Using Nonsense Word Fluency to Predict Reading Proficiency in Kindergarten Through Second Grade for English Learners and Native English Speakers

By Fien, Hank Baker, Scott K; Smolkowski, Keith; Smith, Jean L Mercier; Kame’enui, Edward J; Beck, Carrie Thomas

Abstract. This study examined the validity of Nonsense Word Fluency as an index of beginning reading proficiency for students in kindergarten through second grade. Validity evidence for Nonsense Word Fluency is addressed in the context of research-based instructional practices implemented on a large scale. Technical adequacy data are presented for all students in participating schools, and separately for English learners and native English speakers. Five cohorts of students participated, with each cohort representing approximately 2,400 students. Results support the use of Nonsense Word Fluency in the early grades to screen students for reading problems and predict early reading proficiency. The use of this measure in reading reform is discussed as well as implications for school psychologists.

Reading First is a federal program with the goal of all children reaching grade-level reading proficiency by the end of third grade, which requires an integrated system of reading instruction and assessments designed to prevent reading problems (Reading First, P.L. 107-110, 2002). This system begins in earnest in kindergarten. In addition, the response to intervention (RTI) initiative attempts to reduce the number of students who are misidentified as having a learning disability by intervening strategically and intensely in the early grades (Reading First, P.L. 108-446, 2002). The basis of the prevention framework of these reforms is substantial evidence demonstrating the importance of early academic achievement on a range of long-term outcomes (Finn, Gerber, & Boyd-Zaharias, 2005). The level of school-wide assessment data needed for prevention- oriented reform is unprecedented in public education. These assessments must be able to provide a direct measure of an important skill and approximate performance on a comprehensive measure of learning. In the early grades, a foundational skill of later reading proficiency is the alphabetic principle, which is the ability to link the internal structure of words (letters and letter strings) to their sounds (phonemes). The alphabetic principle is comprised of two fundamental skills: (a) alphabetic understanding (knowledge of letter-sound correspondences) and (b) phonological receding (the ability to blend sounds to read words; National Research Council, 1998). Thus, a critical component of an assessment system should include a direct measure of students’ alphabetic understanding and phonological recoding skill.

Assessing the Alphabetic Principle Using Pseudoword Reading

There is strong empirical support for the use of measures of pseudoword reading to assess the alphabetic principle. In the National Reading Panel report, of the 38 studies included in the meta-analysis on phonics interventions, 18 included a measure of pseudoword reading to determine intervention effectiveness (National Reading Panel, 2002). Moreover, numerous studies have reported substantial correlations between the ability to read pseudowords and the ability to read real words (Beech & Awaida, 1992; Felton & Wood, 1992; Manis, Szeszulski, Holt, & Graves, 1990). In fact, Curtis (1980) concluded that the ability to read pseudowords was the single best predictor of reading ability. Through hierarchical regression procedures, word reading ability was found to be the key predictor of reading comprehension, and pseudoword reading regularly accounted for the greatest portion of variance in word reading performance (Curtis, 1980).

Nonsense Word Fluency (NWF) is a direct measure of pseudoword reading. It is designed to measure alphabetic understanding and phonological recoding ability (Good, Baker, & Peyton, in press). Measures such as NWF and other pseudoword reading measures (e.g., Woodcock Reading Mastery Test-Revised Word Attack subtest; Woodcock, 1987) specifically isolate how well students apply their understanding of phonics rules in learning to decode. That is, NWF is designed to measure how well a student has learned the underlying letter-sound correspondences and phonological recoding skills of the alphabetic principle. The measure expressly avoids tapping student skills in reading real words because it may not be clear what strategies the student is using to accurately read real words (e.g., actually reading a word by deciphering the constituent letter-sound correspondences instead of recalling the whole word from memorization without knowledge of the constituent letter sounds).

NWF is one measure in the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) assessment system (Good & Kaminski, 2002a). Initial evidence for the technical adequacy of NWF was based on a study conducted in the Pacific Northwest (Good, Wallin, Simmons, Kame’enui, & Kaminski, 2002). The concurrent correlation with the Woodcock-Johnson Psycho-Educational Battery-Revised Readiness Cluster was .59 in February of first grade. The predictive correlation between NWF administered in January of first grade with Oral Reading Fluency (ORF) administered in the spring of first grade was .82.

Three published studies have further examined the validity of NWF. The correlation between level estimates (single point in time estimates) of NWF in the winter of first grade with ORF in the spring of first grade was .78, which accounted for 61% of the variance on the ORF outcome measure (Good, Simmons, & Kame’enui, 2001). Moreover, a stratified random sample (n = 330) of kindergarten students from a large urban school district in Philadelphia resulted in concurrent correlations of .62 with the Developmental Reading Assessment (Beaver, 1997) Instructional Reading score, .53 with the Test of Early Reading Ability-Third Edition (Reid, Hresko, & Hammill, 2001) Reading Quotient, and .56 with the Test of Early Reading Ability-Third Edition Alphabet subtest (Rouse & Fantuzzo, 2006). Predictive correlations with first- grade outcomes were reported as .63 for the Developmental Reading Assessment Instructional Reading score and .50 for the Terra Nova (CTB/ McGraw-Hill, 1997) Reading subtest (Rouse & Fantuzzo, 2006).

In a more recent study, Riedel (2007) focused on the relative contribution of NWF at the middle and end of first grade when both ORF and NWF were simultaneously administered to predict end-of-year reading comprehension. Although analyses of relative operating characteristic curves to determine optimal cut points were the primary focus of the study, correlational and logistic regression analyses were also reported. Predictive and concurrent correlations between NWF, administered at the middle and end of first grade, and the Group Reading Assessment and Diagnostic Evaluation, a group- administered standardized test of overall reading ability (Williams, 2001) administered at end of first grade, were .45 and .46. Logistic regression analyses indicated that ORF accounted for most of the variance in the Group Reading Assessment and Diagnostic Evaluation. The NWF correlations were significantly lower than correlations reported in previous studies, prompting Riedel to suggest that in the winter of first grade and at subsequent screening administrations it may be more efficient to use only ORF as a screener of reading comprehension. Riedel also suggested that earlier administrations of NWF (in the middle and end of kindergarten) might be a more important time frame for assessing performance on NWF.

Assessing the English Alphabetic Principle With English Learners

Documenting the psychometric properties of measures used to assess students in specific areas of reading, such as applying the alphabetic principle, is important in targeted reforms such as Reading First. Moreover, because these reforms are intended to include all students expected to meet state reading goals, it is important to understand how these types of measures function specifically with important subgroups of students such as English learners (ELs). In addition, given the prevalence of reading difficulties among ELs, assessments that can be used to help remediate reading difficulties are particularly critical (August & Shanahan, 2007).

A search of the literature did not reveal any published studies specifically examining the validity of pseudoword reading measures for ELs versus English speakers (ESs). Measures of pseudoword reading have been used with ELs and they do appear to be associated with higher order reading skills such as comprehension. For example, in a longitudinal study with ELs, researchers found that the alphabetic principle measured in kindergarten was the single best predictor of word reading and comprehension measured in second grade (Lesaux & Siegel, 2003). The pattern of relations may change depending on the difficulty level of the material. One study reported that ELs in second grade read simple texts at or slightly below their level of oral language proficiency with the same efficiency as ESs, indicating that oral proficiency in the second language contributed only marginally to efficiency of word reading or simple text reading (Geva & Yaghoub Zadeh, 2006). However, when reading materials were more demanding in terms of vocabulary and syntactic structures, oral language proficiency in the second language played a stronger role in text comprehension. Studies that have examined the impact of reading instruction in English with ELs using measures of pseudoword reading as an outcome measure indicate that associations between pseudoword reading measures and measures of reading comprehension may be different for ELs and ESs. Students with limited language proficiency may identify letter sounds (and read words and pseudowords that include these letter sounds) without necessarily knowing the meaning of the words they are decoding (Bialystock, Luk, & Kwan, 2005). Moreover, an EL whose native language is based on an alphabetic writing system (e.g., Spanish) may recognize letter sounds that are similar in English and Spanish (e.g., almost all consonants) without speaking English (Bialystock et al., 2005). In other words, ELs may be able to perform well on pseudoword reading tasks without necessarily having the English language and vocabulary skills required for adequate reading comprehension. However, a number of studies have shown that the best predictors of early reading in English for ELs are phonological awareness, print awareness, and alphabetic knowledge (Baker & Baker, 2008; Chiappe, Siegel, & Wade-Wooley, 2002; Durgunoglu, Nagy, & Hancin-Bhatt, 1993; Lesaux & Siegel, 2003), and that oral language proficiency does not predict how well children will learn phonological awareness and phonics (Geva & Yaghoub Zadeh, 2006). Together, these findings suggest that the relationship between pseudoword reading and other reading outcomes may be more complex for ELs than ESs.

Moderate to strong associations between ORF and reading comprehension are central to the rationale for using ORF as a measure of general reading proficiency (Baker et al., 2008; Fuchs & Deno, 1991; Hintze & Silberglitt, 2005; McGlinchey & Hixson, 2004; Stage & Jacobsen, 2001). In one study involving a comparison of ORF with ELs and ESs, correlation coefficients between ORF at pretest and performance on the Stanford Diagnostic Reading Comprehension subtest were not significantly different among EL and ES second- graders (.73 for ELs and .56 for ESs; Baker & Good, 1995). This finding was replicated with a different measure of comprehension and a different EL population (Hmong) among third- and fifth-grade students. The pattern of correlations was of moderate magnitude for both groups, somewhat higher in third grade for ESs (.71 vs. .61) and somewhat higher in fifth grade for ELs (.69 vs. .57; Wiley & Deno, 2005).

Studies of the differential functioning of ORF for ELs and ESs provide a framework for examining NWF in the current study. It is plausible that the NWF measure might function differently for these two groups of students. In particular, NWF, as an index of reading proficiency, might be less robust for ELs. That is, ELs may have the basic reading skills necessary for rapid and accurate decoding, but at the same time lack the underlying English language skills and vocabulary knowledge necessary to read with comprehension. If this were true, correlations between NWF and ORF may be similar, but the relation between NWF and a comprehensive measure of reading proficiency would be systematically lower for ELs than for ESs. Measuring the pattern of associations on NWF and criterion measures of reading with ELs and ESs in kindergarten through second grade will allow us to explore the nature of the association between pseudoword reading and other reading outcomes.

Purpose of the Study

In this study we investigated students’ knowledge of the alphabetic principle by examining concurrent and predictive relations among measures in the context of schools implementing Reading First. Situating this investigation in the context of Reading First provides a unique opportunity to examine how well a reading measure functions when reading instruction is organized around a cohesive set of instructional practices based on research and implemented to scale. This study specifically addressed the use of NWF (Good & Kaminski, 2002a) as a universal screening tool and as an index of beginning reading proficiency for all kindergarten through secondgrade students assessed in the context of schools implementing Reading First. A second focus was to investigate how NWF functioned with ELs. Nationally, an increasingly large percentage of students in U.S. schools are ELs, and in Oregon, the percentage of ELs in Reading First is approximately 30% (Baker et al., 2007). In Reading First, schools typically use the same measures to assess ELs and ESs. Many of these measures have not been empirically investigated with ELs specifically. The following research questions were addressed:

1. What is the strength of the association between NWF and criterion measures of reading performance for all kindergarten through second-grade students in participant schools?

2. What are the differences in the magnitude of the associations between NWF and criterion measures of reading for ELs and ESs?

3. How stable are NWF scores over time among ELs and ESs?

Method

Participants and Setting

Data for analyses were collected during the first 3 years of the Oregon Reading First implementation (i.e., 2003-2004 [Year 1], 2004- 2005 [Year 2], and 2005-2006 [Year 3]) and involved students in kindergarten, first grade, and second grade. In Years 1 and 2, all 34 Reading First schools were included in the analysis. In Year 3, 33 schools were included because one school discontinued participation in Oregon Reading First during the 2005-2006 school year. Schools eligible for Reading First in Oregon met specific criteria for student poverty level and reading performance. In the year prior to the first year of implementation (i.e., 2002-2003), 77% of students in Reading First schools qualified for free or reduced-cost lunch rates, and 27% of third-graders did not pass minimum proficiency standards on the Oregon Statewide Reading Assessment. During Year 2 (2004-2005), approximately 54% of students were of minority status, 34% of students were ELs, and 12% of students were in special education (Oregon Department of Education, 2006). The schools represented 14 districts. Approximately half of the schools were located in large urban areas, and the remaining schools were approximately equally divided between midsized cities with populations between 50,000 and 100,000 (8 schools) and rural areas (9 schools).

The analyses included ELs and ESs together and separately. Descriptive information about the two student groups is included in Table 1. The groups were similar in the proportion of male and female participants and the percentage reported as qualifying for special education services. Schools identified students as ELs by following state guidelines. These guidelines included two major components. First, data from a home language survey indicated that English was not the primary language spoken in the home. second, the student was administered an English language proficiency measure and scored at a level indicating the student was either a non-English speaker or was limited in his or her English language proficiency. For example, a cut score of three or lower on the Woodcock-Munoz Language Survey (1993) was commonly used as an indicator of EL status.

In Oregon Reading First, virtually all students in kindergarten through third grade participated in four assessments per year, at three regular times. In the fall, winter, and spring, students were administered DIBELS measures (Good & Kaminski, 2002a) as part of benchmark testing. In the spring, students were administered the reading subtest of the 10th edition of the Stanford Achievement Test (SAT-EI; Harcourt Educational Measurement, 2002), which is a group- administered, normreferenced test used in Oregon Reading First to help determine if students were reaching grade-level reading proficiency. Data were included in the analyses if students had a NWF data point in Years 1, 2, or 3.

Measures

DIBELS NWF (Good & Kaminski, 2002a). NWF was administered in the winter and spring of kindergarten; the fall, winter, and spring of first grade; and the fall of second grade (see Table 1). NWF (Good & Kaminski, 2002a) is a timed, fluency-based, standardized measure of students’ knowledge of the alphabetic principle or phonics. Students were presented with an 8.5- X 11-in. paper with consonant-vowel and consonant-vowel-consonant words arranged in a random order. The NWF item pool was selected so that the most frequently occurring letter sounds were represented and every letter corresponded to its most frequently occurring sound (Carnine, SiIbert, Kame’enui, & Tarver, 2004). Students were instructed to provide the sounds of the letters or to read the whole word. For example, on the stimulus item “tob,” students could sound out /t/ /o/ /b/ or read the whole word, tob. Although providing the individual sounds or reading the whole word yield the same points possible, the measure is fluency based and students earn a higher score if they are receding letter sounds into complete words accurately and rapidly. According to Good and Kaminski (2002a) alternate-form reliability for NWF ranged from .67 to .87, and concurrent validity coefficients with the readiness subtests of the Woodcock-Johnson Psycho-Educational Test ranged from .35 to .55. The total number of correct sounds identified in l min was recorded and used in the analyses.

DIBELS ORF. The DIBELS measure of ORF was administered in the spring of first grade and the spring of second grade (see Table 2). This ORF measure was developed following procedures used in the development of other curriculum-based measures (Shinn, 1989, 1998). ORF is a 1-min fluency measure that takes into account accuracy and speed of reading-connected text. Across an extensive number of research studies, ORF consistently is moderately to strongly associated with reading proficiency (Baker et al., 2008; Hintze & Silberglitt, 2005; McGlinchey & Hixson, 2004; Stage & Jacobsen, 2001). The difficulty level of the passages was calibrated by grade (Good & Kaminski, 2002b). In the standard administration protocol, students are administered three passages at each of three assessment points during the year and the median score is used as the representative performance score. In this study, the median passage from the spring administration was used in analysis. Alternate-form reliability drawn from the same level was .89 to .94. Test-retest reliabilities for elementary students ranged from .92 to .97 (Good & Kaminski, 2002b). In the context of Oregon specifically, the correlation between DIBELS ORF passages administered in third grade and the required Oregon State Reading Assessment (Oregon Department of Education, 2000; 2005) administered at the end of third grade was calculated with 364 students and was .67 (Good et al., 2001). The total number of correct words read in l min was recorded and used in the analyses.

SAT-10. In kindergarten, first, and second grade, all reading subtests of the SAT-IO (Harcourt Educational Measurement, 2002) were administered to all students in the spring, at the end of the school year (see Table 1). The SAT-10 is a group administered, norm- referenced test of overall reading proficiency. Kuder-Richardson reliability coefficients for total reading score were .97 at first grade and .95 at second grade. Correlations between the total reading score and the Otis-Lennon School Ability Test ranged from .61 to .74. Across grade levels, testing took between 110 and 155 min. The subtests administered in kindergarten were Sounds and Letters, Word Reading, and Sentence Reading. The subtests administered in first grade were Word Study Skills, Word Reading, Sentence Reading, and Reading Comprehension. The subtests administered in second grade were Word Study Skills, Reading Vocabulary, and Reading Comprehension. We used the total reading standard score, based on grade, in all analyses.

Data Collection Procedures

NWF and ORF measures were administered to students by school- based assessment teams. Each assessment team received a day of training on DIBELS administration and scoring. In addition, a reading coach at each school continued the assessment training by conducting calibration practice sessions with assessment team members. To maintain consistency across testers, the Reading First reading coaches conducted individual checks with each assessment team member before data collection. In addition, test-retest reliability data were collected on NWF and ORF in the spring of the 2004-2005 and 2005-2006 school years. In the spring of 2005 and 2006, six and eight schools, respectively, were randomly selected and 20% of the students in first and second grade were retested on all measures within 3 weeks of the original testing. Testretest reliability coefficients across grades ranged from .84 to .90 on NWF and .94 to .99 on ORF.

The Reading First coach supervised and monitored SAT-EI testing. Reading coaches at each school were trained by the Oregon Reading First state personnel. Coaches provided additional training to all teaching staff in their building on test administration and monitoring. Coaches observed testing procedures using a fidelity implementation checklist. Median fidelity on 18 test administration questions was 98.3%.

Data Analyses

Data analyses involved three steps. First, NWF was correlated with ORF scores in the winter of kindergarten through the spring of second grade and with SAT-EI standard scores in the spring of kindergarten through second grade. These correlations provide validity information about NWF with established, comprehensive measures of reading. second, ELs were compared with ESs and tested for differences in the validity correlations. Third, NWF assessments were correlated across time and tested for differences between ELs with ESs on the stability correlations.

Eighty-six correlations were computed and 39 pairs of correlations were compared to conduct the analyses. Thus, we accepted p values of .001 as statistically significant (Cohen, 1990). Even with this more rigorous standard for significance, all correlations were statistically significant. The individual correlations were based on between 450 and 7000 participants, depending on the student sample and the data available. Even with 450 participants, a correlation of .23 would have been statistically significant at p < .001. Because statistical significance provides little information in this situation, it is useful to interpret correlations as effect sizes (Rosenthal, Rosnow, & Rubin, 2000). However, Cohen (1990) suggests that squared correlations and differences between squared correlations offer a more meaningful metric. Thus, these indices of differences in squared correlations are reported.

Results

Descriptive Statistics

Table 1 presents the sample sizes and proportion of males and students in special education and the sample sizes, means, and standard deviations of the reading measures. The number of total cases is much larger than the number of participants who provided data on any one reading measure because the sample included students in kindergarten who may have been too young to provide data in first, second, or third grade. Similarly, some students entered the sample in second grade, which did not permit data collection in kindergarten or first grade.

Through inspection of data plots and skewness and kurtosis statistics, most reading measures at most assessment points were normally distributed. Although strict criterion values do not exist for skewness and kurtosis, values greater than 1.0 were observed for NWF in the winter and spring of kindergarten and fall and winter of first grade on skewness (2.2, 1.2, 1.9, and 1.2, respectively) and kurtosis (9.8, 3.7, 5.8, and 2.1). Skewed and leptokurtic distributions are not unexpected for performance measures administered early in a developmental sequence because most students are still in the process of learning the basics of a particular skill (e.g., learning to decode in kindergarten). However, bias from skewed data are unlikely in correlations based on large samples (Wang & Thompson, 2007).

Strength of Association Between NWF and Criterion Measures of Reading Performance

In relation to Research Question 1, correlations between NWF and criterion measures of reading (ORF and SAT-EI) provided evidence for the validity of the measure. Relevant correlations, reported for all participants in Table 2, ranged from .51 to .76. Among the predictive and concurrent associations, NWF accounted for between 26% and 58% of the variation in ORF, and between 31% and 54% of the variance in SAT-EI scores. Lower associations between NWF and ORF generally reflected greater amounts of time between test administrations. Correlations between NWF and the SAT-EI, however, remained relatively stable across the different times of NWF collection. The pattern of correlations is consistent with the assertion that the association between NWF and criterion measures of reading is moderate to strong.

Patterns of Association for ELs and ESs

For Research Question 2, differences were tested between ELs and ESs for each of these predictive and concurrent correlations using Fisher’s r-to-Z transformation (Rosenthal & Rosnow, 1991). Table 2 identifies the seven correlations (29% of the total) for which the amount of variance accounted for differed by 5% or greater for ELs and ESs. In these cases, the percent of variance accounted for was greater for ESs. Of these seven correlations, five involved NWF administered in the winter of kindergarten. On these occasions, differences in the percent of overlapping variance ranged from 10% to 13%.

Table 3 presents all of the predictive and concurrent correlations separately for ELs and ESs, along with sample sizes and p values for tests of differences between groups on independent correlations. Five of the 24 correlations in Table 3 represented statistically significant differences (p < .001) between ELs and ESs. In all 5 cases, the correlation was higher for ESs than ELs. In the majority of cases, the correlation magnitudes are similar for the two groups, moderate to strong in value, and slightly higher for ESs.

Stability Among NWF Assessments

Overall, NWF correlated moderately high, between .64 and .77, across successive assessments. Table 4 shows correlations for ELs in the lower left and ESs in the upper right. These correlations represent between 41% and 59% of the variance overlapping between successive administrations of NWF. Correlations diminished across broader time spans, dropping to .35 or 13% overlapping variance between the winter of kindergarten and fall of second-grade assessments for ELs.

Differences between ELs and ESs in stability correlations were tested using Fisher’s r-to-Z transformation. Three of the 15 correlations in Table 4 differed significantly between ELs and ESs. In all three cases the correlation was larger for ESs, and all 3 involved NWF measured in the winter of kindergarten. The largest difference, resulting in a discrepancy of 12% of the variance accounted for, occurred for the correlation between NWF measured in the winter and spring of kindergarten. Nine differences represented a discrepancy in overlapping variance of 5% to 10%, and 5 differed by less than 5%. Data presented in Table 4 confirm that in most instances, even where differences between ELs and ESs exceeded 5% overlapping variance, the correlations reached acceptable levels for both groups.

Discussion

The purpose of this study was to investigate NWF, a measure of the alphabetic principle, by examining concurrent and predictive correlations with criterion measures. Participating schools were implementing Reading First, a large federal initiative targeting reading outcomes in low-performing, high-poverty schools. The context in which the study was conducted is relevant in three ways. First, the study was conducted in schools in which NWF data were used to screen students, monitor progress, and adjust instruction to meet students’ needs. Schools contributing data to this study were similar in that they interpreted performance on NWF as an indication of how well students were learning the alphabetic principle. second, participating schools provided highly specified and research-based reading instruction. This instruction included a strong emphasis on the development of phonological awareness and decoding skills, both of which are captured by performance on NWF. Professional development focused on NWF as an explicit measure of initial decoding skill. Knowledge of the provided instruction contributed valuable information for interpreting the pattern of relations among reading measures. Third, a large number schools and students participated in this study, increasing the external validity of the findings. The study also focused on how NWF functioned specifically with ELs, a critical group of students who are strongly represented in Reading First nationally (Howe, Greenburg, & Levi, personal communication) and in Oregon specifically (Baker et al., 2007, 2008). Strength of Association Between NWF and Criterion Measures of Reading Performance

The strength of the association between NWF and criterion measures of reading performance was investigated for all students assessed in Reading First schools. Various administrations of the NWF measure from the middle of kindergarten through the fall of second grade accounted for moderate to large amounts of variation on two criterion measures (i.e., ORF and the SAT-10). Of 11 correlation coefficients between NWF and ORF, 18% were between .50 and .59, 36% were between .60 and .69, and 45% were between .70 and .79.

The performance of NWF in this study supports prior research demonstrating the validity of decisions made with pseudoword reading measures (Curtis, 1980; Gough, Juel, & Griffith, 1992; Rouse & Fantuzzo, 2006), and further justifies the use of pseudoword reading measures in reading assessment systems. Research has demonstrated that word reading proficiency is a key ingredient in reading comprehension, and pseudoword reading regularly accounts for a considerable amount of variance in word reading proficiency (Lyon, 1994). The validity coefficients found in this study largely replicate findings from earlier studies of NWF (Good et al, 2001, 2002; Rouse & Fantuzzo, 2006). However, concurrent and predictive validity estimates from this study were significantly higher in first grade than correlations reported by Riedel (.63 to .66 compared to .45 to .46; 2007). We do not have a clear idea why these differences may have occurred but do note the studies differed in terms of criterion outcome measures and student populations.

Regarding the within-grade correlations between NWF and the SAT- EI, it is interesting that the winter and spring kindergarten correlations were both .73; the fall, winter, and spring first- grade correlations were .65, .66, and .65, respectively; and the fall secondgrade correlation was .59. Despite the relative decrease in correlation magnitudes from kindergarten to second grade, it is noteworthy that a 1-min measure of phonics knowledge proved to be a robust indicator of overall reading proficiency across this critical period of reading development. In addition, the initial administration of NWF (i.e., winter of kindergarten) accounted for 31 % of the variance on the SAT-EI administered in the spring of second grade, 2.5 years later. Not only does this support the predictive validity of the measure, but it also signals the importance of learning the alphabetic principle early. These data, considered with other research, present compelling evidence that the 1-min NWF measure provides useful information about student facility with the alphabetic principle and that educators can use this information to help determine if students are on track for overall reading proficiency.

The NWF Measurement Construct for ELs and ESs

A second purpose of this study was to psychometrically examine how a measure of the alphabetic principle functions for an important group of students. To date, no study has examined the association between measures of the alphabetic principle and criterion measures of reading, such as ORF and the S AT-10, with ELs specifically. However, the current data are consistent with previous research on the use of fluency-based measures (e.g., curriculum-based measurement) to assess important early academic skill with ELs. For example, previous research found that ORF functioned similarly with Spanish-speaking ELs and ESs in second grade (Baker & Good, 1995). Although correlations between ORF and performance on a state reading test were higher in third grade for ESs than Hmong-speaking ELs, the reverse relationship was found in fifth grade (Wiley & Deno, 2005).

The current results are complex and intriguing regarding the extent to which NWF predicted performance on criterion measures of reading equally well for ELs and ESs. First, the fact that only 5 of 24 correlations were significantly different for ELs and ESs indicates that on the whole, NWF appears to function similarly for both groups. In other words, on 79% of the comparisons, the correlations were statistically equivalent for ELs and ESs. However, when a statistically significant difference was found, it is important to note that the correlations were higher for ESs.

Another index of the difference in correlation magnitudes is the proportion of overlapping variance. The difference in correlation magnitudes between ELs and ESs were categorized into three levels based on the percentage of overlapping variance: greater than 10%, between 5% and 10%, and lower than 5%. For 6 of 24 correlations (25%), the difference in overlapping variance was 10% or greater (the largest difference was 13%); for 3 of the 24 correlations (12%), the difference was between 5% and 10%; and for 15 of 24 correlations (63%), the difference was less than 5%. In other words, the difference in the amount of variance NWF accounted for on two criterion measures of reading was highly comparable for ELs and ESs in the majority of correlation comparisons.

It is important to consider that five of the six largest correlation differences between ELs and ESs in the percentage of overlapping variance involved the initial administration of NWF. which occurred in the winter of kindergarten. Given this pattern, it seems prudent for school psychologists and other school personnel to interpret performance on this measure in kindergarten with more caution for ELs. Perhaps for ELs, issues of early interpretation of measures such as NWF are complicated by the fact these students are pursuing mastery of academic content in a language that may be new for them. However, this is a hypothesis in need of empirical inquiry.

Stability Coefficients

The third purpose of this study was to examine the stability of NWF for ELs and ESs. On the whole, the stability correlations for NWF over time were highly comparable for these two groups. Only 3 of 15 stability coefficients (Table 4) were statistically different for ELs and ESs, and on only one coefficient did the difference in the amount of variance accounted for exceed 10%. All 3 of these correlations involved the initial administration of NWF in the winter of kindergarten. It may be that in the first half of kindergarten, measures of reading performance are less stable for ELs than ESs. In early kindergarten, for example, ELs have to learn that (a) letters represent sounds, and (b) that the association between letter sounds may be different depending on the language. Perhaps NWF is initially a more demanding or confusing task for ELs, but causes fewer difficulties by late kindergarten and first grade. Additional research is needed to identify the precise reasons for this pattern, but school psychologists can use this information to help interpret student performance.

Implications for Assessment

In summary, the NWF measure predicted an important portion of the variance on ORF and SAT-10 scores for all students involved in Reading First. Although there were discrepancies in predictive and concurrent correlations with criterion measures between ELs and ESs, most of the correlations were highly similar, and indicate robust performance of NWF across groups.

Evidence from this study, as well as other empirical studies focusing on DIBELS (Baker et al., 2008; Good et al., 2001, in press; Rousse & Fantuzzo, 2006; Francis, Santi, Barr, Fletcher, Varisco, & Foorman, 2008; Fuchs, Fuchs, & Compton, 2004; Riedel, 2007; Roehrig, Petscher, Nettles, Hudson, & Torgesen, 2008), should be considered in the context of recent intuitive criticisms of DIBELS. For example, DIBELS measures, including NWF, were described as unrelated to comprehension and were likely inappropriate for ELs because of dialect and other issues (Riedel, 2007; Goodman, 2006). However, both assertions are refuted by the data in this study. Concurrent correlations between NWF administered in kindergarten, first, and second grade were consistent and moderately to strongly related to performance on ORF and the SAT-10. Also, the relations between NWF and criterion measures of reading were typically as strong for ELs as ESs.

Regarding DffiELS generally, it has been suggested that DIBELS measures reflect superficial indicators of reading, little more than students “barking at print” (Samuels, 2007, p. 563). Decades of research on ORF has established the consistent association between reading fluency and comprehension. In the vast majority of these studies, fluency is defined as a combination of speed and accuracy of reading connected text, which is precisely the definition of ORF that the developers of DIBELS used when they constructed their measures. ORF is also highly correlated with prosody (Miller & Schwanenflugel, 2006). Indeed, the relationship between ORF and comprehension appears stronger than the association between prosody and comprehension, and there is only minimal evidence that reading with prosody mediates comprehension (Schwanenflugel, Hamilton, Kuhn, Wisenbaker, & Stahl, 2004). There are fewer studies on NWF than there are on ORF, and empirical investigations of these measures adjudicated through a peer-reviewed process should drive serious considerations of then- quality. In this regard, we would like to further encourage the examination of DIBELS in the context of intended and actual use in education settings. We plan to pursue this in future studies by examining DIBELS use in the context of the School-wide Beginning Reading Model (Kame’enui, Simmons, & Coyne, 2000). Data-based critiques of DIBELS are warranted, necessary, and could advance the field of formative evaluation systems (Fuchs et al., 2004; Francis et al., 2008). Providing psychometrically sound data to monitor the progress of students systematically over time is a major objective in multipurpose assessment systems such as DIBELS. Fuchs et al., and Francis et al. have raised questions about DIBELS measures for monitoring progress that should provide fertile ground for research (see also Baker et al., 2008, and Good et al., in press).

Implications for Practicing School Psychologists

Although the legislative origins differ for Reading First (i.e., No Child Left Behind) and RTI (i.e., Individuals with Disabilities Education Act, 2004), the underlying features of each initiative are highly similar (Gersten & Dimino, 2006). Both initiatives emphasize that the best way to prevent or minimize reading problems is through early identification and strategic intervention. Both Reading First and RTI emphasize school-wide approaches to reading instruction and insist that available resources within the school be directed toward the unified purpose of providing effective early reading instruction for all students, including students with reading problems, students who are ELs, and advanced readers. School psychologists are well positioned to understand the common goals of school-wide approaches to early reading instruction and can provide guidance on how to link various service delivery entities (e.g., Title 1, special education, and general education) that have the same underlying objectives.

Initiatives such as Reading First and RTI have led schools to implement kindergarten through third grade assessment systems that efficiently screen all students at the beginning of the year. Many school psychologists are aware of the predictive information derived from ORF, and that a measure like ORF is not sensitive to important knowledge and skill differences among students in kindergarten through the first half of first grade (Baker, Plasencia-Peinado, & Lezcano-Lytle, 1998; Fuchs, Fuchs, Hamlett, Walz, & Germann, 1993; Hasbrouck & Tindal, 2006). In a prevention-oriented approach to early reading instruction and intervention, waiting until the end of first grade to assess which children are at risk for reading difficulties limits the ability of schools to strategically intervene with specific students during a valuable period of instructional time. Of course, one solution is to assess students in kindergarten and the first part of first grade on measures that reliably and validly identify the best student candidates for interventions. Evidence from this study supports the use of NWF to screen students for reading problems and to help determine the level of instructional support students require.

In the context of Reading First, the findings of the current study suggest that schools teaching ELs to read in English should seriously consider interpreting the performance on a pseudoword reading measure such as NWF similarly for ELs as ESs. This type of interpretation may provide an instructional benefit for ELs. For instance, if ELs are being taught to read in English, this study suggests that problematic performance on NWF, used as a measure of the alphabetic principle and as an overall index of early reading performance, could be interpreted similarly for ELs and ESs. That is, low performance could be interpreted as a sign of concern. Difficulty decoding pseudowords may be attributable to a student not having received sufficient instruction in the alphabetic principle, or it may be that student’s difficulty understanding and applying the alphabetic principle stems from underlying physiological causes, a pattern that characterizes 5% to 7% of the population (Lyon, 1994). The various underlying causes of a student’s difficulty and subsequent instructional solutions may vary, but the ultimate goal should remain the same. Our best knowledge about how to help students instructionally is to focus on teaching them how to apply the alphabetic principle in reading, and this reading strategy should be applied consistently, systematically, and intelligently.

Limitations

A primary limitation of this study relates to external validity. By virtue of being in Reading First, participating schools shared two common characteristics. First, schools were selected to participate based on high poverty rates and low reading achievement. However, across the 3 years of the study, we observed an increase in student achievement (Baker et al., 2007), with Reading First schools becoming more similar to non-Reading First schools. second, by virtue of participating in Reading First, these schools agreed to implement scientifically based reading instruction. It is not known if these findings would be comparable in schools that deliver reading instruction that varies from approaches that stress explicit instruction in essential reading elements. A second limitation is that these findings are based on one state and one high-stakes reading measure (i.e., SAT-10). We do not know if these results would be similar in other states and with other types of high- stakes reading measures.

A third limitation of this study relates to the use of NWF for screening and progressmonitoring purposes. Although this study provides preliminary evidence for the use of NWF for the purposes of screening, future research needs to include additional analyses (e.g., relative operating characteristic curves) that will further refine the diagnostic accuracy of NWF for screening purposes. Moreover, because different conclusions are being reached about the use of NWF for the purpose of measuring students’ reading growth (Fuchs et al., 2004; Good et al., in press) we plan to investigate the function of growth to address these issues in future research.

Directions for Future Research

The current study represents a first step in a series of studies to examine the use of NWF as a screening and progress-monitoring tool. Fuchs (2004) recommends three stages for “substantiating the tenability” of a given progress-monitoring tool. Stage 1 involves the investigation of performance at one point in time. According to this framework, this current study would be characterized as a Stage 1 investigation. Stage 2 involves investigation into the technical features of slope or progress over time. Studies in the curriculum- based measures literature have documented student growth rates on various fluency-based measures (Deno, Fuchs, Marston, & Shin, 2001; Fuchs et al., 1993), but relatively few studies have documented how growth on a particular progress-monitoring measure is correlated with improvement in overall competence in the academic domain (Baker et al., 2008; Fuchs et al., 2004; Good et al., in press). Thus, future research on NWF should investigate how students grow on NWF over time and the relation between growth and performance on important outcome measures (Good et al., in press), and for important subgroups of students (e.g., ELs).

In Stage 3, the instructional utility of a measure is studied. This type of evidence is provided when a study examines how the use of a particular measure improves educational decisions and student achievement. Although not studied in an experimental design, we have preliminary evidence that the large-scale implementation of NWF as a screening measure in Reading First is associated with yearly gains on end-of-year NWF and ORF outcomes, and, perhaps more important, on yearly increases on the SAT-10 and the state reading test (Baker et al., 2007).

Future research with ELs should explore the interaction between instructional quality (e.g., Baker, Gersten, Haager, & Dingle, 2006) and response to instruction as measured through curriculum-based measures. Research should address the interaction of initial performance, response to instruction, and performance on criterion measures of reading at later points in time.

Conclusions

Evidence from this study supports the use of NWF in the early grades to screen students for reading problems. Using data to intervene early and strategically is a major assessment activity expected by schools in Reading First as well as schools using RTI to assist in making decisions about instructional effectiveness and special education. In our view, one strength of Reading First is the use of a comprehensive assessment framework for making decisions about students and program impact. This study provides evidence that NWF offers a robust index of early reading proficiency for students in kindergarten through first grade, including ELs and ESs. Our efforts to provide the type of instruction that students need should be evaluated regularly and vigorously, and the intensity of our instructional efforts should be increased regularly and systematically, to give students the best chance to master the alphabetic principle as quickly as possible. NWF could be an important component of those efforts. Date Received: June 22, 2007

Date Accepted: May 27, 2008

Action Editor: Matthew Burns

References

August, D., & Shanahan, L. (2006). Developing literacy in second- language learners: Report of the National Literacy Panel on Language Minority Children and Youth. Washington, DC: National Literacy Panel on Language-Minority Children and Youth (U.S.).

Baker, S. K., & Good, R. (1995). Curriculum-based measurement of English reading with bilingual Hispanic students: A validation study with second-grade students. School Psychology Review, 24, 561-579.

Baker, S. K., Plasencia-Peinado, J., & Lezcano-Lytle, V. (1998). The use of curriculum-based measurement with language-minority students. In M. R. Shinn (Ed.), Advanced applications of curriculum- based measurement (pp. 175-213). New York: Guilford Press.

Baker, S. K., Smolkowski, K., Katz, R., Fien, H., Seeley, J., Kame’enui, E., et al. (2008). Reading fluency as a predictor of reading proficiency in low performing high poverty schools. School Psychology Review, 37, 18-37.

Baker, S. K., & Baker, D. L. (2008). English learners and response to intervention: Improving quality of instruction in general and special education. In E. L. Grigorenko (Ed.), Educating individuals with disabilities: IDEA 2004 and beyond (pp. 249-272). New York: Springer.

Baker, S. K., Gersten, R., Haager, D., & Dingle, M. (2006). Teaching practice and the reading growth of first-grade English learners: Validation of an observation instrument. Elementary School Journal, 107, 200-219.

Baker, S. K., Smith, J. M., Fien, H., Otterstedt, J., Katz, R., Baker, D. L., et al. (2007). Three year Oregon Reading First report. Eugene: Pacific Institutes for Research, University of Oregon.

Beaver, J. (1997). Developmental reading assessment. Upper Arlington, OH: Upper Arlington City Schools.

Beech, J. R., & Awaida, M. (1992). Lexical and nonlexical routes: A comparison between normally achieving and poor readers. Journal of Learning Disabilities, 25, 196-206.

Bialystok, E., Luk, G., & Kwan, E. (2005). Bilingualism, biliteracy, and learning to read: Interactions among languages and writing systems. Scientific Studies of Reading, 9, 43-61.

Camine, D., Silbert, J., Kame’enui, E., & Tarver, S. (2004). Direct instruction reading (4th ed.). Upper Saddle River, NJ: Pearson.

Chiappe, P., Siegel, L., & Wade-Woolley, L. (2002). Linguistic diversity and the development of reading skills: A longitudinal study. Scientific Studies of Reading, 6, 369-400.

Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304.

CTB/McGraw-Hill. (1997). CTBS complete battery. Monterey, CA: CTB/ McGraw-Hill.

Curtis, M. E. (1980). Development of components of reading skill. Journal of Educational Psychology, 72, 656-669.

Deno, S. L., Fuchs, L. S., Marston, D., & Shin, J. (2001). Using curriculum-based measurement to establish growth standards for students with learning disabilities. School Psychology Review, 30, 507-524.

Durgunoglu, A. Y., Nagy, W. E., & Hancin-Bhatt, B. J. (1993). Cross-language transfer of phonological awareness. Journal of Educational Psychology, 85, 453-465.

Felton, R. H., & Wood, F. B. (1992). A reading level match study of nonword reading skills in poor readers with varying IQ. Journal of Learning Disabilities, 25, 318-326.

Finn, J., Gerber, S., & Boyd-Zaharias, J. (2005). Small classes in the early grades, academic achievement, and graduating from high school. Journal of Educational Psychology, 97, 214-223.

Francis, D., Santi, K. L., Barr, C., Fletcher, J., Varisco, A., & Foorman, B. (2008). Form effects on the estimation of students’ oral reading fluency using DIBELS. Journal of School Psychology, 46 315- 342.

Fuchs, L. S. (2004). The past, present, and future of curriculum- based measurement research. School Psychology Review, 33, 188-192.

Fuchs, L. S., & Deno, S. L. (1991). Paradigmatic distinctions between instructionally relevant measurement models. Exceptional Children, 57, 488-500.

Fuchs, L. S., Fuchs, D., & Compton, D. L. (2004). Monitoring early reading development in first grade: Word identification fluency versus nonsense word fluency. Exceptional Children, 71, 7.

Fuchs, L. S., Fuchs, D., Hamlett, C. L., Walz, L., & Germann, G. (1993). Formative evaluation of academic progress: How much growth can we expect? School Psychology Review, 22, 27-48.

Gersten, R., & Dimino, J. A. (2006). New directions in research- Current issues in special education and reading instruction-RTI (Response to intervention): Rethinking special education for students with reading difficulties (yet again). Reading Research Quarterly, 41, 92.

Geva, E., & Yaghoub Zadeh, Z. (2006). Reading efficiency in native English-speaking and English-as-a-second-language children: The role of oral proficiency and underlying cognitive-linguistic processes. Scientific Studies of Reading, 10, 31-57.

Good, R., Baker, S., & Peyton, J. (in press). Making sense of nonsense word fluency: Determining adequate progress in early first grade reading. Reading & Writing Quarterly.

Good, R. H., & Kaminski, R. A. (2002a). Nonsense Word Fluency. In R. H. Good & R. A. Kaminski (Eds.), Dynamic Indicators of Basic Early Literacy Skills (6th ed.). Eugene, OR: Institute for Development of Educational Achievement. Available from http:// dibels .uoregon.edu/

Good, R. H., & Kaminski, R. (2002b). DIBELS Oral Reading Fluency passages for first through third grades (Technical Report No. 10). Eugene: University of Oregon.

Good, R. H., Simmons, D. C., & Kame’enui, E. J. (2001). The importance and decision-making utility of a continuum of fluency- based indicators of foundational reading skills for third-grade high- stakes outcomes. Scientific Studies of Reading, 5, 257-288.

Good, R. H., Wallin, 1. U., Simmons, D., Kame’enui, E. J., & Kaminski, R. (2002). System-wide percentile ranks for DIBELS benchmark assessment (Technical Report No. 9). Eugene: University of Oregon.

Goodman, K. S. (2006). A critical review of DIBELS. In K. S. Goodman (Ed.), The truth about DlBELS: What it is, what it does (pp. 1-39). Portsmouth, NH: Heinemann.

Gough, P., Juel, C., & Griffith, P. (1992). Reading, spelling and the orthographic cipher. In P. Gough, L. Enri, & R. Treiman (Eds.), Reading acquisition (pp. 35-48). Hillsdale, NJ: Erlbaum.

Harcourt Educational Measurement. (2002). Stanford Achievement Test [SAT-IO]. San Antonio, TX.

Hasbrouck, J., & Tindal, G. A. (2006). Oral reading fluency norms: A valuable assessment tool for reading teachers. The Reading Teacher, 59, 636-646.

Hintze, J., & Silberglitt, B. (2005). A longitudinal examination of the diagnostic accuracy and predictive validity of R-CBM and high- stakes testing. School Psychology Review, 34, 372-386.

Individuals with Disabilities Education Act of 2004, pub. L. 108- 466, (2004).

Kame’enui, E. J., Simmons, D. C., & Coyne, M. D. (2000). Schools as host environments: Toward a school-wide reading improvement model. Annals of Dyslexia, 50, 31-52.

Lesaux, N., & Siegel, L. (2003). The development of reading in children who speak English as a second language. Developmental Psychology, 39, 1005-1020.

Lyon, G. R. (1994). Frames of reference for the assessment of learning disabilities: New views on measurement issues. Baltimore, MD: Brookes.

Manis, F., Szeszulski, P. A., Holt, L. K., & Graves, K. (1990). Variation in component word recognition and spelling skills among dyslexic children and normal readers. In T. Carr & B. A. Levy (Eds.), Reading and its development: Component skills approaches (pp. 207-259). New York: Academic Press.

McGlinchey, M. T., & Hixson, M. D. (2004). Contemporary research on curriculum-based measurement: Using curriculum-based measurement to predict performance on state assessments in reading. School Psychology Review, 33, 193-204.

Miller, J. S., & Schwanenflugel, P. J. (2006). Prosody of syntactically complex sentences in the oral reading of young children. Journal of Educational Psychology, 84, 839-853.

National Reading Panel. (2002). Summary of the US National Reading Panel Report: Teaching children to read. Newark, DE: Division of Research and Policy, International Reading Association.

National Reading Panel. (2000). Report of the National Reading Panel: Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction. Washington, DC: National Institute of Child Health and Human Development.

National Research Council. (1998). Preventing reading difficulties in young children. Washington, DC: National Academy Press.

No Child Left Behind Act of 2001. (PL 107-110). Title I, part B, student reading skills improving grants, subpart 1, Reading First.

Oregon Department of Education. (2000). Report cards-School and district. Salem: Oregon Department of Education.

Oregon Department of Education. (2005). Closing the achievement gap: Oregon ‘s plan for Success for All Students. Salem: Oregon State Department of Education.

Oregon Department of Education. (2006). Oregon Reading First. Retrieved August 9, 2006, from http://www .ode.state.or.us/search/ results/?id=96

Oregon Reading First, (n.d.). Curriculum review. Retrieved January 28, 2008, from http://oregonreadingfirst.uoregon.edu/ curriculum_review.php

Reading First. P.L. 107-110, Part B, Subpart 1, 2002.

Reading First, P.L. 108-446, Part B, sec 614 [b][6][b] 2002.

Reid, D. K., Hresko, W. P., & Hammill, D. D. (2001). Test of Early Reading Ability-Third Edition. Austin, TX: Pro-Ed.

Riedel, B. W. (2007). The relation between DIBELS, reading comprehension, and vocabulary in urban firstgrade students. Reading Research Quarterly, 42, 546567.

Roehrig, A. D., Petscher, Y., Nettles, S. M., Hudson, R. F., & Torgesen, J. K. (2008). Accuracy of the DffiELS Oral Reading Fluency measure for predicting third grade reading comprehension outcomes. Journal of School Psychology, 46, 343-366.

Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw- Hill. Rosenthal, R., Rosnow, R. L., & Rubin, D. B. (2000). Contrasts and effect sizes in behavioral research: A correlational approach. New York: Cambridge University Press.

Rouse, H. L., & Fantuzzo, J. W. (2006). Validity of the Dynamic Indicators for Basic Early Literacy Skills as an indicator of early literacy for urban kindergarten children. School Psychology Review, 35, 341-356.

Samuels, S. J. (2007). Commentary: The DIBELS tests: Is speed of barking at print what we mean by reading fluency? Reading Research Quarterly, 42, 563-566.

Schwanenflugel, P. J., Hamilton, A. M., Kuhn, M. R., Wisenbaker, J. M., & Stahl, S. A. (2004). Becoming a fluent reader: Reading skill and prosodie features in the oral reading of young readers. Journal of Educational Psychology, 96, 119-129.

Shinn, M. R. (1989). Curriculum-based measurementAssessing special children. New York: Guilford Press.

Shinn, M. R. (1998). Advanced applications of curriculum-based measurement. New York: Guildford Press.

Stage, S. A., & Jacobsen, M. D. (2001). Predicting student success on a state-mandated performance-based assessment using Oral Reading Fluency. School Psychology Review, 30, 407-420.

Wang, Z., & Thompson, B. (2007). Is the Pearson r2 biased, and if so, what is the best correction formula? Journal of Experimental Education, 75, 109-125.

Wiley, H. I., & Deno, S. L. (2005). Oral reading and maze measures as predictors of success for English learners on a state standards assessment. Remedial & Special Education, 26, 207-214.

Williams, K. T. (2001). Technical manual: Group Reading Assessment and Diagnostic Evaluation. Circle Pines, MN: American Guidance Service.

Woodcock, R. (1987). Woodcock Reading Mastery Test-Revised. Circle Pines, MN: American Guidance.

Woodcock, R. W., & Munoz-Sandoval, M. R. (1993). Woodcock-Munoz Language Survey-English. Itasca, IL: Riverside Publishing Company.

Hank Fien

University of Oregon

Scott K. Baker

Pacific Institutes for Research, University of Oregon

Keith Smolkowski

Abacus Consulting, Oregon Research institute

Jean L. Mercier Smith

Pacific Institutes for Research

Edward J. Kame’enui and Carrie Thomas Beck

University of Oregon

This work was supported by an Oregon Reading First subcontract from the Oregon Department of Education to the University of Oregon (8948). The original Oregon Reading First grant was made from the U.S. Department of Education grant to the Oregon Department of Education (S357A0020038).

Correspondence regarding this article should be addressed to Scott K. Baker, Pacific Institutes for Research, University of Oregon, 1600 Millrace Drive, Suite 109, Eugene, OR 97403; E-mail: sbaker@uoregon.edu

Copyright 2008 by the National Association of School Psychologists, ISSN 0279-6015

Hank Fien received his PhD from the University of Oregon in 2004. He is currently Research Associate at the Center on Teaching and Learning, where he serves as Principal Investigator of an Institute of Education Sciences grant evaluating the impact of a read-aloud curriculum on students’ vocabulary acquisition and oral retell skills. His research interests include using formative assessments to guide instructional decision making and empirically validating interventions aimed at preventing or ameliorating student academic problems.

Scott K. Baker, PhD, is Director of Pacific Institutes for Research and Associate Director at the Center on Teaching and Learning. His research interests are in literacy and mathematics interventions and the instructional needs of English language learners.

Keith Smolkowski, PhD, is Associate Scientist and Research Analyst at Oregon Research Institute and Research Methodologist at Abacus Research, LLC. His professional work involves research on early literacy instruction, curriculum-based measurement, child and adolescent social behavior, and teacher and parent behavior management practices. His methodological work has focused on the design and analysis of group-randomized trials and the statistical modeling of longitudinal, multilevel data.

Jean L. Mercier Smith, PhD, is Research Associate at the Pacific Institutes for Research. Her research interests include data-based decision making for instructional leaders, school-wide systems of instructional support, and beginning reading instruction for English learners.

Edward J. Kame’enui, PhD, is Dean-Knight Professor of Education and Director of the Institute for the Development of Educational Achievement and the Center on Teaching and Learning in the College of Education at the University of Oregon. His areas of interest include the prevention of reading failure, school-wide implementation of beginning reading instruction, and the design and delivery of effective teaching and assessment strategies and systems.

Carrie Thomas Beck, PhD, is Research Associate at the University of Oregon. Her research and teaching interests are in the areas of early literacy, vocabulary instruction, and instructional design.

Copyright National Association of School Psychologists Fall 2008

(c) 2008 School Psychology Review. Provided by ProQuest LLC. All rights Reserved.