DIBELS 6th Edition

Letter Naming Fluency

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 LNF 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 6th Edition Letter Naming Fluency (LNF) is a standardized, individually administered measure of a student’s accuracy and fluency with naming a series of upper- and lower-case letters of the alphabet. The measure is designed as an indicator of later reading risk for students in kindergarten and first grade. The measure is timed for one minute. Letters omitted, substituted, and hesitations of more than three seconds are scored as errors. Letters self-corrected within three seconds are scored as accurate. The number of correct letters named in 1-minute is the letter naming fluency rate.

 

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

GradeK1
Criterion 1 FallEmpty bubbleEmpty bubble
Criterion 1 WinterEmpty bubbledash
Criterion 1 Springdashdash
Criterion 2 Falldashdash
Criterion 2 Winterdashdash
Criterion 2 Springdashdash

Primary Sample

 

Criterion 1, Fall

Grade

K

1

Criterion

SAT-10

SAT-10

Cut points: Percentile rank on criterion measure

20th percentile

20th percentile

Cut points: Performance score (numeric) on criterion measure

6 correct letters

33 correct letters

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

Not Provided

Not Provided

Base rate in the sample for children requiring intensive intervention

0.43

0.35

False Positive Rate

0.38

0.35

False Negative Rate

0.19

0.18

Sensitivity

0.81

0.82

Specificity

0.62

0.65

Positive Predictive Power

0.62

0.56

Negative Predictive Power

0.81

0.87

Overall Classification Rate

0.70

0.71

Area Under the Curve (AUC)

0.77

0.82

AUC 95% Confidence Interval Lower Bound

0.76

0.81

AUC 95% Confidence Interval Upper Bound

0.78

0.83

 

Criterion 1, Winter

Grade

K

1

Criterion

SAT-10

NA

Cut points: Percentile rank on criterion measure

20th percentile

NA

Cut points: Performance score (numeric) on criterion measure

27 correct letters

NA

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

Not Provided

NA

Base rate in the sample for children requiring intensive intervention

0.44

NA

False Positive Rate

0.29

NA

False Negative Rate

0.19

NA

Sensitivity

0.81

NA

Specificity

0.71

NA

Positive Predictive Power

0.69

NA

Negative Predictive Power

0.82

NA

Overall Classification Rate

0.75

NA

Area Under the Curve (AUC)

0.84

NA

AUC 95% Confidence Interval Lower Bound

0.83

NA

AUC 95% Confidence Interval Upper Bound

0.85

NA

 

Reliability

GradeK1
RatingFull bubbleEmpty bubble
  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 LNF 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 preventing 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 the (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: 1- week test-retest reliability: The data were collected on a total of 633 students. Of the sample, about 51% female, 75% white, 14% Black, and 7% Hispanic, with 4% Asian or Native American. About 29% were eligible for free or reduced lunch; 20% Title 1 students; and 6% were in special education programs. There were 4 English as a second language/limited English proficiency (ESL/LEP) students, 10 gifted/talented students, and 1 disabled student.

Study b: Alternate form reliability: Participants included 86 kindergarten students from a midsized city in Northwestern Massachusetts. Of the total sample, 93% were Caucasian, 2% African American, 2% Hispanic, and 2% Asian and consisted of 44 girls and 42 boys.

Study c: Alternate form reliability: Participants were from kindergarten, first, second, and third grade classrooms in two elementary schools in separate school districts in Lane County, Oregon. The sample from School 1 consisted of 88% of white, non-Hispanic, 7% of Hispanic, 3% of Asian/Pacific Islander, 1% of Black, non-Hispanic, and 1% of Native American. Of the School 1 sample, 41% were eligible for free and reduced lunch. The sample from School 2 consisted of 94% of white, non-Hispanic, 4% of Hispanic, 1% of Asian/Pacific Islander, 1% of Black, non-Hispanic, and less than 1% of Native American. Of the School 2 sample, 42% were eligible for free and reduced lunch.

 

  1. Description of the analysis procedures for each reported type of reliability: Test-retest reliability: Students were re-administered the same test in the three weeks following the end-of-year benchmark assessment. Test-retest reliability was estimated as the correlation coefficient between the test and retest.

Alternate form reliability: Students were administered three different forms for the middle of year ORF test. Alternate-form reliability of a single form was estimated by the correlation between the score recorded on the other forms. The median of correlation coefficients between three forms is reported. Delayed alternate form reliability was estimated by correlating ORF 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.

Internal consistency: The reliability of the ORF fall to spring gain score, a confirmatory factor analysis (CFA) measurement model that included the three fall ORF passage scores to define latent fall ORF ability and the three spring ORF passages to define latent spring ORF ability to estimate the reliability was used. The covariance between the two fall median scores is an estimate of the fall true score variance, the covariance between the two spring median scores is an estimate of the spring true score variance and the four covariances between the two fall median scores and two spring median scores are each an estimate of the covariance between fall and spring true scores. The average of the four covariances as the best single estimate of the fall-spring true score covariance. The true gain score variance was computed as fall true score variance plus spring true score variance minus two times the covariance of fall and spring true scores. For the observed gain score variance, the observed fall and spring variances in the same formula in place of the true score variances were used. Reliability coefficient was computed as the ratio of the true gain score variance to the observed gain score variance.

 

  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

1-week Test-retest

Kindergarten

633

0.86

0.84

0.88

Alternate Form

Kindergarten

86

0.94

0.91

0.96

1-month alternate form

Kindergarten

71

0.89

0.82

0.91

1-month alternate form

First Grade

80

0.86

0.79

0.89

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

GradeK1
RatingFull 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 Letter Sounds is a individually administered screening measure to be used for establishing benchmarks and monitoring progress. It takes 1 minute to administer. The median of alternate form reliability is .85, and the median of test-retest reliability is .66. The measure’s predictive validity with SAT-10 is .68, and the concurrent validity with SAT-10 is .72.

TOWRE sight word efficiency (SWE) is a measure of accuracy and fluency in reading phonetically regular and irregular words from the TOWRE (Torgesen et al., 1999). The number of words spoken correctly within 45 seconds is counted, and this constitutes the final score for sight word efficiency. This subtest’s concurrent validity with the WRMT-R Word Identification subtest is .92. Alternate form reliability for the Sight Word Efficiency subtest is .97 and test-retest reliability is .96 (Torgesen et al., 1999).

Stanford Achievement Test-10 (SAT-10) Reading Comprehension is a published norm-referenced test designed to assess reading comprehension. Students are required to read text passages and then answer questions.

Note that because letter naming is a very specific 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 kindergarteners from a school district in a northwest state. Of the sample, 48% were males, 50% white, 21% American Indian/Alaskan Native, 7% Asian, 2% African American, and 2% Hawaiian/Pacific Islanders. The sample had 35% of Hispanic ethnicity. 27% of the students in the sample had LEP status, and 8% of the students were eligible for special education.

Kindergarten predictive validity: The sample included 218 kindergarteners 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 eligible for free or reduced lunch.

Grade 1 concurrent validity: The sample included 1,592 first grade students from a school district in a northwest state. 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 1 predictive validity: The sample in the study consisted of 27,813 first grade students from 321 schools in Florida. Only students with complete data on both outcome measures (ORF and SAT-10) were included in the study.

 

  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

Predictive

Kindergarten

SAT-10 Total Reading Scaled Score

171

0.78

0.71

0.83

Predictive

Kindergarten

SAT-10 Total Reading Scaled Score

162

0.73

0.65

0.79

Predictive

Kindergarten

TOWRE SWE

218

0.72

0.65

0.78

Predictive

Kindergarten

Spring of First Grade CBM-R

50

0.72

0.55

0.82

Predictive

Kindergarten

easyCBM Letter Sounds Score

180

0.71

0.63

0.78

Concurrent

Kindergarten

easyCBM Letter Sounds Score

257

0.68

0.61

0.74

Predictive

Kindergarten

First Grade DRA Instructional Reading Level

330

0.67

0.61

0.73

Concurrent

First

easyCBM Letter Sounds Score

227

0.68

0.60

0.74

Predictive

First

SAT-10

27,813

0.55

0.54

0.56

 

 

  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 LNF measure is well supported by criterion measures. From kindergarten to first grade, DIBELS 6th LNF measure scores are moderately to strongly correlated with the easyCBM Letter Sounds, TOWRE–SWE, SAT-10 Total Reading, First Grade DRA Instructional Reading Level, and First Grade CBM–R, with validity coefficients ranging from r = .55 – .78.

 

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. Cummings, K. D., Kaminski, R. A., Good, R. H. & O’Neil, M. (2011). Assessing phonemic awareness in preschool and kindergarten: Development and initial validation of First Sound Fluency. Assessment for Effective Intervention, 36(2) 94–106

Goffreda, C. T., DiPerna, J. C., & Pedersen, J. A. (2009). Preventive screening for early readers: Predictive validity of the Dynamic Indicators of Basic Early Literacy Skills (DIBELS). Psychology in the Schools, 46(6), 539-552.

Kaminski, R. A., & Good, R. H., III. (1996). Toward a technology for assessing basic early literacy skills. School Psychology Review, 25(2), 215-227.

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.

 

Sample Representativeness

GradeK1
Data
  • Local without Cross-Validation
  • Local without Cross-Validation
  • Primary Classification Accuracy Sample

     

    Grade

    K

    1

    Criterion

    SAT-10 (20th percentile)

    SAT-10 (20th percentile)

    National/Local Representation

    Oregon

    Oregon

    Date

    2003-06

    2003-06

    Sample Size

    5,634

    4,953

    Male

    51%

    51%

    Female

    49%

    49%

    Gender Unknown

    0%

    0%

    Free or Reduced-price Lunch Eligible

    69%

    69%

    White, Non-Hispanic

    57%

    57%

    Black, Non-Hispanic

    11%

    11%

    Hispanic

    22%

    22%

    American Indian/Alaska Native

    5%

    5%

    Other

    <1%

    <1%

    Race/Ethnicity Unknown

    <1%

    <1%

    Disability Classification

    67% eligible

    67% eligible

    First Language

    English

    English

    Language Proficiency Status

    26% English learners

    26% English learners

     

    Bias Analysis Conducted

    GradeK1
    RatingNoNo
    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

    GradeK1
    Data
  • Individual
  • Individual
  • Administration & Scoring Time

    GradeK1
    Data
  • 3 minutes
  • 3 minutes
  • Scoring Format

    GradeK1
    Data
  • Manual
  • Automatic
  • Manual
  • Automatic
  • Types of Decision Rules

    GradeK1
    Data
  • Benchmark Goals
  • Benchmark Goals
  • Evidence Available for Multiple Decision Rules

    GradeK1
    Data
  • Yes
  • Yes