USING EARLY LITERACY ASSESSMENTS TO PREDICT READING ACHIEVEMENT Anna Michelle Gillard, PhD, NCSP...

Post on 27-Mar-2015

219 views 0 download

Tags:

Transcript of USING EARLY LITERACY ASSESSMENTS TO PREDICT READING ACHIEVEMENT Anna Michelle Gillard, PhD, NCSP...

USING EARLY LITERACY ASSESSMENTS TO PREDICT READING ACHIEVEMENT

Anna Michelle Gillard, PhD, NCSPNASP Annual Conference March 5, 2010

Early Literacy Assessment

Essential to reading acquisition Early literacy skills include

Phonological awareness Vocabulary skills Letter knowledge

Purposes of assessment include: Progress monitoring Identification of struggling students

Why is this important?

Monitor progress Identify struggling students Develop appropriate interventions

Individual Growth & Development Indicators Early literacy measures created through collaboration

between the Universities of Minnesota, Kansas, and Oregon Created to measure early childhood development, one area

of which is early literacy Include three subtests

Picture Naming Rhyming Alliteration

Reliability and validity

(McConnell, Priest, Davis, & McEvoy, 2000; Missal & McConnell, 2004)

Picture Naming

1 minute, timed fluency measure of expressive language

Child is required to name pictures

Rhyming

• 2 minute fluency measure of phonological awareness

• Child is required to identify the picture in a set of 3 that sounds like the target picture

Alliteration

• 2 minute fluency measure of phonological awareness

• Child is required to identify the picture in a set of 3 that starts with the same sound as the target picture

DIBELS

Measures of early literacy skills Phonological awareness Letter knowledge

Timed, fluency measures Formerly mandated through the Reading First

grant Research shows that DIBELS are predictive of

reading achievement

(Gillard, 2008; Good, Simmons, & Kame’enui, 2001; Kaminski & Good, 1996)

Florida Assessments In Reading (FAIR)

New statewide reading assessment (K-12) Three levels of assessment:

Broad Screening Targeted Diagnostics Progress Monitoring

Primary measure for K-2: Probability of Reading Success (PRS)

Participants: Cohort 1 (2007-2008)

95 students in five VPK classes Demographic make-up 82 remaining in Kindergarten (08-09) 75 remaining in First grade (09-10)

However, FAIR data not available for all students

Participants: Cohort 2 (2008-2009)

180 students in 11 VPK classes Demographic make-up 165 included in this sample

FAIR data not available for all students

Measures

• IGDIs– Administered Fall, Winter, & Spring– All measures attempted

• DIBELS– Only Cohort 1– ISF and LNF administered within first 30 days of school– Reading First schools given DIBELS three times

• FAIR– AP 1: Administered between 6th and 40th day of school– AP 2: Administered between 66th and 100th day of

school– All students: Broad Screening, Broad Diagnostics– Some students: Targeted Diagnostics

Cohort 1 Results: FAIR

ANOVA for PRS-AP1 ANOVA for PRS-AP2

•Picture Naming, Rhyming, Alliteration included at each measurement period

Measurement Time

df F Sig.

Fall 3 .960 .417

Winter 3 4.208 .009

Spring 3 3.290 .026

Measurement Time

df F Sig.

Fall 3 1.541 .212

Winter 3 1.584 .201

Spring 3 2.665 .055

Cohort 2 Results: FAIR

ANOVA for PRS-AP1 ANOVA for PRS-AP2

•Picture Naming, Rhyming, Alliteration included at each measurement period

Measurement Time

df F Sig.

Fall3 7.540 .000

Winter3 12.138 .000

Spring3 17.620 .000

Measurement Time

df F Sig.

Fall3 9.741 .000

Winter3 5.337 .002

Spring3 13.874 .000

Cohort 1 Results: FAIR

Coefficients for PRS-AP1

Model t Sig.

PN1 1.040 .302

RHY1 -.261 .795

ALL1 .963 .339

PN2 1.367 .176

RHY2 -.718 .475

ALL2 2.610 .011*

PN3 .494 .623

RHY3 .359 .721

ALL3 2.204 .031*

Cohort 2 Results: FAIR

Coefficients for PRS-AP1

Model t Sig.

PN1 2.424 .017*

RHY1 1.233 .220

ALL1 1.878 .063

PN2 3.476 .001*

RHY2 .805 .422

ALL2 2.311 .022*

PN3 4.172 .000*

RHY3 -.075 .940ALL3 3.503 .001*

Coefficients for PRS-AP2

Model t Sig.

PN1 2.393 .018*

RHY1 .747 .457

ALL1 1.419 .158

PN2 3.473 .001*

RHY2 1.112 .268

ALL2 1.130 .260

PN3 4.174 .000*

RHY3 .459 .647

ALL3 1.893 .060*

Results: FAIR

•Picture Naming, Rhyming, Alliteration included at all measurement times

Model Summary Cohort 1

Measurement Time R2 Adj. R2

Fall AP1 .041 -.002Winter AP1 .157 .119Spring AP1 .130 .091Fall AP2 .065 .023Winter AP2 .066 .024Spring AP2 .108 .067

Results: FAIR

Picture Naming, Rhyming, Alliteration included at all measurement times

Model Summary Cohort 2

Measurement Time

R2 Adj. R2

Fall AP1 .140 .121

Winter AP1 .197 .181

Spring AP1 .269 .253

Fall AP2 .102 .083

Winter AP2 .163 .146

Spring AP2 .227 .210

Results: DIBELS

Measurement Time df F Sig.

Fall 3 3.003 .036

Winter 3 8.428 .000

Spring 3 4.603 .005

ANOVA for DIBELS ISF ANOVA for DIBELS LNF

Measurement Time df F Sig.

Fall 3 4.953 .003

Winter 3 9.116 .000

Spring 3 7.064 .000

Results: DIBELS

Coefficients for DIBELS LNF

Model t Sig.PN1 2.893 .005*RHY1 .235 .815ALL1 .827 .411PN2 3.346 .001*RHY2 -.870 .387

ALL2 2.581 .012*

PN3 .726 .470

RHY3 1.128 .263

ALL3 2.771 .007*

Coefficients for DIBELS LNF

Model t Sig.PN1 2.707 .008*RHY1 -.063 .950ALL1 -.090 .929PN2 2.608 .011*RHY2 -1.452 .151

ALL2 3.404 .001*

PN3 .593 .555

RHY3 -.026 .979

ALL3 2.918 .005*

Results: DIBELS

Model Summary ISF

Measurement time

R2 Adj. R2

Fall .110 .073

Winter .257 .227

Spring .163 .127

Model Summary LNF

Measurement time

R2 Adj. R2

Fall .169 .135

Winter .273 .243

Spring .230 .197

Implications

Results suggest preschool measures can be used to predict kindergarten and some first grade reading measures

If the PRS score can be used to predict reading success as measured by the SAT-10, and the IGDIs can be used to predict PRS scores, then we may be able to predict, in preschool, which students are most likely to struggle on the SAT-10

References

DIBELS- http://dibels.uoregon.edu/index.php Gillard, A.M. (2008). The Predictive Validity of Kindergarten

Assessment Good, Simmons, & Kame’enui (2001). Kaminski, R.A. & Good, R.H. (1996). Toward a technology for

assessing basic early literacy skills. School Psychology Review, 25, 215-227.

McConnell, S. R., Priest, J. S., Davis, S. D., & McEvoy, M. A. (2002). Best practices in measuring growth and development for preschool children. In A. Thomas & J. Grimes (Eds.), Best Practices in School Psychology IV (pp. 1231– 1246). Bethesda, MD: National Association of School Psychologists.

Missall, K. & McConnell, S.R. (2004). Psychometric characteristics of Individual Growth and Development Indicators: Picture Naming, Rhyming, and Alliteration

Questions?

Contact Information

Anna Michelle Gillard, PhD, NCSP gillardm@stlucie.k12.fl.us