also be of great value inconsidering the effects of earlier and latergrade retention, especially given researchersuggestions of tbe effect of early retention(e.g., in first grade) on dropping out of higbscbooi (Alexander, Entwisle, & Horsey,1997).

Tbe analyses of longitudinal reading tra-jectories in this study revealed that early graderetention {kindergarten througb second grade)did not yield advantages in reading trajectoriesfrom first to eighth grade, relative to studentsretained later (third through fiftb grad es), but amore linear progress rate was noted. Altboughtbe idea of early retention has intuitive appeal,

achievement and adjustment, but research re-veals that the practice of grade retention is"nonsense," in that it appears to do more harmtban good (Jimerson, 2001). Neitber grade re-tention nor social promotion will adequatelyaddress tbe needs of students (Jimerson, 2001 ;Jimerson et al., 2006); rather, specific evi-dence-based interventions are required to pro-mote the cognitive and social competence ofstudents.

Refe rencesAlexander, K. L .. Enlwisle, D. R., & Horsey, C. S. (1997).From first grade forward; Early foundations of highschool dropout. Sociology of Education, 70(2), 87-107.Bramlett. R. K.. Murphy. J. J.. Johnson . J., Wallingsford,L., & Hall, J. D. (2002). Contemporary practices inschool psychology: A national survey of roles andreferral problems. Psychology in ihe Schools. 39, 3 2 7 -335.Bryk. A. S.. & Raudenbush. S. W. (1992). Hierarchicallinear models: Applications and data analysis meth-ods. Newbury Park. CA: Sage Publications.Cadigan. D.. Entwisle. D. R.. Alexander, K. L.. & Pallas,A. M. (1988). First-grade retention among low achiev-ing students: A search for significant predictors. Mer-rill-Palmer Quarterly, 34. 7 1 -8 8 .Dawson. P. (1998). A primer on student grade retention:What the research says. Communique. 26(8). 28-30.Fitzmaurice, G. M., Laird, N. M., & Ware. J. H. (2004).Applied longitudinal analysis. Hoboken. NJ: JohnWiley & Sons.Graue, E., & DiPema. J. (2000). Redshirting and earlyretention: Who gets the "gift of time" and what are itsoutcomes? American Educational Re.^tearch Joumal,37 , 5 0 9 -3 3 4 .Gloeckler, T. (1986). Data-based decision-making proce-dures for determining in-grade retention. Education,

107, 182-186.Hintze, J- M., & Silberglitt, B. (2005). A longitudinalexatnination of the diagnostic accuracy and predictivevalidity of R-CBM and high-stakes testing. SchoolP.iychology Review, 340), 372-386.Holmes, C. t . (1989). Grade-level retention effects: Ameta-analysis of research studies. In L. A. Shepard &M. L. Smith (Eds.) Flunking grades: Research andpolicies on retention (pp. 16-33 ). London: The FalmerPress.Holme.s. C. T.. & M anhew s, K. M. (1984). The effects ofnonpromotion on elementary and junior high schoolpupils: A meta-anatysis. Reviews of Educational Re-search, 54. 225-236.Howe, K. B., & Shinn. M. M. (2002). Standard readingassessment passages (RAPs) for u.'ie in General Out-


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' ' 1Jimerson, S. R. (2001). Meta-analysis of grade retentionresearch: Implications for practice in the 21st century.School Psychology Review, 30, 4 2 0 - 4 3 8 .Jimerson, S., Anderson, G. E.. & Whipple, A. D. (2002).Winning the battle and losing the war: Examining therelationship between grade retention and dropping outof high school. Psychology in the Schools, 39. 4 4 1 -457.Jimerson. S.. Carlson, E.. Rotert, M., Egeland, B., &Sroufe, L. A . (1997). A prospective, longitudinal studyof the correlates and consequences of early grade re-tention. Joumal of School Psychology, 35. 3-25.Jimerson. S. R., Pletcher, S. M., Graydon, K., Schnurr,

B. L., Nickerson. A. B., & Kundeii. D. K. (2(K)6).Beyond grade retention and social promotion: Promot-ing the social and academic competence of students.Psychology in the Schooh, 43, 85-97.

Marston. D. (1989). A curriculum-based measurementapproach to assessing academic performance: What itis and why do it. In M. R. Shinn (Eid.), Curriculum-based measurement: Asse.\sing special children (pp,18-78). New York: Guilford Press.Martinez, B., & Vandergrift. J, A. (1991). Eailing students:Is it worth Ihe cost? (Issue Paper .1). Tempe: MorrisonInstitute for Puhlic Policy. Arizona Slate University.Shinn. M. R. (1989). Identifying and defining academicproblems: CBM screening and eligibility procedures.In M. R. Shinn (Ed.). Curriculum-based measurement:Assessing speciai children (pp. 90-129). New York;Guilford.

Date Received: July 7, 2005Date Accepted: December 13, 2005Actioti Editor: John Hintze

Benjamin Silberglitt received his PhD in Educational Psychology (School Psychology)from the University of MinnesotaTwin Cities in 2003. He currently serves as theOutcomes Manager for the St. Croix River Education District, managing the research,assessmeni, and evaluation efforts of its tnember districts.Shane Jimerson, PhD, is a faculty member at the University of California, Santa Barbara,in the Gevirtz Graduate School of Education with both the Counseling, Clinical, andSchool Psychology program and the Child and Adolescent Development program. Hisscholai^hip continues to examine the importance of early experiences on subsequentdevelopment and to emphasize the importance of research infonning professional practiceto promote the social and cognitive competence of children.Matthew K. Bums, PhD, is an Associate Professor of Educational Psychology at theUniversity of Minnesota. Current research interests include curriculum-based assessment,response to intervention, problem-solving teams, and consultative service delivery forspecial education.James Appleton is a school psychology doctoral student at the University of Minnesotaworking with the Center for Applied Research and Educational Improvement. He isinterested in student engagement with school, social development, and evidence-basedinterventions.


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does timing of retention make a difference

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