DIBELS 6th Edition
Nonsense Word Fluency – Correct Letter Sounds

Descriptive Information

Please provide a description of your tool:

DIBELS Nonsense Word Fluency (NWF) is a standardized, individually-administered test of the alphabetic principle – including letter-sound correspondence and of the ability to blend letters into words in which letters represent their most common sounds. The student is presented an 8.5” x 11” sheet of paper with randomly ordered VC and CVC nonsense words (e.g., sig, rav, ov) and asked to produce verbally either (a) the individual letter sound of each letter, or (b) verbally produce, or read, the whole nonsense word. For example, if the stimulus word is “mip” the student could say /m/ /i/ /p/ or say the word /mip/ to obtain a total of three correct letter sounds (CLS). The student is allowed 1 minute to produce as many letter-sounds as she can, and the final score is the number of letter-sounds produced correctly in one minute. Because the measure is fluency based, students receive a higher score if they are phonologically recoding the word and receive a lower score if they are providing letter sounds in isolation. The NWF measure takes about 2 minutes to administer and has over 20 alternate forms, per grade, for monitoring progress. Cut points for intensive intervention are addressed in this application. Benchmark cut points, as well as cut points for intensive intervention, are available at https://dibels.uoregon.edu/docs/marketplace/dibels/DIBELS-6Ed-Goals.pdf

The tool is intended for use with the following grade(s).

Preschool / Pre - kindergarten
Kindergarten
First grade
Second grade
Third grade
Fourth grade
Fifth grade
Sixth grade
Seventh grade
Eighth grade
Ninth grade
Tenth grade
Eleventh grade
Twelfth grade

The tool is intended for use with the following age(s).

0-4 years old
5 years old
6 years old
7 years old
8 years old
9 years old
10 years old
11 years old
12 years old
13 years old
14 years old
15 years old
16 years old
17 years old
18 years old

The tool is intended for use with the following student populations.

Students in general education
Students with disabilities
English language learners

ACADEMIC ONLY: What skills does the tool screen?

Reading

Phonological processing:

RAN
Memory
Awareness
Letter sound correspondence
Phonics
Structural analysis

Word ID

Accuracy
Speed

Nonword

Accuracy
Speed

Spelling

Accuracy
Speed

Passage

Accuracy
Speed

Reading comprehension:

Multiple choice questions
Cloze
Constructed Response
Retell
Maze
Sentence verification
Other (please describe):

Listening comprehension:

Multiple choice questions
Cloze
Constructed Response
Retell
Maze
Sentence verification
Vocabulary
Expressive
Receptive

Mathematics

Global Indicator of Math Competence

Accuracy
Speed
Multiple Choice
Constructed Response

Early Numeracy

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Concepts

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Computation

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematic Application

Accuracy
Speed
Multiple Choice
Constructed Response

Fractions/Decimals

Accuracy
Speed
Multiple Choice
Constructed Response

Algebra

Accuracy
Speed
Multiple Choice
Constructed Response

Geometry

Accuracy
Speed
Multiple Choice
Constructed Response

Other (please describe):

Please describe specific domain, skills or subtests:

BEHAVIOR ONLY: Which category of behaviors does your tool target?

Internalizing
Externalizing
Internalizing and Externalizing

BEHAVIOR ONLY: Please identify which broad domain(s)/construct(s) are measured by your tool and define each sub-domain or sub-construct.

Acquisition and Cost Information

Where to obtain:

Email Address

support@dibels.uoregon.edu

Address

5292 University of Oregon, Eugene, OR 97403

Phone Number

1-888-497-4290

Website

https://dibels.uoregon.edu

Initial cost for implementing program:

Cost

$0.00

Unit of cost

student

Replacement cost per unit for subsequent use:

Cost

Unit of cost

Duration of license

Additional cost information:

Describe basic pricing plan and structure of the tool. Provide information on what is included in the published tool, as well as what is not included but required for implementation.

All materials required for administration are available for free download at https://dibels.uoregon.edu. The DIBELS Data System (DDS) is not required, but is available for online data entry, management and reporting for a cost of $1.00 per student per year. Included with the DDS service is optional tablet based administration through the HiFi Reading app available for free download at the Apple app store. Training is required for assessors and is available through online DDS training modules. The cost of the training ranges from $40 - $79 per person. Additional costs include the cost of printing and the cost of a computer (required) and tablets (optional).

Provide information about special accommodations for students with disabilities.

The DIBELS directions are designed to be used unmodified with all students. They have been validated with tens of thousands of students to work the way they do. In a very small number of cases though, a small number of accommodations are approved. They are used only in situations where they are necessary to obtain an accurate score for a student. When approved accommodations are used, the examiner should mark an “A” on the front cover of the testing booklet. Scores with accommodations can be used as any another of DIBELS scores. Approved accommodations should only be used with students who have a documented need for such supports, not to improve performance for multiple students. DIBELS 6th Edition approved accommodations for NWF are: • Enlarged student materials • Colored overlays, filters or lighting adjustments • Assistive technology (e.g., hearing aids, assistive listening devices) Marker or ruler for tracking

Administration

BEHAVIOR ONLY: What type of administrator is your tool designed for?

General education teacher
Special education teacher
Parent
Child
External observer
Other

If other, please specify:

What is the administration setting?

Direct observation
Rating scale
Checklist
Performance measure
Questionnaire
Direct: Computerized
One-to-one
Other

If other, please specify:

Does the tool require technology?

No

If yes, what technology is required to implement your tool? (Select all that apply)

Computer or tablet
Internet connection
Other technology (please specify)

If your program requires additional technology not listed above, please describe the required technology and the extent to which it is combined with teacher small-group instruction/intervention:

What is the administration context?

Individual
Small group   If small group, n=
Large group   If large group, n=
Computer-administered
Other

If other, please specify:

What is the administration time?

Time in minutes

2

per (student/group/other unit)

student

Additional scoring time:

Time in minutes

1

per (student/group/other unit)

student

ACADEMIC ONLY: What are the discontinue rules?

No discontinue rules provided
Basals
Ceilings
Other

If other, please specify:

If the student does not get any sounds correct in words 1-5, discontinue the task and record a score of 0.

Are norms available?

Yes

Are benchmarks available?

Yes

If yes, how many benchmarks per year?

Two for kindergarten (middle and end of year), three for first grade (beginning, middle and end of year), and one for second grade (beginning of year). Beginning- and middle-of-year benchmarks are included for review in this submission.

If yes, for which months are benchmarks available?

Beginning months are typically September, October and November; middle months are December, January, and February; and end months are typically March, April, May and June. Regardless of when the benchmark occurs, we recommend that all students are tested within a one-month window. If DIBELS NWF is administered outside of that one month time frame, it should not be entered as the benchmark score for the student

BEHAVIOR ONLY: Can students be rated concurrently by one administrator?

If yes, how many students can be rated concurrently?

Training & Scoring

Training

Is training for the administrator required?

Yes

Describe the time required for administrator training, if applicable:

1-4 hours of training

Please describe the minimum qualifications an administrator must possess.

Paraprofessional

No minimum qualifications

Are training manuals and materials available?

Yes

Are training manuals/materials field-tested?

Yes

Are training manuals/materials included in cost of tools?

No

If No, please describe training costs:

Online training for administration and scoring of DIBELS 6th edition is available at https://dibels.uoregon.edu/training/. The cost of the training ranges from $40 - $79 per person and includes all DIBELS 6th Edition subtests. Cost depends on whether a group discount is applied, and whether the trainee is a DIBELS Data System customer.

Can users obtain ongoing professional and technical support?

Yes

If Yes, please describe how users can obtain support:

Technical support is available from the DIBELS Data System at the University of Oregon, https://dibels.uoregon.edu (phone: 1-888-497-4290, email: support@dibels.uoregon.edu, hours of operation: 6:00am to 5:30pm Pacific Time, Monday through Friday).

Scoring

How are scores calculated?

Manually (by hand)
Automatically (computer-scored)
Other

If other, please specify:

Do you provide basis for calculating performance level scores?

Yes

What is the basis for calculating performance level and percentile scores?

Age norms
Grade norms
Classwide norms
Schoolwide norms
Stanines
Normal curve equivalents

What types of performance level scores are available?

Raw score
Standard score
Percentile score
Grade equivalents
IRT-based score
Age equivalents
Stanines
Normal curve equivalents
Developmental benchmarks
Developmental cut points
Equated
Probability
Lexile score
Error analysis
Composite scores
Subscale/subtest scores
Other

If other, please specify:

Does your tool include decision rules?

Yes

If yes, please describe.

Grade-based, empirically determined cut points for risk and benchmark goals, based on ROC analyses predicting performance at the 20th and 40th percentile on the SAT-10 Total Reading.

Can you provide evidence in support of multiple decision rules?

Yes

If yes, please describe.

Please describe the scoring structure. Provide relevant details such as the scoring format, the number of items overall, the number of items per subscale, what the cluster/composite score comprises, and how raw scores are calculated.

There are two types of raw scores that can be calculated for NWF. The first, correct letter sounds (CLS) is calculated by adding the number of letter-sounds produced correctly in one minute. The second, words recoded completely and correctly (WRC) is calculated by adding the total number of nonwords that were recoded correctly in one minute. This screening application focuses specifically on CLS. There is no cluster/composite score for NWF. Describe the tool’s approach to screening, behavior samples, test format, and/or scoring practices, including steps taken to ensure that it is appropriate for use with culturally and linguistically diverse populations and students with disabilities.

Describe the tool’s approach to screening, samples (if applicable), and/or test format, including steps taken to ensure that it is appropriate for use with culturally and linguistically diverse populations and students with disabilities.

DIBELS NWF is a standardized, individually administered test of a student's alphabetic principle skills, including letter-sound correspondences and of the ability to blend letters into words in which letters represent their most common sounds. NWF is designed for use with students in kindergarten through grade 2. The student is presented with randomly ordered Vowel-Consonant (e.g., ig, ot) and Consonant-Vowel - Consonant (e.g., sim, tob, lut) nonsense words on an 8.5”x11” sheet of paper and asked to verbally produce the individual letter sound of each letter or read the whole nonsense word. For example, if the stimulus word is “sig” the student could say, /s/ /i/ /g/ or say the word “sig” to obtain a total of three letter-sounds correct. The student is allowed one minute to produce as many letter-sounds as he/she can, and the final score is the number of letter-sounds produced correctly in one minute. The tool provides information on student performance in English. There are specific scoring rules regarding articulation and dialect to mitigate linguistic bias. Students are not penalized for differences in speech production that are the result of dialect, first-language, or articulation

Classification Accuracy & Cross-Validation Summary

Grade	Kindergarten	Grade 1	Grade 2
Classification Accuracy Fall
Classification Accuracy Winter
Classification Accuracy Spring

Stanford Achievement Test: 10th Edition (SAT-10)

Classification Accuracy

Select time of year

Fall

Winter

Spring

Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.

The Stanford Achievement Test – 10th Edition (SAT-10; Harcourt Educational Measurement, 2002) was administered to students in grades 1 and 2 as the outcome measure that would indicate "healthy" reading performance at the end of the school year. The SAT-10 is external to the DIBELS assessment system and is a nationally recognized test primarily developed to measure student achievement in reading in kindergarten through grade 12. The SAT-10 is a group-administered, norm-referenced test of overall reading proficiency. The measure is not timed, although guidelines with flexible time recommendations are given. In first grade, all four recommended subtests were administered: Word Study Skills, Word Reading, Sentence Reading, and Reading Comprehension. This battery takes about 155 minutes to complete. In second grade, three subtests were administered: Word Study Skills, Reading Vocabulary, and Reading Comprehension. This battery takes about 110 minutes to complete. Correlations between the total reading score and the Otis-Lennon School Ability Test ranged from .61 – .74. The normative sample is representative of the U.S. student population. Across all testing occasions, students below the 20th percentile on the SAT10 were identified as needing intensive intervention.

Do the classification accuracy analyses examine concurrent and/or predictive classification?

Concurrent
Predictive

Describe when screening and criterion measures were administered and provide a justification for why the method(s) you chose (concurrent and/or predictive) is/are appropriate for your tool.

Describe how the classification analyses were performed and cut-points determined. Describe how the cut points align with students at-risk. Please indicate which groups were contrasted in your analyses (e.g., low risk students versus high risk students, low risk students versus moderate risk students).

We used a two-stage process for determining cut-points for intensive need. First, we plotted Receiver Operating Characteristic (ROC) curves at each time point and grade and the associated end-of-year criterion measure and determined the area under the curve (A). Prior to conducting our analyses, we decided to calculate cut points only for those measures and time points where the AUC met or exceeded .75. An AUC of less than .75 suggests that the measure may not represent accuracy beyond teacher judgment, and we believe that providing cut-points for measures with an AUC value less than .75 would imply greater confidence in the measures than is warranted. Second, we conducted a diagnostic analysis of each measure at each time point (i.e., season. For each analysis, we examined two statistics: sensitivity and specificity. We chose to focus on sensitivity and specificity (rather than PPV and NPV) because they remain stable indicators regardless of the prevalence of reading difficulties in the population (Pepe, 2003). Further, we emphasized sensitivity in our analyses because of its practical application in a prevention model in education. Specifically, we want to be confident that students receive the instructional support they require as early as possible. All cut-points were determined using an optimal decision threshold associated with sensitivity at or above .80. This criterion roughly corresponds to the statement that, we will miss an opportunity to provide additional support to only 20% of students who are likely to score below the 20th percentile on the SAT10.

Were the children in the study/studies involved in an intervention in addition to typical classroom instruction between the screening measure and outcome assessment?

Yes

If yes, please describe the intervention, what children received the intervention, and how they were chosen.

All students were part of the Oregon Reading First study. Each participating school provided at least 90 minutes of daily, scientifically based reading instruction for all kindergarten through third-grade students with a minimum of 30 minutes of daily small-group, teacher-directed reading instruction.

Cross-Validation

Has a cross-validation study been conducted?

No

If yes,

Select time of year.

Fall

Winter

Spring

Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.

Do the cross-validation analyses examine concurrent and/or predictive classification?

Concurrent
Predictive

Describe when screening and criterion measures were administered and provide a justification for why the method(s) you chose (concurrent and/or predictive) is/are appropriate for your tool.

Describe how the cross-validation analyses were performed and cut-points determined. Describe how the cut points align with students at-risk. Please indicate which groups were contrasted in your analyses (e.g., low risk students versus high risk students, low risk students versus moderate risk students).

Were the children in the study/studies involved in an intervention in addition to typical classroom instruction between the screening measure and outcome assessment?

If yes, please describe the intervention, what children received the intervention, and how they were chosen.

---

Classification Accuracy - Fall

Evidence	Grade 1	Grade 2
Criterion measure	Stanford Achievement Test: 10th Edition (SAT-10)	Stanford Achievement Test: 10th Edition (SAT-10)
Cut Points - Percentile rank on criterion measure	20	20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	19 correct letters	52 correct letters
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)	0.84	0.82
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.83	0.81
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.85	0.83

Statistics	Grade 1	Grade 2
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Grade 1	Grade 2
Date	2003-06
Sample Size
Geographic Representation	Pacific (OR)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Winter

Evidence	Kindergarten	Grade 1
Criterion measure	Stanford Achievement Test: 10th Edition (SAT-10)	Stanford Achievement Test: 10th Edition (SAT-10)
Cut Points - Percentile rank on criterion measure	20	20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	15 correct letters	48 correct letters
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)	0.85	0.87
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.84	0.86
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.86	0.88

Statistics	Kindergarten	Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1
Date	2003-06	2003-06
Sample Size
Geographic Representation	Pacific (OR)	Pacific (OR)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Reliability

Grade	Kindergarten	Grade 1	Grade 2
Rating

*Offer a justification for each type of reliability reported, given the type and purpose of the tool.

We evaluated alternate form reliability and test-retest reliability to assess the reliability of DIBELS 6th Edition NWF CLS subtest. Alternate form reliability: Alternate-form reliability indicates the extent to which test results generalize to different item samples. Students are tested with two or more different (i.e., alternate) but equivalent forms of the test within some relatively short interval of time, and scores from these forms are correlated. The use of alternate form reliability is justified because it uses different but equivalent forms, thereby avoiding practice effects inherent in test-retest reliability where the same form is administered twice. In addition, it is important to establish that different forms are equivalent given the need to use different forms for progress-monitoring across year. Test-retest reliability: Test-retest reliability is evaluated by administering a same test to same individuals twice within a short interval and correlating scores from the two test administrations. Test-retest reliability provides some measure of reliability without the confound of (expected) student growth between administration. It also ensures representativeness and stability of a test over time.

*Describe the sample(s), including size and characteristics, for each reliability analysis conducted.

Study a: Kindergarten alternate form reliability: Participants were from five half-day kindergarten classes in a suburban school district in the middle Atlantic states. Students selected were those believed to have enough English skills to benefit from English instruction. Selections were made after students were ranked by their teachers as having high, average, or low literacy skills to obtain a sampling of skill levels. 25.6% of the students had a primary language other than English. Study d: Grade 1 test-retest reliability: Participants were 938 students from two Pacific Northwest school districts. The first district had five participating schools and was rural. The second district, with seven participating schools, was suburban. Study f: Grade 1 one-month alternate form: Participants at two elementary schools near Eugene, Oregon. The first school had a total population of 490 students in a town of around 53,000. The second school had a population of 580 in a town of around 4,700.

*Describe the analysis procedures for each reported type of reliability.

Alternate form reliability: Delayed alternate form reliability was estimated by correlating Daze scores measured at different measurement points across year—beginning-, middle-, and end of year. The median of correlation coefficients between the three benchmark assessments is reported. To assess two-week alternate form reliability, students were administered alternate Daze form two weeks after the middle-of-year benchmark assessment. Two-week alternate form reliability was calculated as correlation between the scores from the scores from these two forms. Inter-rater reliability: Using shadow scoring, student responses to the measure were scored by two examiners. Inter-rater reliability was estimated as correlation between the scores from two examiners.

*In the table(s) below, report the results of the reliability analyses described above (e.g., internal consistency or inter-rater reliability coefficients).

Type of	Subgroup	Informant	Age / Grade	Test or Criterion	n	Median Coefficient	95% Confidence Interval Lower Bound	95% Confidence Interval Upper Bound

Results from other forms of reliability analysis not compatible with above table format:

Manual cites other published reliability studies:

Yes

Provide citations for additional published studies.

Good, R. H., & Jefferson, G. (1998). Contemporary perspectives on Curriculum-Based Measurement validity. In M. R. Shinn (Ed.), Advanced applications of Curriculum-Based Measurement (pp. 61-88). New York: Guilford. Tindal, G., Marston, D., & Deno, S. L. (1983). The reliability of direct and repeated measurement (Research Rep. 109). Minneapolis, MN: University of Minnesota Institute for Research on Learning Disabilities

Do you have reliability data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?

No

If yes, fill in data for each subgroup with disaggregated reliability data.

Type of	Subgroup	Informant	Age / Grade	Test or Criterion	n	Median Coefficient	95% Confidence Interval Lower Bound	95% Confidence Interval Upper Bound

Results from other forms of reliability analysis not compatible with above table format:

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

Validity

Grade	Kindergarten	Grade 1	Grade 2
Rating

*Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.

easyCBM Passsage Reading Fluency (PRF) is an individually administered measure of fluency with connected text. The median of alternate form reliability ranges from .96 to .92, and the median of test-retest reliability with alternate forms ranges from .97 to .91. easyCBM Word Reading Fluency (WRF) is an individually administered screening measure of the fluency with which students read individual words. The median alternate form reliability is .95, and test-retest reliability ranges from .92 to .95. Predictive validity with the SAT-10 is .82 (kindergarten), .65 (Grade 1), and .31 (Grade 2). Stanford Achievement Test—10th Edition. The SAT-10 is a group-administered, norm-referenced test of overall reading proficiency (SAT10; Harcourt Assessment, 2004, 2007 Normative Update). The SAT-10 Reading subtests were administered at the end of the year and assess the essential reading skills including phonemic awareness, decoding, phonics, vocabulary, and comprehension. The measure is not timed, although guidelines with flexible time recommendations are given. The SAT-10 was primarily developed to measure student reading achievement in kindergarten through grade 12. The SAT-10 Reading test serves as an appropriate criterion measure for validity analysis of DIBELS Daze measure because it has been widely used across states as an established measure of reading. In particular, the SAT-10 is external to DIBELS progress monitoring system, and was developed based on a nationally representative norming sample, which supports the generalizability of the scores. An alpha reliability coefficient for total SAT-10 reading scores was .87. Validity coefficient with the Otis-Lennon School Ability Test ranged r = .61–.75. The SAT-10 Reading test is also aligned with International Reading Association (IRA)/National Council of Teachers of English (NCTE) standards, state standards, and the National Assessment of Education Progress (NAEP). TOWRE Phonetic Decoding Efficiency (PDE) is a measure of non-word reading (Torgessen et al., 1999). The total number of words spoken correctly within 45 seconds constitutes a student’s final score for Phonetic Decoding Efficiency. Concurrent validity with the WRMT-R word attack subtest is .89. Alternate-form reliability for PDE is .97, and test-retest reliability is .90 (Torgessen et al., 1999). Note that because nonsense word reading is a transitory and rapidly developing skill, validity correlations with a general outcome measure, such as the SAT-10, at the end of the year are expected to be somewhat weaker than for skills that develop more evenly over time. However, they are still expected to be strong relative to Cohen’s rule of thumb for interpreting correlations (i.e., over .50).

*Describe the sample(s), including size and characteristics, for each validity analysis conducted.

Kindergarten concurrent validity: The sample included 1,511 kindergarten students from one school district in a northwest state. The sample was 48% male, 50% White, 21% American Indian/Alaskan Native, 7% Asian, 2% African American, 2% Hawaiian/Pacific Islanders, 35% of Hispanic, 27% LEP, and 8% eligible for special education. Kindergarten predictive validity: The sample included 218 kindergarten students from a large, rural primary school in northern Georgia. The demographic data were available for 159, of whom 66% were boys, 62% Caucasian, 30% African American, 2% Hispanic, 1% Asian, and 6% mixed ethnicities. 43% of the participants for whom demographic data were available were eligible for free or reduced lunch. Grade 1 concurrent validity: The sample included 213 first-grade students attending a public primary school in a semirural area in northeast Georgia. Of the sample in the study, 51% were males, 53% Caucasian, 24% African American, 6% Hispanic, 4% multiracial, 1% Asian, and 4% missing. Thirty-three percent of the sample were eligible for free or reduced lunch. Grade 1 predictive validity: The sample included 1592 first grade students from a school district. Of the sample, 50% were males, 51% white, 22% American Indian/Alaskan Native, 7% Asian, 2% African American, and 1% Hawaiian/Pacific Islanders. The sample had 33% of Hispanic ethnicity. 24% of the students in the sample had LEP status, and 9% of the students were eligible for special education. Grade 2 concurrent and predictive validity: The sample included 1,468 second grade students from a school district in a northwest state. Of the sample, 48% were males, 52% white, 20% American Indian/Alaskan Native, 8% Asian, 2% African American, and 1% Hawaiian/Pacific Islanders. The sample had 32% of Hispanic ethnicity. 21% of the students in the sample had LEP status, and 10% of the students were eligible for special education.

*Describe the analysis procedures for each reported type of validity.

Concurrent validity: Concurrent validity was evaluated by examining the strength of correlation between the screening measure and the criterion measures administered at approximately the same time of the year. Predictive validity: Predictive validity was evaluated by examining the strength of correlation between the screening measure and the student future performance on the criterion measures.

*In the table below, report the results of the validity analyses described above (e.g., concurrent or predictive validity, evidence based on response processes, evidence based on internal structure, evidence based on relations to other variables, and/or evidence based on consequences of testing), and the criterion measures.

Type of	Subgroup	Informant	Age / Grade	Test or Criterion	n	Median Coefficient	95% Confidence Interval Lower Bound	95% Confidence Interval Upper Bound

Results from other forms of validity analysis not compatible with above table format:

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

Chard, D. J., Stoolmiller, M., Harn, B. A., Wanzek, J., Vaughn, S., Linan-Thompson, S. & Kame’enui, E. J. (2008) Predicting reading success in a multilevel schoolwide reading model: A retrospective analysis. Journal of Learning Disabilities, 41(2), 174-188. Cummings, K. D., Dewey, E. N. Latimer, R. J., & Good, R. H. (2011). Pathways to word reading and decoding: The roles of automaticity and accuracy, School Psychology Review, 40(2), 284-295. Fien, H., Baker, S. K., Smolkowski, K., Smith, J. L. M., Kame'enui, E. J., & Thomas Beck, C. (2008). Using nonsense word fluency to predict reading proficiency in K-2 for English learners and native English speakers. School Psychology Review, 37, 391–408. Fien, H., Park, Y., Baker, S. K., Smith, J. L. M., Stoolmiller, M., & Kame'enui, E. J. (2010). An examination of the relation of nonsense word fluency initial status and gains to reading outcomes for beginning readers. School Psychology Review, 39, 631–653. Harn, B. A., Stoolmiller, M., & Chard, D. J. (2008). Measuring the dimensions of alphabetic principle on the reading development of first graders: The role of automaticity and unitization. Journal of Learning Disabilities, 41(2), 143-157. Munger, K. A. & Blachman, B. A. (2013). Taking a "simple view" of the Dynamic Indicators of Basic Early Literacy Skills as a predictor of multiple measures of third-grade reading comprehension, Psychology in the Schools, 50(7), 722-737. Vanderwood, Linklater, & Healy (2008). Predictive accuracy of Nonsense Word Fluency for English Language Learners. School Psychology Review, 37(1).

Describe the degree to which the provided data support the validity of the tool.

Overall, the validity of DIBELS 6th NWF CLS measure is well supported by criterion measures. From Kindergarten to second grade, DIBELS NWF CLS scores are moderately to strongly correlated with the easyCBM WRF, easyCBM PRF, SAT-10 Total Reading, and SAT-10 Sounds and Letters, TOWRE – SWE, and TOWRE – PDE, with validity coefficients ranging from r = .65 – .89

Do you have validity data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?

No

If yes, fill in data for each subgroup with disaggregated validity data.

Type of	Subgroup	Informant	Age / Grade	Test or Criterion	n	Median Coefficient	95% Confidence Interval Lower Bound	95% Confidence Interval Upper Bound

Results from other forms of validity analysis not compatible with above table format:

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

Bias Analysis

Grade	Kindergarten	Grade 1	Grade 2
Rating	No	No	No

Have you conducted additional analyses related to the extent to which your tool is or is not biased against subgroups (e.g., race/ethnicity, gender, socioeconomic status, students with disabilities, English language learners)? Examples might include Differential Item Functioning (DIF) or invariance testing in multiple-group confirmatory factor models.

No

If yes,

a. Describe the method used to determine the presence or absence of bias:

b. Describe the subgroups for which bias analyses were conducted:

c. Describe the results of the bias analyses conducted, including data and interpretative statements. Include magnitude of effect (if available) if bias has been identified.