Examination of the Predictive Validity of Preschool Early Literacy … · 2020-06-19 · School Psychology Review, 2007, Volume 36, No. 3, pp. 433-452 Examination of the Predictive

School Psychology Review,2007, Volume 36, No. 3, pp. 433-452

Examination of the Predictive Validity of Preschool EarlyLiteracy Skills

Kristen MissallUniversity of Kentucky

Amy ReschlyUniversity of Georgia

Joseph BettsRenaissance Learning, Inc.

Scott McConnellCenter for Early Education and Development, University of Minnesota

David Heistad, Mary Pickart, Christina Sheran, and Doug MarstonMinneapolis Public Schools

Abstract. The predictive validity of early literacy skills of children amongpreschool is relatively unknown. The purpose of this longitudinal study was toprovide this examination. From a sample of preschoolers, longitudinal data wereavailable for 143 of the children in kindergarten and for 116 of them through theend of first grade. Preschool children were assessed in the fall, winter, and springwith Early Literacy Individual Growth and Development Indicators (EL-IGDIs).In the fall, winter, and spring of kindergarten, literacy skills were assessed andcurriculum-based measurement data in reading were collected in the spring ofkindergarten and first grade. Results showed significant increases in mean EL-IGDI scores. In most instances, preschool administrations of the EL-IGDIs weremoderately correlated with kindergarten measures of alphabetic principle andphonological awareness. Preschool EL-IGDIs were found to be significantlypredictive of later outcomes in oral reading fluency both at the end of kindergartenand at the end of first grade. The diagnostic utility of these measures was foundto be strong. Implications for practice are discussed.

This research was funded in part by the U.S. Department of Education, as part of the Minnesota EarlyLiteracy Project (Grant S349A010152). The first three authors contributed equally to this article. Thisproject was completed through a partnership between the Center for Early Education and Development atthe University of Minnesota and the Research, Evaluation and Assessment Department of the MinneapolisPublic Schools, Scott R. McConnell and David Heistad, Directors.

Correspondence regarding this article should be addressed to Kristen Missall, 235 Dickey Hall, Universityof Kentucky, Lexington, KY 40506-0017; e-mail: [email protected]

Copyright 2007 by the National Association of School Psychologists, ISSN 0279-6015433

School Psychology Review, 2007, Volume 36, No. 3

In the past 15 years, reading achieve-ment has been at the forefront of educationalinitiatives (e.g., Goals 2000: Educate AmericaAct, 1994), debate (e.g., whole language vs.phonics, reading readiness vs. emergent liter-acy), and more recently, sweeping educationalreform legislation (such as the No Child LeftBehind Act of 2001). Although working toincrease reading proficiency among our na-tion's school-age youth, it has become evidentthat the development of foundational literacyskills is critically important in the years beforeformal schooling. At the time of school entry,striking differences exist between young chil-dren in language and early literacy develop-ment, educational opportunities, and life expe-riences (National Assessment of EducationalProgress, 1999; Shonkoff & Phillips, 2000;Snow, Bums, & Griffin, 1998).

Children who enter school behind theirpeers in language and early literacy develop-ment are unlikely to catch up (Fletcher &Lyon, 1998; Juel, 1988; Scarborough, 2002;Torgeson, 2002) and are at high risk for read-ing failure (Fey, Catts, & Larrivee, 1995;Stanovich, 1986; Whitehurst & Lonigan,2002) as well as high school drop-out andbroader social failure (National Center for Ed-ucational Statistics, 1992; Snow et al., 1998).Particular groups of young children are espe-cially at risk for reading failure, includingchildren with disabilities (Aram, Ekelman, &Nation, 1984; Bashir & Scavuzzo, 1992), chil-dren who live in poverty (Walker, Greenwood,Hart, & Carta, 1994), and children who speaka primary language other than English (August& Hakuta, 1997; Gutierrez-Clellan, 1999).Nevertheless, current educational practices inearly elementary school generally allow chil-dren to proceed with reading-related tasks attheir own rate. It is not until students havefailed to acquire reading skills, and gaps be-tween poor and proficient readers are large andoften intractable, that formal intervention(e.g., Title 1 services, special education) isintroduced. Yet, prediction about reading suc-cess can be made with very young children(Snow et al., 1998). In this era of increasedaccountability and escalating stakes, schools

and districts cannot afford to "wait" for stu-dents to fail. As such, there is increasing rec-ognition that preschool education and earlyliteracy development are imperative for im-proving later reading proficiency.

Development of Early Literacy Skills

Reading and early literacy are distinct butrelated concepts. Early literacy skills developduring the first 5 years of life and long beforeformal schooling when reading becomes the pri-mary academic focus. Early skills, such as pho-nological awareness (e.g., rhyming, alliteration),vocabulary, letter naming, and word manipula-tion (e.g., word blending, word segmenting), arestrongly related to the ability to use phonics later,and are precursory skills for leaming to readsuccessfully (Adams, 1990; Hart & Risley,1995; Snow et al., 1998). In addition, early lit-eracy skills, such as expressive and receptivelanguage, understanding of concepts of print,linguistic awareness, letter-sound correspon-dence, emergent writing skills, and alphabeticprinciples, all contribute in varying degrees toreading development (Snow et al., 1998; for acomplete discussion, see Whitehurst & Lonigan,1998). Together, these skills build the founda-tion for reading. The earlier these foundationalskills are acquired, the more efficiently and ef-fectively additional skills can be learned.

Curriculum-Based MeasurementLiteracy Assessment

Based on almost 30 years' work, curric-ulum-based measurement (CBM) is an evi-dence-based approach to measuring studentprogress in core academic skill areas (Deno,1985, 1997; Fuchs & Deno, 1991; Shinn,1998). The years of research have culminatedin substantial evidence for the reliability andvalidity of this approach, mostly within thearea of reading (R-CBM; Ardoin et al., 2004;Baker & Good, 1995; Espin & Deno, 1995;Fuchs, Fuchs, & Maxwell, 1988; Hintze &Silberglitt, 2005; Hintze, Shapiro, Conte, &Basile, 1997; McGlinchey & Hixson, 2004;Shinn, Good, Knutson, Tilly, & Collins,1992). R-CBM has been used to create school

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Early Literacy Skills

and district norms (Deno, 1985; Shinn, 1988)and as a screening tool to identify lower per-forming at-risk students (Good, Gruba, & Ka-minski, 2002). However, there has been adearth of assessment tools of prereading, lit-eracy skills, and limited methods to monitorstudents' progress or evaluate the effective-ness of interventions in these skills. Of spe-cific need are measures that cross develop-mental periods related to early literacy skill,from birth, when language and communica-tion skills begin to develop, through early el-ementary school.

Efforts have been made to extend the"rationale, procedures, and criteria" (Kamin-ski & Good, 1996, p. 216) of CBM to earlyliteracy. The Dynamic Indicators of BasicEarly Literacy Skills (DIBELS), developed byKaminski and Good (1996), are widely used inkindergarten and first grade across the UnitedStates to screen and monitor students'progress in prereading (available at http://www.dibels.uoregon.edu). A similar extensionof the CBM rationale, procedures, and criteriaresulted in the development of measures, in-dividually and collectively referred to as Indi-vidual Growth and Development Indicators(IGDIs), to be used with preschool childrenaged 3-5 years (McConnell, McEvoy, &Priest, 2002; Priest et al., 2001; available athttp://www.ggg.umn.edu) and infants and tod-dlers (Greenwood, Luze, & Carta, 2002; Luze,Linebarger, Greenwood, Carta, & Walker,2001; available at http://www.igdi.ku.edu).

Like R-CBM, the preschool Early Liter-acy IGDIs (EL-IGDIs) were designed to beeasy to administer, inexpensive, reliable andvalid, and sensitive to age and interventioneffects (Priest et al., 2001). Preliminary re-search has focused primarily on the psycho-metric properties of the measures (McConnell,Priest, Davis, & McEvoy, 2002; Missall &McConnell, 2004; Missall, McConnell, & Ca-digan, 2006), although some intervention stud-ies have been completed (McConnell, Priest etal., 2002; Phaneuf & Silberglitt, 2003). Over35% of 2004 Early Reading First Granteesused EL-IGDIs to assess child language andliteracy outcomes (U.S. Department of Educa-

tion, 2004) and the Pre-Elementary EducationLongitudinal Study (2004; http://www.peels.org/Assessments.asp) adapted the measuresfor its national evaluation of young children.A literature review indicated that EL-IGDIsare the only currently available CBM-likemeasures of early literacy for ages 3-5.

Given the strong influence of earlychildhood and preschool experiences on earlyliteracy development and the critical differ-ences in literacy skill apparent among childrenat the start of school, it behooves educators toexamine and link preschool measures of liter-acy skills with those used in primary schools.Once these links are established, this informa-tion may be used for screening and monitoringstudents' core literacy skills before school en-try and for early identification of those at riskfor later reading failure. Although EL-IGDIshave strong theoretical connections and ade-quate psychometric properties with preschool-aged children, there are currently no studiesthat link these measures to other measures ofprereading administered in kindergarten andfirst grade or with reading proficiency overtime. Therefore, the broad purpose of thisstudy was to examine longitudinal growth onEL-IGDIs from preschool through the end ofkindergarten and the relation of that growth toliteracy and reading performance in kindergar-ten and first grade. More specifically, we ex-amined three research questions: (a) Are EL-IGDIs sensitive to early literacy skill growthfrom preschool through the end of kindergar-ten? (b) What are the associations betweenperformance on EL-IGDIs in preschool andperformance on measures of early literacyskills and passage reading in kindergarten?and (c) What are the associations betweenperformance on EL-IGDIs in preschool andreading at the end of first grade?

Method

Participants

Participants were children initially re-cruited for a university study conducted in pre-schools located within a 2-mile radius of low-performing, high-poverty elementary schools in

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a large, urban school district in the Midwest. Asample of 398 children was recruited at age 4 tothe university study. Of these children, 143 at-tended kindergarten in this school district andwere selected for this project as a conveniencesample. One-hundred sixteen students were stillenrolled in the district at the end of first grade.Of the 143 students for whom preschool andkindergarten assessment data were collected,about 40% were African American, 34% wereEuropean American, 10% were Asian Ameri-can, 10% were American Indian, and about6% were Hispanic American. There weremore females (54.5%) than males (45.5%) inthe sample. Fifteen of the students were eligi-ble for services because of limited Englishproficiency as English language learners, andout of those 15, 60% had a native language asHmong, 20% had Spanish, 13% had Somali,and the remaining 7% were classified asLatvian or unknown. Fifty-eight percent of thestudents were eligible for free or reduced-pricelunch. None of the students in the sample wereeligible or served under special educationalservices.

Measures and Procedures

Procedures for data collection are de-scribed concurrently with each set of measures.

EL-IGDIs. Preschool EL-IGDIs, in-cluding Picture Naming, Rhyming, and Allit-eration (Early Childhood Research Institute onMeasuring Growth and Development, 1998,2000), are typically administered at least threetimes per year, and often seasonally, in pre-school to generate slope estimates of growthover time (McConnell, Priest et al., 2002; Mis-sall et al., 2006). EL-IGDIs are described inthe following paragraphs; however, a techni-cal report that includes psychometric informa-tion and study descriptions for all EL-IGDIscan be found online at http://www.ggg.unm.edu/techreports/dissemination.html#TechRep.Graduate research assistants were trained on theadministration of the EL-IGDIs and adminis-tered the measures on three occasions. Each ad-ministration lasted approximately 10 min per

child. Fidelity was evaluated with administrationchecklists available at http://www.ggg.umn.edu/get/procedures and materials/index.html. Allresearch assistants met minimum reliabilitycriteria of 90% on each measure before datacollection.

Picture Naming. Picture Naming (PN) iscompleted by presenting children with pic-tures of objects found in natural environments,including the home (e.g., cake, sink), class-room (e.g., glue, book), and community (e.g.,rabbit, train). Children are asked to name pic-tures as quickly as possible. The number ofpictures named correctly in 1 min is the child'sscore.

Research on the psychometric propertiesof PN has suggested it is a valid indicator ofchildren's expressive language skills. Ade-quate criterion validity has been reported pre-viously (Priest, McConnell, McEvoy, & Shin,2000) with the Peabody Picture VocabularyTest (Dunn & Dunn, 1997; r = .56-.75) andthe Preschool Language Scale (Zimmerman,Steiner, & Pond, 2002; r = .63-.79). Evidenceof construct validity has also been reportedwith significant correlations found betweenPN and chronological age (r = .41-.60), in-cluding preschool children without identifiedrisks (r = .63), children enrolled in Head Start(r = .32), and preschool children with disabil-ities (r = .48; McConnell, Priest et al., 2002).One-month alternate-form reliability coeffi-cients have ranged from r = .44 to .78 (Mc-Connell, Priest et al., 2002). Test-retest reli-ability across three weeks was r = .67. Hier-archical linear modeling (HLM) resultscentered at 66 months of age showed an av-erage PN score (correct responses in 1 min)of 26.9 for children without identifiedrisks, 19.0 for children living in low-incomeenvironments, and 16.9 for children with iden-tified disabilities (Priest, McConnell et al.,2000). In a different longitudinal study, HLMresults centered at 59 months of age showedan average PN score of 22.2 for children with-out identified risks, 18.9 for children withspeech-language impairments, and 7.2 for

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Spanish-speaking children learning English(Missall et al., 2006).

Rhyming. In Rhyming (RH), the child ispresented with a card that has one stimuluspicture on the top of the card (e.g., bees) andthree pictures across the bottom of the cardrepresenting one correct and two incorrect re-sponses (e.g., house, pants, cheese). The ex-aminer points to and names each picture andinstructs the child, "Point to the picture thatsounds the same as the top picture." Eachadministration continues for 2 min and achild's score is the number of correctly iden-tified rhymes. A child can receive a score ofzero by failing the sample items at the begin-ning of the administration or by passing thoseitems and then answering every administrationitem incorrectly (although the latter is ararity).

Criterion validity of the RH IGDI wasexamined in previously reported research withmoderate to high correlations with the Pea-body Picture Vocabulary Test (r = .56-.62),Concepts About Print (Clay, 1985; r = .54-.64), and Test of Phonological Awareness(Torgeson & Bryant, 1994; r = .44-.62; Mc-Connell, Priest et al., 2002). Studies of con-current validity have found moderate to highcorrelations with PN (r = .46-.63) and Allit-eration (r = .43; Missall, 2002), as well aswith DIBELS (Kaminski & Good, 1996) mea-sures of Letter-Naming Fluency (r =.48-.59)and Onset Recognition Fluency or InitialSound Fluency (r = .44-.68; McConnell,Priest et al., 2002; Missall, 2002). Evidence ofconstruct validity has been reported betweenRH and age, including children with disabili-ties and those living in poverty (r = .46;Priest, Silberglitt, Hall, & Estrem, 2000).Test-retest reliability over three weeks wasr = .83-.89 (Missall & McConnell, 2004).HLM results centered at 53 months of ageshowed an average RH score (correct re-sponses in 2 min) of 7.6 for children withoutidentified risks, 6.5 for children living in low-income environments, and 5.1 for childrenwith identified disabilities (Priest, Silberglitt etal., 2000). Results also showed that RH was

sensitive to children's monthly rate of growth,with children without identified risks gain-ing 0.4 rhymes per month, children from low-income families gaining 1.0 rhyme per month,and children with identified disabilities gain-ing 0.4 rhymes per month. In a different lon-gitudinal study, HLM results centered at 59months of age showed an average RH scoreof 12.0 for children without identifiedrisks, 6.8 for children living in poverty, 5.8 forchildren with speech-language disabilities,and 0.3 for Spanish-speaking children learningEnglish (Missall et al., 2006).

Alliteration. Similar to RH, Alliteration(AL) IGDI cards depict four pictures: at thetop is a picture representing the stimulus word(e.g., cake) and under the stimulus picture is arow of three other pictures (e.g., cat, sink,bear) with one correct and two incorrect re-sponses. The child is instructed, "Point to thepicture that starts with the same sound as thetop picture." AL is administered for 2 min andthe score is the number of beginning soundsidentified correctly. As with RH, a score ofzero can be obtained by either failing all thesample items or by passing the sample itemsand then failing to answer any of the followingitems correctly.

Criterion validity of AL has been exam-ined with the Peabody Picture VocabularyTest (r = .40-.57), Test of PhonologicalAwareness (r = .75-.79), and Concepts AboutPrint (r = .34-.55; McConnell, Priest et al.,2002). Concurrent validity with DIBELS Let-ter-Naming Fluency has been reported asmoderate to high (r = .49-.71; McConnell,Priest et al., 2002; Missall, 2002). AL has beencorrelated with age (r = .61) and found to bestable over time with test-retest reliabilityover three weeks resulting in moderate to highcorrelations (r = .62-.88; Priest, Silberglitt etal., 2000). There is also evidence that ALscores in preschool children vary by risk, in-come, and disability status (e.g., higher forstudents without risk or identified disabilities).HLM results centered at 53 months of ageshowed an average AL score (correct re-sponses in 2 min) of 5.2 for children without

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identified risks, 4.3 for children in low-incomeenvironments, and 4.4 for children with iden-tified disabilities (Priest, Silberglitt et al.,2000). HLM results centered at 59 months ofage showed an average AL score of 9.0 forchildren without identified risks, 4.4 for chil-dren living in poverty, 4.6 for children withspeech-language impairments, and 3.8 forSpanish-speaking children learning English(Missall et al., 2006).

Kindergarten assessments. The Min-neapolis Public Schools Kindergarten Assess-ments were administered to all students in thedistrict in the fall and spring. In addition, abrief progress check was administered imme-diately following winter break. These assess-ments consisted of measures of early literacyand mathematical concepts; however, onlyfluency based measures of early literacy andreading are described here. Some research hasbeen conducted on the technical adequacy andvalidity of these kindergarten assessments(Betts, Pickart, Heistad, & Sheran, 2005; Mar-ston et al., 2007; Pickart, Sheran, Betts, Heis-tad, & Muyskens, 2006). In general, there isevidence of adequate test-retest and internalconsistency reliability when examined as in-dividual measures (Marston et al., 2007), do-mains (i.e., phonemic awareness, alphabeticprinciple), and as an overall early literacycomposite (Pickart, Sheran, Betts, Heistad, &Muyskens, 2006). Further, the kindergartenassessments are highly correlated with first-grade R-CBM (r = .80) and moderately tohighly correlated with spring of second-gradestandardized test scores in reading (r = .66)and mathematics (r = .60; Pickart et al.,2006).

Temporary staff were hired and trainedto administer and score the assessments. As-sessors were typically retired kindergartenteachers trained by a district specialist in re-search and assessment. Administration timefor the beginning- and end-of-kindergarten as-sessments was approximately 20 min on eachoccasion (all components); the winter progresscheck lasted approximately 10 min. Descrip-tions of each measure follow.

EL-IGDIs. PN, RH, and AL IGDIs wereincluded as part of the fall and spring district-wide kindergarten assessments.' (EL-IGDIswere collected a total of five times in thestudy: three during the preschool year and twoduring kindergarten). Administration andscoring followed the standardized proceduresdescribed previously as part of the preschoolEL-IGDI assessments.

Letter Naming. Research has consis-tently found that letter naming is predictive oflater reading (Bishop, 2003; Scanlon & Vel-lutino, 1996). The district probe was adminis-tered in the beginning- and end-of-kindergar-ten assessments. To administer Letter Naming,the examiner presented a card with 70 ran-domly ordered lowercase letters and askedstudents to name letters as quickly as possible.The total number of correct letters named in 1min was recorded.

Letter-Sound Correspondence. This mea-sure was developed by the district to assessstudents' knowledge of letter sounds. The Let-ter-Sound Correspondence probe card had 70randomly ordered lowercase letters. The as-sessor gave the following directions: "When Isay begin, I want you to say the sound for theletter you see." Correct responses includedcommon letter sounds. The total number ofcorrect responses in 1 min was recorded. Let-ter-Sound Correspondence was administeredto all students in the fall, winter, and spring ofkindergarten.

Onset Phoneme Identification. The dis-trict's Onset Phoneme Identification measurewas developed to assess phonemic awarenessand was administered in the winter. The probeconsisted of 18 words presented orally to thestudent. The examiner gave the following di-rections: "I will tell you a word and you willgive me the first sound that you hear. If I saycat, you will say /k/." Items for the purpose ofmodeling and practice were presented beforethe measure was administered. The number ofcorrect responses in 1 min was recorded.

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Phoneme Segmentation. The district mea-sure of Phonemic Segmentation was based onthe work of Yopp (1988) and similar to theDIBELS segmentation measure (Marston etal., 2007). The same procedures were fol-lowed for the phoneme segmentation probe asthe onset phoneme identification task. Wordswere presented aloud by the examiner to thestudent, but the students were instructed to sayall the phonemes in the presented word. Di-rections were: "I will tell you a word and youwill give me the sounds you hear in that word.If I say cat, you will say /k/ /a/ /t/." Sampleitems were administered for modeling andpractice before probe items. The probe con-sisted of two- and three-phoneme words, andwas scored by counting the correct number ofphonemes isolated by the student in 1 min.The total number of correct responses wasrecorded. Phoneme Segmentation was admin-istered in the spring of kindergarten.

Passage reading. In the end-of-kindergar-ten assessment, students were presented withone preprimer oral reading passage and askedif they could read any of the words on thepage. If yes, then the passage was adminis-tered according to standard R-CBM proce-dures. The total number of words read cor-rectly from the passage in 1 min was recorded.Some students were unable to read connectedtext at the end of kindergarten; however, thismeasure was included so that a full range ofstudent skill could be captured by the assess-ment.2 End-of-kindergarten passage readinghas been used in the district since the 2001-2002 school year and has been found to becorrelated with first-, second-, and third-gradereading (Pickart et al., 2006).

First-grade reading. R-CBM assess-ments were administered to all students in thespring of first grade as part of the district'sassessment program. Three first-grade readingpassages were administered according to stan-dard R-CBM procedures (e.g., standardizedinstructions and guidelines, time limits). Thenumber of words read correctly in 1 min foreach passage was recorded (total number of

words read minus incorrect words). Wordsread correctly was defined as words pro-nounced correctly within the context of thesentence. Mispronunciations, reversals, andomissions were marked as incorrect. The av-erage number of words read correctly for thethree passages was used for data analysis inthis study. The mean has typically been usedin the district because its research has foundhigher reliability and validity coefficients withthe mean R-CBM score, as opposed to themedian score, in the spring of first grade.

Data Analysis

To address the research questions, anumber of quantitative methods were used.Descriptive statistics provided an initial de-scription of the mean and variation in vari-ables, and correlations provided basic evi-dence for predictive validity. Distributions ofthe variables were investigated, which lead tothe use of zero-inflated Poisson models forparts of the analysis. Zero-inflated Poissonmodels are useful when handling count datawith positive skewing, overdispersion, and anexcessive number of zero scores (Hall, 2000;Lambert, 1992; McLachlan & Peel, 2000).Zero-inflated Poisson models allow for analy-sis of two processes: one with respect to thezero outcomes and one with respect to thenonzero outcomes (Lambert, 1992; Muthen &Muthen, 2005).

Analyses investigated trends over timeon each of the EL-IGDIs using a latent vari-able growth approach (Bollen, 1989; Duncan,Duncan, Strycker, Li, & Alpert, 1999). In ad-dition, a general latent variable model (Bollen,1989) was used to evaluate the relation be-tween preschool measures and kindergartenmeasures. EL-IGDIs were modeled as ob-served indicators of a general early literacylatent variable measured at three distinct timesduring the pre-kindergarten year. Early read-ing skills assessed during kindergarten weresimilarly modeled. This allowed for modelingthe direct and indirect effects of early literacyvariables measured in preschool on the skillsmeasured during kindergarten.

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Multiple regression models were used toanalyze the relation between preschool EL-IGDIs and the end-of-kindergarten and end-of-first-grade reading skills as measured byR-CBM. The relation of the preschool mea-sures to the end-of-first-grade reading was alsoanalyzed using a logistic regression model(Hosmer & Lemeshow, 2000) to investigatethe EL-IGDIs with respect to whether studentsreached the benchmark criteria of reading cor-rectly at least 60 words per minute on thefirst-grade R-CBM assessment. To facilitatethis analysis, scores on the first-grade R-CBMwere classified into two groups based onwhether they achieved at least 60 words readcorrectly within 1 min-henceforth referredto as "masters" or "nonmasters." As a by-product of the results of the logistic regres-sion, it was possible to compute classificationand diagnostic accuracy indices. We com-puted the following indices: total classificationaccuracy, sensitivity, specificity, positive pre-dictive power, negative predictive power, falsepositives, and false negatives. Sensitivity wascomputed with respect to the students who didnot meet the benchmark at the end of firstgrade.

Results

Descriptive Analyses

Descriptive data for all measures are inTable 1. Results indicated growth in meanscores from preschool to the end of kindergar-ten on PN, RH, and AL IGDIs. The scoreincrease was quite small during preschool andsubstantial during kindergarten, and scores onseveral of the measures indicated a floor ef-fect. These measures also tended to show largevariations, as demonstrated by comparingstandard deviation and mean values. An inves-tigation of the distributions showed severalmeasures had non-normal distributions as de-termined by skewness and kurtosis valuesgreater than two times the standard error of thestatistic, including: preschool fall, winter, andspring RH; preschool fall, winter, and springAL; kindergarten fall AL, Letter Naming, andLetter-Sound Correspondence; and kindergar-

ten spring R-CBM. All of the remaining mea-sures had higher order moments, indicatingnormal distributions, and were treated as such.

Along with the identification of the flooreffect and large skew in distribution, many zeroresponses were found in the preschool data. Forthe fall, winter, and spring preschool observa-tions of RH, 39%, 43%, and 37% of the distri-bution was found to be zeros, respectively, and47%, 60%, and 52% for AL, respectively. Forthe kindergarten fall AL and Letter-Sound Cor-respondence, the frequency of zeros was 14%and 37%, respectively. The last two non-normalvariables, kindergarten fall Letter Naming andkindergarten spring R-CBM, had 9% and 3.5%zeros, respectively. Letter Naming was trans-formed to normality by square root and thespring R-CBM variable transformed to normal-ity by natural logarithm of the number correctplus one. All references and results of the springR-CBM scores were computed on the trans-formed scores but reported as words read cor-rectly per minute by applying the inversetransformation.

Pearson product moment correlationsare reported in Table 2. It should be noted thatthese correlations were attenuated due to re-striction of range as indicated above. Each ofthe preschool administrations of the EL-IGDIswas moderately correlated with measures ofalphabetic principle (Letter Sounds and LetterNames) administered in the fall of kindergar-ten. Low to moderate correlations were foundwith measures of alphabetic principle and pho-nological awareness administered in the win-ter and spring of kindergarten. However, somecorrelations were not found to be significantlydifferent from zero in this small sample.

Growth Analysis of IGDIs FromPreschool Through Kindergarten

Missing data were found at some mea-surement occasions. All students were ex-pected to be measured at all times; however,some students were not in attendance or avail-able for follow-up and were not measured.Little's test (Little, 1988) was used to evaluatethe extent to which the data could be consid-

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Table 1Descriptive Data

Variable Mean SD Range

Preschool 1: Fall (N = 110)Picture NamingRhymingAlliteration

Preschool 2: Winter (N = 130)Picture NamingRhymingAlliteration

Preschool 3: Spring (N = 125)Picture NamingRhymingAlliteration

Beginning of kindergarten (N = 143)Picture NamingRhymingAlliterationLetter SoundsLetter Naming

Winter progress check (N = 132)Letter SoundsOnset Phonemes

End of kindergarten (N = 136)Picture NamingRhymingAlliterationLetter SoundsLetter NamingPhonemic SegmentationPassage Reading

First-grade oral reading (N = 116)Below 60 wpm benchmark (N = 58)Above 60 wpm benchmark (N = 58)

Note. wpm = Words per minute.

ered missing completely at random (Little &Rubin, 1987). Results indicated the hypothesisof missing completely at random could not berejected (X2 [92] = 97.84, p = .3 1). Therefore,students with complete data were treated as arandom subsample and estimates unbiasedwith respect to the original sample (Little &Rubin, 1987; Lohr, 1999).

For the latent growth analysis, each in-dividual EL-IGDI (PN, RH, and AL) was

evaluated longitudinally as a set of latent tra-jectory variables (Bollen & Curran, 2006;Duncan et al., 1999). Latent growth trajecto-ries were modeled with latent intercept, linear,and quadratic components. The quadraticcomponent was used to evaluate the apparentnonlinear mean growth (see Table 1). For thePN variable a normal model was used as PN atall times appeared to be normally distributedand the maximum likelihood estimator was

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18.03.92.2

20.55.42.5

21.76.53.0

28.510.26.25.5

17.3

21.619.5

31.913.611.934.334.231.725.666.629.3

104.0

7.455.343.32

7.466.314.12

7.446.794.52

7.046.715.937.34

13.87

15.559.89

6.707.146.50

19.4517.8018.9228.3846.2518.5633.63

4-390-200-15

3-420-210-18

0-400-230-21

3-480-270-390-340-62

0-710-43

11-460-280-260-870-910-810-125

0.67-200.33


Table 2Correlations Between Preschool Early Literacy Measures and Criterion

Measures

Criterion Measures

Fall ofKindergarten Winter of Kindergarten Spring of Kindergarten First-

GradePredictive Letter Letter Letter Onset Letter Letter Phonemic Passage OralMeasures Sounds Names Sounds Phonemes Sounds Names Segmentation Reading Reading

Preschool fallPicture Naming .54** .59** .34** .29** .32** .43** .31** .37** .42**Rhyming .47** .49** .31** .35** .26** .35** .33** .26** .37**Alliteration .47** .49** .08 .09 .17 .34** .15 .29** .26**

Preschool winterPicture Naming .51** .54** .28** .40** .30** .45** .32** .42** .48**Rhyming .53** .55** .19* .22* .16 .38** .33** .36** .41**Alliteration .55** .51"* .27** .18 .23** .33** .22* .48** .43**

Preschool springPicture Naming .49** .49** .28** .37** .27** .29** .36** .36** .37**Rhyming .50** .59** .28** .31** .30** .41** .41** .42** .51"*Alliteration .59** .61** .24** .23** .29** .43** .24* .58** .50**

p < .05.**p < .01.

used. However, RH and AL were modeled asa zero-inflated Poisson, using robust maxi-mum likelihood estimators; diagnostic indicesindicated the models converged to global op-tima as evaluated by the equality of likelihoodestimates from 10 different starting values.

Picture Naming. Results indicated thequadratic parameter was not significantly dif-ferent from zero. The resulting linear modelappeared to fit the data moderately well asmeasured by the standardized root meansquare residual (SRMR - .10), comparativefit index (CFI = .89), and Tucker-Lewis Index(TLI = .89). The linear model resulted inparameter estimates indicating that children onaverage started preschool naming about 18pictures. Children had an average slope pa-rameter of about three pictures per measure-ment period, indicating they on average in-creased their PN score by about 6 over the

course of the preschool year. An interestingresult was the significant negative correlation(r = -. 51) between the latent intercept factorand the latent slope parameter, indicating thatchildren who initially scored lower on PNtended to have more rapid rates of increase onPN over the 2 years of preschool and kinder-garten than children scoring higher.

Rhyming. As with the PN model, thequadratic parameter was not significantlydifferent from zero in the Poisson process ofthe model for students not in the zero groupclass. Therefore, the quadratic parameterwas dropped from the model. Results of thismodel indicated that the probability of beingin the zero class at the beginning of thepreschool year was about 49% and it de-creased at each measurement point to only a10% probability by the fall of kindergartenand less than a 0.1% probability by the end

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of kindergarten. This indicates that childrenentering preschool were just as likely to beable to answer at least one item correctly asnot answer any items correctly. However,the probability decreased over time and bythe beginning of kindergarten it was highlylikely that a student answered at least oneitem correctly and almost all students were ableto answer one item correctly by the end of kin-dergarten. Results for the students who were notin the zero class indicated that a linear growthmodel was the most appropriate. The modelindicated that these students, on average, in-creased about two items correct at each timepoint. By the end of the preschool year thechildren were expected to earn scores around 9,and by the end of kindergarten, students wereable to identify about 13 rhymes.

Alliteration. A similar model was usedfor the AL variables as with the RH model. Thistime all the latent trajectory variables for theintercept, linear slope, and quadratic term weresignificant. There was about a 59% chance that achild starting preschool would not be able toanswer at least one AL item correctly. This prob-ability decreased over preschool to about a 53%chance of scoring zero by the end of the schoolyear. Children in the sample had about a 20%chance of being in the zero class at the beginningof kindergarten, but by the end of kindergartenless than 0.1% of the students were expected tobe in the zero class. Students in the nonzero classshowed a significant positive increase from ascore of about 2 correct at the beginning ofpreschool to about 12 correct by the end ofkindergarten. The linear slope parameter wasabout -. 08 and the quadratic curvature param-eter was about .42, indicating a concave up-growth curve with constant acceleration. Therate of change was a positive function of the timeof measurement, suggesting the rate of changeearly in the preschool year was not as rapid asduring kindergarten.

Relation Between EL-IGDls andKindergarten Measures

Table 2 provides estimates of the valid-ity coefficients between each of the EL-IGDIs

and the kindergarten measures. Most correla-tions were significant. To analyze the effect ofthe preschool measures on the beginning-of-kindergarten performance, each preschoolmeasurement occasion was treated indepen-dently and the beginning-of-kindergarten as-sessment scores on RH, AL, Letter Sounds,and Letter Names were used as observed in-dicators of a general early literacy factor (seeFigure 1). Because of the non-normality andexcess kurtosis in the preschool variables, RH,and AL, the weighted least squares estimatorwas used to handle the potential bias in esti-mation of standard errors (Bollen, 1989). Re-sults of the three latent variable models are inTable 3. The table shows results of each of thepreschool early literacy variables in relation tothe underlying latent factor (LI-L3), the earlyreading skills observed variables to the under-lying latent early reading skills variable (L4-L7), and the direct effect of the preschoollatent early literacy variable on the kindergar-ten latent early reading skills variable (GI).

Examination of the fit statistics deter-mined a moderate fit of all the models to thedata. Because of the exploratory nature of thisstudy and the small sample size, no adjust-ments to the models were undertaken to helpimprove fit. One option would have been toindicate correlated residuals at, or between,each measurement occasion or to model latentgrowth factors of EL-IGDIs across time. Thepercentage of variance accounted for in eachof the kindergarten latent variables reflectingearly reading skills attributable to the earlyliteracy measures increased over time and wasquite substantial. Large direct effects also in-dicated a standard deviation change in theearly literacy latent variable results with al-most a complete standard deviation change inthe early reading latent variable.

Direct effect of the early literacy latentvariable, as measured by the preschool EL-IGDIs, on the beginning-of-kindergarten read-ing skills was represented by the GI parameterestimate. All indirect effects of the early liter-acy latent variable on observed variables atkindergarten are the product of the GI variableand the specific coefficient estimate (Lx). For

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instance, the indirect effect of changes in thefall early literacy latent variable on the LNvariable at the beginning of kindergarten isabout 0.76 (G1 X L6 = 0.91 X 0.84 = 0.76).This indicates that a standard deviation unitchange in early literacy skills at the fall ofpreschool was expected to result in about athree-quarters standard deviation shift in theLN variable at the beginning of kindergarten.The results indicated large and substantial di-rect and indirect effects.

To evaluate the effects of preschool fallEL-IGDIs on end-of-kindergarten R-CBM,the EL-IGDIs measured at each time pointduring the preschool year were summed to atotal score. Summing the measures at eachtime point resulted in distributions that werenormally distributed. Results indicated the fallpreschool measure (n = 104) was correlated.38 (p < .01) with the end-of-kindergartenmeasure of R-CBM; the winter preschoolmeasure (n = 124) was correlated .50 (p <.01), and the spring measurement (n = 118)was correlated .51 (p < .01). All measureswere found to be significantly linearly relatedto end-of-kindergarten R-CBM.

dl - PN

-•tL L2

d2 RH -E

o >12( W

Two follow-up analyses were com-pleted with respect to the AL and RH IGDIsindependently. Because a large number ofchildren scored zero on these measures dur-ing preschool, it was important to evaluatehow the zero class (children with a score ofzero at each time) performed in comparisonto the nonzero class (children with at leastone score above zero) on the end-of-kindergar-ten R-CBM. To evaluate differences in oralreading fluency rates, a regression analysis wasrun using R-CBM as the outcome variable andgroup membership as the predictor. However,just the RH measure was investigated becauseonly 2 students had complete data on AL duringpreschool as well as the end-of-kindergartenR-CBM.

Fifty-three students had completed pre-school RH and end-of-kindergarten measures;30 students were in the zero class and 23 werein the nonzero class. The regression modelwas significant (F[1,51] = 11.45, p < .001, R2

= .18). Parameter estimates indicated that thenonzero class averaged about 41 words readcorrectly per minute at the end of kindergartenwhereas the zero class only averaged about 14.

el

Figure 1. Latent variable measurement and structural equation model forEarly Literacy Individual Growth and Development Indicators' effects onkindergarten reading skills

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Table 3Latent Variable Model Standardized Estimates at Each Preschool

Measurement Time with Beginning of Kindergarten Reading Skills

Parameter Fall Preschool Winter Preschool Spring Preschool

Li 0.71 0.66 0.68L2 0.73 0.70 0.79L3 0.64 0.68 0.74L4 0.74 0.73 0.82L5 0.83 0.86 0.86L6 0.84 0.83 0.78L7 0.84 0.81 0.81GI 0.91 1.00 0.98R2 .83 .88 .97

×2 39.93 54.95 70.62df 13 13 13

p Value <.001 <.001 <.001CFl .94 .92 .90TLI .90 .87 .84

RMSEA .14 .16 .19SRMR .05 .05 .06

Note. [Li preschool PN; L2 = preschool RH; L3 - preschool AL; L4 = kindergarten RH; L5 - kindergarten AL;L6 = kindergarten LN; L7 = kindergarten LS; G1 = preschool early literacy with beginning of kindergarten reading].R2 indicates the percent of variance of the beginning of kindergarten latent variable explained by the early literacy latentvariable; CFI = comparative fit index; TLI = Tucker-Lewis index; RMSEA = root mean square error of approxima-tion; SRMR = standardized root mean square residual.

The zero class was found to be significantlybehind the nonzero class of students.

Relation Between EL-IGDIs and First-Grade Oral Reading

Table 2 provides validity coefficients ofeach EL-IGDI with the end-of-first-grade R-CBM. For further analysis of the relation be-tween the preschool measures and the end-of-first-grade R-CBM, we used the total score ateach time (as done in the previous analysiswith respect to end-of-kindergarten R-CBMscores). Results indicated the fall (n = 88,r =.46, p < .01), winter (n = 106, r =.54,p < .01), and spring (n = 101, r =.54, p <.01) measures were significantly correlatedwith the end-of-first-grade R-CBM.

Differences in the end-of-first-grade R-CBM between the zero class (n = 25) and thenonzero class (n = 20) with respect to RH

were evaluated. The regression analysis wassignificant (F[1, 43] = 22.66, p < .001, R2

=

.35). Parameter estimates for the model indi-cated that the nonzero class averaged about 95words read correctly per minute as opposed tothe 36 words averaged by the zero class at theend of first grade. It was also possible toclassify the students with respect to their zero-class status and to their status on the end-of-first-grade R-CBM benchmark (whether theyachieved 60 words read correctly per minute).This classification allowed for the computa-tion of the odds ratio, which indicated thatstudents in the nonzero class during preschoolwere almost 12.7 times more likely to meet thebenchmark than were students in the zero class.

A final logistic regression was used todetermine how well the EL-IGDIs, adminis-tered in the fall of preschool, correctly classi-fied those who reached an end-of-first-grade

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R-CBM benchmark of 60 words per minute,indicating a grade-appropriate reading level(Fuchs, Fuchs, & Deno, 1982; MinneapolisPublic Schools Content Standards, n.d.). Ofthe 88 students who had R-CBM data andcomplete fall of preschool data, 53% of thesample (n = 47) achieved this benchmark.The results of the logistic regression weresignificant (X2 [3] = 20.97, p < .001,Nagelkerke R2

= .28). Parameter estimatesindicated the RH and AL variables did notsignificantly increase prediction. However, us-ing only the PN variable in the model, thecorrect classification increased from about53% to about 73%, which is almost a 38%increase in correct classification. Diagnosticaccuracy indices indicated sensitivity to beabout 64% and specificity to be about 81%.Results further indicated that the percentage offalse negatives was about 36% and false pos-itives about 19%. The positive predictivepower was found to be about 74% and thenegative predictive power was about 72%.

Discussion

Learning to read is one of the most im-portant milestones of childhood. Indeed, read-ing is critical for success throughout schooland in life. As such, it is not surprising thatreading, or more accurately improving thereading proficiency of students across theUnited States, is the subject of considerabledebate and concern. It is increasingly recog-nized that preschool and kindergarten are op-portune times to promote literacy developmentand to screen and intervene at the first signs ofreading difficulties. Therefore, the purpose ofthis study was to examine measures of earlyliteracy from preschool through the end ofkindergarten and the link between preschoolmeasures and later reading.

In general, results indicated the EL-IG-DIs were sensitive to growth in preschool, asdemonstrated in previous studies (Priest, Mc-Connell et al., 2000), and the measures con-tinued to be sensitive to growth across kinder-garten. This was true in terms of scores ofindividual measures and the total score of all

measures summed together. In terms of valid-ity, previous research examined the concurrentvalidity of the EL-IGDIs with other early lit-eracy measures, namely the DIBELS (Kamin-ski & Good, 1996), revealing low to moderatecorrelations (McConnell, Priest et al., 2002;Missall, 2002). However, this study wasamong the first to examine the longitudinalassociations between preschool administra-tions of the EL-IGDIs and kindergarten mea-sures of early literacy skills and reading flu-ency at the end of kindergarten and first grade.Although the size of the correlations varied,most were significant and in the low to mod-erate range.

An interesting finding arose out of thelarge, negative correlation of initial status andgrowth over time on the PN task, whereby stu-dents with higher scores tended to grow moreslowly than students with lower initial scores.When examining the effects of the EL-IGDIs asa single factor on later reading skills, changesin the EL-IGDIs predicted large changes inlater early reading skills. This suggests thatany attempt to increase a student's early liter-acy skills with respect to language, rhyming,and alliteration should result in positive shiftsin that student's later reading skills. This typeof finding helps to bolster support for inter-vention research and the potential long-termeffects on later reading ability of students.

Also of interest is the diagnostic utilityof the PN IGDI in identifying later outcomes.Measures of sensitivity and specificity werefair, but of more importance were the higherlevels of positive predictive power and nega-tive predictive power. The positive predictivepower and negative predictive power are morelikely to reflect intended use of the measure aseducators will want to use the measure topredict later status. Arguably, one of the morecompelling findings of this study was the levelwith which the PN IGDI at the fall of pre-school correctly classified first-grade readers(72.7%). These results should be interpretedwithin the context of the exploratory nature ofthis study and small sample sizes. However,they provide a strong basis for follow-uplarge-scale studies.

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Results of RH IGDI provided some in-sight into students' early literacy skill devel-opment by indicating that preschoolers unableto answer a single item correctly had a muchlower reading outcome both at the end ofkindergarten and the end of first grade whencompared to preschoolers able to answer atleast one item correctly on at least one occa-sion in preschool. Because of the small sam-ples sizes, it was impossible to complete asimilar analysis with the AL IGDI. However,given these results, it appears to be a provoc-ative follow-up analysis.

Several implications and caveats may bedrawn from this study and more broadly fromwork in early literacy assessment and earlyintervention. First, our results indicate that it ispossible to assess children's literacy skills andgrowth in these skills before the start of formalschooling. Furthermore, this information canbe collected and maintained across a contin-uum from preschool through kindergarten.Given what is known about the developmentof foundational literacy skills (e.g., language,phonological awareness, concepts of print)from birth to age 5, the striking differencesthat exist among students at the commence-ment of formal schooling, and the long-termnature of reading difficulties not effectivelyremediated by Grades 2 or 3 (Juel, 1988;Stanovich, 1986), there is a clear rationale forliteracy assessment before school entry and inthe first year of formal schooling. Moreover, theassessment tools are available. The issue, then,becomes one of purpose and utility.

Any number of assessment tools or vari-ables might be used to predict which studentswill fail in school or which students may havedifficulty learning to read (e.g., students withdisabilities, living in poverty, those who speakEnglish as a second language). However, mea-sures such as those described in this study maybe used for the early identification of studentswho are at risk for later reading problemsbefore problems are severe and gaps betweengood readers and poor readers are large. Fur-thermore, measures like these also support thecritical link between assessment and interven-tion practices (Reschly, 1988). There is prom-

ise that these measures, developed in the moldof CBM, may be used in a CBM-like mannerwithin a problem-solving model (Deno, 1989)to monitor effects of interventions and toguide changes based on students' own data toaffect the greatest rate of skill growth.

An example of the utility of early literacyassessment may be found in the work conductedby the Minneapolis Public Schools. Benchmarksfor student performance have been set using thekindergarten assessments (Pickart et al., 2006).Kindergarten benchmarks have been linked tofirst-grade oral reading and passing scores on thestate-mandated high-stakes reading assessmentadministered in the third grade. These bench-marks have allowed the district to identify stu-dents "not on track" for reaching desired levelsof proficiency on state-mandated assessmentsyears before the administration of such assess-ments, providing valuable opportunities for earlyintervention. This information has also beenused for program evaluation and to identify out-standing teachers and/or instructional methods.In addition, Minneapolis Public Schools cur-rently uses a problem-solving model forscreening, early intervention, and if necessary,special education eligibility determination, toaddress both academic and behavioral con-cerns (Marston, Muyskens, Lau, & Canter,2002; Muyskens, Marston, & Reschly, 2005).The Kindergarten Assessments are an impor-tant part of this problem-solving model, link-ing kindergarten to the process and measuresalready in place for other elementary grades.

Although there is great promise in thistype of work for screening and early interven-tion with reading difficulties, it is a compli-cated science. Research is clear that multipleearly literacy skills contribute to reading ac-quisition (see Snow et al., 1998; Whitehurst &Lonigan, 1998). The predictive validity of thevarious skills, however, can make data inter-pretation and instructional and interventionplanning somewhat difficult. In the words ofKaminski and Good (1998), "Early literacyskills such as phonological awareness, printawareness, and letter naming generally are notimportant tool skills in their own right. In-stead, they are transitory, [or] enabling, skills

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that facilitate the acquisition of reading,[which is] an important tool skill" (p. 123).

Limitations and Future Research

In any longitudinal study, the attrition ofsubjects is a limitation, possibly confoundingresults--certainly this study is no exception.Results in this analysis were based upon theassumption that data were missing completelyat random, which was inferred from the resultsof a single statistical estimator and the re-search design, which attempted to include allstudents at each measurement; therefore, esti-mates should not be biased. Researchersshould be aware of this problem and designfuture studies to ameliorate, to the extent pos-sible, the effects. Along with good follow-upprocedures for assessing students who may havebeen absent on a testing occasion, a viable optionwould be to gather salient demographic vari-ables. With the collection of important back-ground variables, researchers may be able meetthe less restrictive case of missing at random.

Another important issue that arises is thegeneralizability of the estimates and predictiverelationships to a larger population of stu-dents. The sample in this study was small andhighly selective. The students represented aselect group of children from families living inpoverty in a particular geographical region.There is compelling evidence that childrenwho live in poverty are disproportionately rep-resented in the number of children who expe-rience school difficulty, special educationplacement, and school dropout (Puma et al.,1997; Snow et al., 1998). Although these sta-tistics make it all the more important to inter-vene with this population, it must be consideredwhen interpreting findings from this study.

This study is at the beginning of a line ofnecessary research on preschool literacy as-sessment and intervention. One important av-enue of future work is to create benchmarkscores for EL-IGDIs to apply meaning. Cur-rently, when a 4-year-old child completes PN,we are uncertain which score, or range of scores,reflects "on-track" or "at-risk" performance.

Determining these benchmarks is a criticalstep in influencing the utility of the measures.

Results from this study provide prelim-inary evidence of predictive validity with re-spect to reading, but the exploratory natureand limited sample does not warrant identifi-cation of benchmark scores from these data.Once these scores are set, however, a secondnecessary step involves following up with stu-dents who are at risk and in need of morefrequent monitoring than a standard seasonalschedule. At this time, each of the EL-IGDIs issensitive to a monthly rate of growth (cf. Mc-Connell, Priest et al., 2002; Missall & Mc-Connell, 2004; Priest, McConnell et al., 2000),although rates vary per measure and per sam-ple and tend to be too small for effectivelydetermining response to intervention. Further,although EL-IGDIs were designed for usewith preschool children from 3 to 5 years ofage, there is speculation about whether allthree measures are appropriate for the full agerange for all children. For example, this andother research has shown floor effects on themeasures, particularly RH and AL, which mayindicate that tasks are quite difficult for a gooddeal of preschoolers, and ceiling effects forPN for children without risk factors (Estrem,McConnell, & Mein, 2006; Missall, 2002;Missall et al., 2006). However, this is the firststudy to discern, at least on the RH IGDI, howthe floor effect may actually provideinformation.

The specific age range for sensitivity ofeach of the EL-IGDIs needs to be determined.Similarly, it is currently unknown how cutscores may link the EL-IGDIs together. If, forexample, PN measures skills that emerge beforeRH and AL, it would be helpful to know whatPN scores indicated and whether that child wasdevelopmentally ready for assessment with RHand AL. As results of this research indicated, theprobability of being able to respond correctly toRH and AL items increased remarkably acrosspreschool and kindergarten. Further explorationof the zero-class classification approach may behelpful in such an endeavor as it may provide amethod to evaluate the probability of leaving thezero class based on PN score.

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Interestingly, the developmental periodbefore formal schooling and the initiation offormal schooling in kindergarten are generallyviewed as separate and distinct entities. Yet, itis clear that children do not enter kindergartenas blank slates; there are large differences inacquired educational skills, opportunities, andexperiences before children ever cross thedoors of our nation's schools. The preschoolyears are a time of tremendous growth andprovide an incredible opportunity for educa-tion, assessment, and early intervention. How-ever, amending the typical K-12 educationperspective to include preschool requires asignificant paradigm shift, one in which schoolpsychologists, with their backgrounds in childdevelopment, assessment, and consultation,are in a unique position to lead.

Footnotes

1Given the time and financial commitmentsof administering a comprehensive assessment to allkindergarten students in the district, full Minneap-olis Kindergarten Assessments are administered inthe fall and spring. This administration scheduleallows for the identification of students belowbenchmark levels of performance for the purposesof early intervention, the calculation of growthacross the school year, and evaluation and compar-

ison of students' performance from year to year.2 No floor effects have been found for this mea-

sure; 4% of students in this study earned 0 on this task.

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Date Received: May 11, 2006Date Accepted: March 16, 2007

Action Editor: John Hintze 0

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Kristen N. Missall, PhD, is Assistant Professor at the University of Kentucky. Shegraduated from the University of Minnesota and completed a two-year postdoctoralexperience at the Center for Early Education and Development at the University ofMinnesota. She conducts research in the areas of early literacy, social skill development,school adjustment, and general outcome measurement, and has particular interest in theskills and experiences of children transitioning from preschool to kindergarten.

Amy L. Reschly, PhD, is Assistant Professor in the Department of Educational Psychol-ogy & Instructional Technology at the University of Georgia. She is a graduate of theUniversity of Minnesota. Her primary research interests are in the areas of studentengagement at school and with learning, drop-out prevention, and curriculum-basedmeasurement, particularly in the areas of reading and early literacy.

Joseph Betts, MMIS, PhD, is School Psychologist and Measurement Statistician workingwith the Center for Cultural Diversity and Minority Education. He specializes in the useof latent trait theory and modem item response models to assess student academic achieve-ment and development. In addition, his research focuses on issues related to measurement withdiverse student groups, such as predictive bias and measurement invariance.

David Heistad, PhD, is Executive Director of Research, Evaluation and Assessment forthe Minneapolis Pubic Schools and is a member of the Institute for Education SciencesUrban Education Research Taskforce.

Scott R. McConnell, PhD, is Professor in the Department of Educational Psychology andDirector of Community Engagement for the Center for Early Education and Developmentat the University of Minnesota. He has published articles on the assessment and treatmentof social behavior deficits, social competence, school adjustment, and academic perfor-mance, including development of early literacy skills.

Mary Pickart is Teacher on Special Assignment in the Research, Evaluation and AssessmentDepartment for the Minneapolis Public Schools. She coordinates the district's kindergartenand first-grade assessments. Her research interests include early literacy and intervention.

Christina P. Sheran earned her PhD in Educational Psychology with a dual major in EarlyEducation Special Education and School Psychology from the University of Minnesota.Currently she works in Research and Evaluation in the Minneapolis Public Schoolsdeveloping early measures for children age 3 to Grade 3 and training and coaching pre-kteachers in the area of early literacy.

Doug Marston, PhD, NCSP, is the Administrator for Research and Evaluation in SpecialEducation, Minneapolis Public Schools. His research interests include curriculum-basedmeasurement, problem-solving models, and using technology for making data-basededucation decisions.

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TITLE: Examination of the Predictive Validity of Preschool EarlyLiteracy Skills

SOURCE: Sch Psychol Rev 36 no3 S 2007

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