DIBELS 6th Edition

Phoneme Segmentation 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 PSF are:

  • Assistive technology (e.g., hearing aids, assistive listening devices)

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 Phoneme Segmentation Fluency (PSF) is a standardized, individually administered test of phonological awareness. The PSF measure assesses a student’s ability to segment three- and four-phoneme words into their individual phonemes fluently. The PSF measure has been found to be a good predictor of later reading achievement (Kaminski & Good, 1996). The PSF task is administered by the examiner reading aloud words of three to five phonemes. Then, the student is asked to say the individual phonemes for each word. For example, the examiner says, “sat,” and the student says, “/s/ /a/ /t/” to receive three possible points for the word. After the student responds, the examiner presents the next word, and the number of correct phonemes produced in one minute determines the final score. The PSF measure takes about 2 minutes to administer and has over 20 alternate forms 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
  • Error analysis

 

Classification Accuracy

GradeK
Criterion 1 Falldash
Criterion 1 WinterEmpty bubble
Criterion 1 Springdash
Criterion 2 Falldash
Criterion 2 Winterdash
Criterion 2 Springdash

Primary Sample

 

Criterion 1, Winter

Grade

K

Criterion

SAT-10

Cut points: Percentile rank on criterion measure

20th percentile

Cut points: Performance score (numeric) on criterion measure

28 correct sound segment

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

Not Provided

Base rate in the sample for children requiring intensive intervention

0.44

False Positive Rate

0.40

False Negative Rate

0.19

Sensitivity

0.81

Specificity

0.60

Positive Predictive Power

0.61

Negative Predictive Power

0.80

Overall Classification Rate

0.69

Area Under the Curve (AUC)

0.79

AUC 95% Confidence Interval Lower Bound

0.78

AUC 95% Confidence Interval Upper Bound

0.80

 

Reliability

GradeK
RatingEmpty bubble
  1. Justification for each type of reliability reported, given the type and purpose of the tool: We evaluated alternate form reliability to assess the reliability of DIBELS 6th Edition PSF subtest.

Alternate form reliability: Alternate-form reliability indicates the extent to which test results generalize to different item samples. Students are tested with two different (i.e., alternate) but equivalent forms of the test within some relatively short interval of time, and scores from these two 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.

 

 

  1. Description of the sample(s), including size and characteristics, for each reliability analysis conducted: Study a: 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.

 

 

  1. Description of the analysis procedures for each reported type of reliability: Study a: Alternate form reliability: All measures were administered in early March of the school year, and three alternate form probes were administered for DIBELS PSF. The maximum amount of time that elapsed between administrations was 3 school days.

 

  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

86

0.97

0.96

0.98

One-month alternate form

K

63

0.74

0.60

0.80

 

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

GradeK
RatingHalf-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 Score (LSS) 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.

The TerraNova, second edition (CTB/McGraw-Hill, 1997) is a group-administered achievement test. The measure was nationally standardized on a stratified sample of 114,312 students (Grades 1-12) from 778 school districts during the fall of 1999 and another 149,798 students (Grades K-12) in the spring of 2000. Stratification variables included geographic region, urbanicity, socioeconomic status, and special needs. The TerraNova demonstrates acceptable internal consistency, with Kuder-Richardson Formula 20 coefficients for all subtests and total scores ranging from the middle .80s to .90s.

Note that because phoneme segmenting 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 consistently over time. However, they are still expected to be strong relative to Cohen’s rule of thumb for interpreting correlations (i.e., over .50).

 

2.Description of the sample(s), including size and characteristics, for each validity analysis conducted: Concurrent validity: The sample included 1,511 kindergarteners from a school district. 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.

Predictive validity: The study included a stratified, random sample of 330 kindergarten children, of whom 49% were males, with an average age of 66 months (SD = 3.8). In the sample, 55% were African American, 17% Caucasian, 17% Hispanic, 9% Asian, and 2% other. Thirty-one percent of these children qualified for free or reduced lunch.

 

3.Description of the analysis procedures for each reported type of validity: Concurrent validity: Correlations were examined for the strength of the associations between the predictor, (i.e., DIBELS PSF administered in winter of kindergarten), with the criterion measure, (i.e., easyCBM Letter Sounds Score administered in winter of kindergarten).

Predictive validity: Correlations were examined for the strength of the associations between the predictor, (i.e., kindergarten DIBELS PSF), with the criterion measure, (i.e., easyCBM Letter Sounds Score as first grade outcome).

 

4.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

easyCBM Letter Sound Fluency

187

0.74

0.67

0.80

Concurrent

K

easyCBM Phoneme Segmenting Fluency

187

0.73

0.66

0.79

Predictive

K

Spring 1st grade Woodcock Johnson Total Reading

37

0.60

0.34

0.76

 

 

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

 

6.Describe the degree to which the provided data support the validity of the tool: Overall, the validity of DIBELS 6th PSF measure is well supported by criterion measures. In kindergarten, DIBELS 6th PSF scores are moderately to strongly correlated with the easyCBM Letter Sounds Fluency, easyCBM Phoneme Segmentation Fluency, and Woodcock Johnson Total Reading, with validity coefficients ranging from r = .60 – .74.       

 

 

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: Hintze, J. M., Ryan, A. L., & Stoner, G. (2003). Concurrent validity and diagnostic accuracy of the Dynamic Indicators of Basic Early Literacy Skills and the Comprehensive Test of Phonological Processing. School Psychology Review, 32, 541-556.

Rouse, H. R., & 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, 341-355. Burke, M. D., Hagan-Burke, S., Kwok, O., & Parker, R. (2009). Predictive validity of early literacy indicators from the middle of kindergarten to second grade. The Journal of Special Education, 42, 209-226.

Burke, M. D., Crowder, W., Hagan-Burke, S., & Zou, Y. (2009). A comparison of two path models for predicting reading fluency. Remedial and Special Education, 30, 84-95. 

Sample Representativeness

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

     

    Grade

    K

    Criterion

    SAT-10 (20th percentile)

    National/Local Representation

    Pacific

    Date

    2003-06

    Sample Size

    5634

    Male

    51%

    Female

    49%

    Gender Unknown

    0%

    Free or Reduced-price Lunch Eligible

    69%

    White, Non-Hispanic

    57%

    Black, Non-Hispanic

    11%

    Hispanic

    22%

    American Indian/Alaska Native

    5%

    Other

    <1%

    Race/Ethnicity Unknown

    <1%

    Disability Classification

    7% eligible

    First Language

    English

    Language Proficiency Status

    26% English learners

     

    Bias Analysis Conducted

    GradeK
    RatingNo
    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

    GradeK
    Data
  • Individual
  • Administration & Scoring Time

    GradeK
    Data
  • 3 minutes
  • Scoring Format

    GradeK
    Data
  • Manual
  • Automatic
  • Types of Decision Rules

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

    GradeK
    Data
  • Yes