DIBELS 6th Edition

Nonsense Word Fluency - Correct Letter Sounds

Cost

Technology, Human Resources, and Accommodations for Special Needs

Service and Support

Purpose and Other Implementation Information

Usage and Reporting

Initial Cost:

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.

 

Replacement Cost:

For users of the DDS, the replacement cost is $1 per student per year.

 

Annual license renewal fee subject to change.

 

Included in Cost:

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).

Technology Requirements:

·  Computer or tablet*

·  Internet connection*

*An internet-connected device is required to download the materials. Administering the measure itself does not require technology, unless administrators are using the optional DDS platform.

 

Training Requirements:

·  1-4 hours of training

 

Qualified Administrators:

·  Paraprofessionals

·  Professionals

 

Accommodations:

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 like any other 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

Where to Obtain:

Website: https://dibels.uoregon.edu

Address: 5292 University of Oregon, Eugene, OR 97403

Phone number: 1-888-497-4290

Email: support@dibels.uoregon.edu

 

Access to Technical Support:

Technical support is available from the DIBELS Data System team at the University of Oregon, who can be reached online (https://dibels.uoregon.edu), by phone (1-888-497-4290), or by email (support@dibels.uoregon.edu). Hours of Operation: 6:00am - 5:30pm PT, Monday through Friday.
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.

 

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.
Assessment Format:

·  One-to-one

 

Administration Time:

·  2 minutes per student

 

Scoring Time:

·  1 minute per student*

*If using tablet-based administration with the HiFi Reading app, scoring is automatic.

 

Scoring Method:

·  Calculated manually*

*If using tablet-based administration with the HiFi Reading app, scoring is automatic.

 

Scores Generated:

·  Raw score

·  Percentile score

Developmental benchmarks 

 

Classification Accuracy

GradeK12
Criterion 1 FalldashEmpty bubbleEmpty bubble
Criterion 1 WinterEmpty bubbleEmpty bubbledash
Criterion 1 Springdashdashdash
Criterion 2 Falldashdashdash
Criterion 2 Winterdashdashdash
Criterion 2 Springdashdashdash

Primary Sample

 

Criterion 1, Fall

Grade

K

1

2

Criterion

Not Provided

SAT-10

SAT-10

Cut points: Percentile rank on criterion measure

Not Provided

20th percentile

20th percentile

Cut points: Performance score (numeric) on criterion measure

Not Provided

19 correct letters

52 correct letters

Cut points: Corresponding performance score (numeric) on screener measure

Not Provided

Not Provided

Not Provided

Base rate in the sample for children requiring intensive intervention

Not Provided

0.35

0.34

False Positive Rate

Not Provided

0.29

0.35

False Negative Rate

Not Provided

0.20

0.19

Sensitivity

Not Provided

0.80

0.81

Specificity

Not Provided

0.71

0.65

Positive Predictive Power

Not Provided

0.60

0.54

Negative Predictive Power

Not Provided

0.87

0.87

Overall Classification Rate

Not Provided

0.75

0.70

Area Under the Curve (AUC)

Not Provided

0.84

0.82

AUC 95% Confidence Interval Lower Bound

Not Provided

0.83

0.81

AUC 95% Confidence Interval Upper Bound

Not Provided

0.85

0.83

 

Criterion 1, Winter

Grade

K

1

2

Criterion

SAT-10

SAT-10

Not Provided

Cut points: Percentile rank on criterion measure

20th percentile

20th percentile

Not Provided

Cut points: Performance score (numeric) on criterion measure

15 correct letters

48 correct letters

Not Provided

Cut points: Corresponding performance score (numeric) on screener measure

Not Provided

Not Provided

Not Provided

Base rate in the sample for children requiring intensive intervention

0.44

0.36

Not Provided

False Positive Rate

0.28

0.31

Not Provided

False Negative Rate

0.18

0.19

Not Provided

Sensitivity

0.82

0.81

Not Provided

Specificity

0.72

0.69

Not Provided

Positive Predictive Power

0.69

0.60

Not Provided

Negative Predictive Power

0.83

0.87

Not Provided

Overall Classification Rate

0.76

0.74

Not Provided

Area Under the Curve (AUC)

0.85

0.87

Not Provided

AUC 95% Confidence Interval Lower Bound

0.84

0.86

Not Provided

AUC 95% Confidence Interval Upper Bound

0.86

0.88

Not Provided

 

Reliability

GradeK12
RatingEmpty bubbleFull bubbledash
  1. 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.

 

  1. Description of 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.

 

  1. Description of 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.

 

  1. Reliability of performance level score (e.g., model-based, internal consistency, inter-rater reliability).

Type of Reliability

Age or Grade

n

Coefficient

95% Confidence Interval: Lower Bound

95% Confidence Interval: Upper Bound

Alternate form

K

40

0.94

0.89

0.97

Three-week alternate form

K

91

0.86

0.80

0.91

Delayed alternate form

K

1428

0.73

0.71

0.75

Test-retest

1

938

0.94

0.93

0.95

Test-retest

1

3506

0.87

0.86

0.88

One-month alternate form

1

77

0.83

0.75

0.87

Delayed alternate form

1

1,567

0.76

0.74

0.78

Delayed alternate form

1

1546

0.73

0.71

0.75

Disaggregated Reliability

The following disaggregated reliability data are provided for context and did not factor into the Reliability rating.

Type of Reliability

Subgroup

Age or Grade

n

Coefficient

95% Confidence Interval: Lower Bound

95% Confidence Interval: Upper Bound

None

 

 

 

 

 

 

 

Validity

GradeK12
RatingFull bubbleFull bubbleHalf-filled bubble
  1. Description of each criterion measure used and explanation as to 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).

 

  1. Description of 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.

 

  1. Description of 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.

 

  1. Validity for the performance level score (e.g., concurrent, predictive, 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 Validity

Age or Grade

Test or Criterion

n

Coefficient

95% Confidence Interval: Lower Bound

95% Confidence Interval: Upper Bound

Concurrent

K

SAT-10 Total Reading

171

0.78

0.71

0.83

Predictive

K

SAT-10 Sounds and Letters

178

0.73

0.65

0.79

Concurrent

K

easyCBM WRF

227

0.85

0.81

0.88

Predictive

K

easyCBM WRF

188

0.81

0.76

0.85

Concurrent

K

TOWRE - PDE

213

0.75

0.69

0.80

Concurrent

1

easyCBM WRF

196

0.74

0.67

0.80

Predictive

1

easyCBM - PRF

259

0.73

0.67

0.78

Concurrent

1

easyCBM - WRF

259

0.69

0.62

0.75

Concurrent

1

TOWRE - SWE

213

0.68

0.60

0.75

Concurrent

2

easyCBM WRF

213

0.67

0.59

0.74

Concurrent

2

easyCBM - PRF

213

0.66

0.58

0.73

Concurrent

1

SAT-10 Total Reading

175

0.65

0.56

0.73

Predictive

2

SAT-10 Total Reading

171

0.78

0.71

0.83

Predictive

2

SAT-10 Sounds and Letters

178

0.73

0.65

0.79

Predictive

1

easyCBM WRF

227

0.85

0.81

0.88

 

  1. Results for other forms of validity (e.g. factor analysis) not conducive to the table format: Not Provided.

 

  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.

 

Disaggregated Validity

The following disaggregated validity data are provided for context and did not factor into the Validity rating.

Type of Validity

Subgroup

Age or Grade

Test or Criterion

n

Coefficient

95% Confidence Interval: Lower Bound

95% Confidence Interval: Upper Bound

None

 

 

 

 

 

 

 

 

Results for other forms of disaggregated validity (e.g. factor analysis) not conducive to the table format: Not Provided  

 

If your manual cites other published validity studies, provide these citations: 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).

Sample Representativeness

GradeK12
Data
  • Local without Cross-Validation
  • Local without Cross-Validation
  • Local without Cross-Validation
  • Primary Classification Accuracy Sample

     

    Grade

    K

    1

    2

    Criterion

    SAT-10 (20th percentile)

    SAT-10 (20th percentile)

    Not Provided

    National/Local Representation

    Pacific/Oregon

    Pacific/Oregon

    Not Provided

    Date

    2003-06

    2003-06

    Not Provided

    Sample Size

    5634

    4953

    Not Provided

    Male

    51%

    51%

    Not Provided

    Female

    49%

    49%

    Not Provided

    Gender Unknown

    0%

    0%

    Not Provided

    Free or Reduced-price Lunch Eligible

    69%

    69%

    Not Provided

    White, Non-Hispanic

    57%

    57%

    Not Provided

    Black, Non-Hispanic

    11%

    11%

    Not Provided

    Hispanic

    22%

    22%

    Not Provided

    American Indian/Alaska Native

    5%

    5%

    Not Provided

    Other

    <1%

    <1%

    Not Provided

    Race/Ethnicity Unknown

    <1%

    <1%

    Not Provided

    Disability Classification

    67% eligible

    67% eligible

    Not Provided

    First Language

    English

    English

    Not Provided

    Language Proficiency Status

    26% English learners

    26% English learners

    Not Provided

     

    Bias Analysis Conducted

    GradeK12
    RatingNoNoNo
    1. Description of the method used to determine the presence or absence of bias: Not Provided  

     

    1. Description of the subgroups for which bias analyses were conducted: Not Provided  

     

    1. Description of the results of the bias analyses conducted, including data and interpretative statements: Not Provided

    Administration Format

    GradeK12
    Data
  • Individual
  • Individual
  • Individual
  • Administration & Scoring Time

    GradeK12
    Data
  • 3 minutes
  • 3 minutes
  • 3 minutes
  • Scoring Format

    GradeK12
    Data
  • Manual
  • Automatic
  • Manual
  • Automatic
  • Manual
  • Automatic
  • Types of Decision Rules

    GradeK12
    Data
  • Benchmark Goals
  • Benchmark Goals
  • Benchmark Goals
  • Evidence Available for Multiple Decision Rules

    GradeK12
    Data
  • Yes
  • Yes
  • Yes