DIBELS 6th Edition

Oral Reading Fluency

Cost Technology, Human Resources, and Accommodations for Special Needs Service and Support Purpose and Other Implementation Information Usage and Reporting

Cost per student for Year 1: $0.00

Online Costs:

$ 1.00 Per-student per year (for online data entry, management, and reporting)

The DIBELS 6th Edition materials can be downloaded, free of charge, at: https://dibels.uoregon.edu. The materials consist of the manuals and test materials, directions for administration, test forms, technical manuals, and student protocols.

Use of the DIBELS Data System for the purpose of entering and managing data, as well as generating project, district, school, class, or student reports costs $1.00 per student per year.

Testers will require 1-4 hours of training. The examiners must at a minimum be a paraprofessional.

Training manuals and materials are available and have been field-tested. On-line traing materials for administration and scoring of 6th edition will be available from https://dibels.uoregon.edu sometime during the 2013-14 school year. The pricing structure for these materials is to be determined.

Ongoing 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).

Accommodations:

A list of DIBELS approved accommodations is available in the Administration and Scoring Guide. 

Where to obtain: University of Oregon DIBELS Data System 

Address: 5292 University of Oregon, Eugene, OR 97403

Phone:  1-888-497-4290

Website: https://dibels.uoregon.edu

The DIBELS Oral Reading Fluency (ORF) is a standardized, individually administered test of accuracy and reading fluency with connected text for students in Grades 1 through 5. It is a standardized set of passages and administration procedures designed to identify children who may need additional instructional support, and monitor progress toward instructional goals.

Student performance is measured by having students read a passage aloud for one minute. Words omitted, substituted, and hesitations of more than three seconds are scored as errors. Words self-corrected within three seconds are scored as accurate. The number of correct words per minute from the passages is the oral reading fluency rate.

The tool provides information on student performance in English. 

The administration of the test takes 2 minutes and should be administered one-on-one to individual students.

There are 26 test forms for Grade 1 (20 are typically used for progress monitoring, the other six are typically used for benchmarking) and 29 for all other grades (each grade has 20 passages that are typically used for progress monitoring and nine passages that are typically used for benchmarking).

The raw score consists of the number of words read minus the number of errors for a total of words read correctly in one minute. There is no cluster/composite score. Raw scores can be converted to percentiles by looking up the equivalent percentile in a tech report (Cummings, Otterstedt, Kennedy, Baker and Kame’enui, 2011). Raw scores can be compared to the criterion- and norm-referenced benchmark scores that are also available from dibels.uoregon.edu.

 

Reliability of the Performance Level Score

Grade12345
RatingFull bubbleFull bubbleFull bubbleFull bubbleFull bubble

Type of Reliability

Age or Grade

n (range)

Coefficient

SEM

Information (including normative data) / Subjects

range

median

3-week test-retest

First

320

NR

0.94

     

Baker et al. (2008). Participants were students at 34 Oregon Reading First Schools across 16 school districts. The study included 17 schools in large urban areas, eight in midsize cities, and nine in rural areas. Approximately 10% of the students received special education services and 32% were English language learners.

3-week test-retest

First

320

NR

0.98

     

3-week test-retest

Second

320

NR

0.97

     

2-week test-retest

First

73

NR

0.97

 

Cummings, Stoolmiller, Baker, Fien, & Kame’enui (under review). Participants were 73 first grade students during the 2008-2009 academic year from a subset of schools participating in the Oregon Reading First program.

2-week test-retest

Third

64

NR

0.93

 

Cummings, Stoolmiller, Baker, Fien, & Kame’enui (under review). Participants were 64 third grade students during the 2007-2008 academic year from a subset of schools participating in the Oregon Reading First program.

3-week test-retest

First and Second

 

0.94 - 0.99

NR

 

Fien et al. (2010). Participants were a random subset of 20% of the students in first and second grade in schools that participated in the federally funded Oregon Reading First Program during the 2006-2007 school year.

Alternate form

Second

134

0.87 - 0.96

0.92

     

Francis et al. (2008). Participants were second grade students in two large urban school districts in Texas. There were 69 female students and 65 male students. The ethnic composition was 31% African–American, 3% Asian, 57% Hispanic, and 9% Caucasian, with 80% economically disadvantaged.

Alternate form (one passage)

First

86

NR

0.89

     

Roberts, Good, & Corcoran (2005). Participants were 86 first grade students in six schools in an urban, southeastern school district. Participating schools served low income, Title I populations.

Alternate form (three passages)

First

86

NR

0.96

     

2-week test-retest

First

     

NR

0.97

     

Stoolmiller, Biancarosa, & Fien (2013). Participants were a random subsample of first grade students from a subset of 4 schools in a school district in Western Oregon during the academic year 2009–2010.

2-week test-retest

Third

 

NR

0.93

 

Stoolmiller, Biancarosa, & Fien (2013). Participants were a random subsample of third grade students from a subset of 4 schools in a school district in Western Oregon during the academic year 2009–2010.

Alternate form

Second

209

0.92 - 0.93

NR

 

Stoolmiller, Biancarosa, & Fien (2013). Participants were 209 second grade students from a subset of 4 schools in a school district in Western Oregon during the academic year 2009–2010.

Inter-passage

First

 

0.94 -0.95

NR

7.47

Unpublished (SEM Range = 6.73 – 8.20)

Inter-passage

Second

 

NR

0.93

9.79

Unpublished (SEM Range = 8.35 – 10.06)

Inter-passage

Third

 

090 - 0.93

0.91

11.19

Unpublished (SEM Range = 8.89 – 11.67)

Inter-passage

Fourth

 

0.84 - 0.92

NR

11.53

Unpublished (SEM Range = 9.62 – 14.47)

Inter-passage

Fifth

 

NR

0.93

10.46

Unpublished (SEM Range = 10.43 – 10.65)

 

Reliability of the Slope

Grade12345
RatingdashEmpty bubbledashdashdash

Type of Reliability

Age or Grade

n (range)

Coefficient Range

Coefficient Median

SEM

Fall-to-spring gain

Second grade

666 students

5,000 simulated

0.765 - 0.907

0.869

7.5

Information (including normative data) / Subjects:

Information reported in the table above is from Cummings, Stoolmiller, Baker, Fien, & Kame’enui (2015). Participants were 666 second-grade students from a subset of nine of 51 schools taking part in Oregon Reading First. Parameters of a confirmatory factor analysis (CFA) measurement model were used to simulate two sets of three fall and three spring passage scores (5,000 replications) to define latent fall and spring ORF ability. Reliability of fall-to-spring gain was calculated as the ratio of the true gain score variance to the observed gain score variance.

In the sample, 10% of students received special education services; 21% were English learners; 50% were female, 47% male, and 3% did not report gender; 43% were White, 30% Hispanic, 14% Black, 10% other non-White ethnic groups, and 4% did not report race/ethnicity.

Validity of the Performance Level Score

Grade12345
RatingFull bubbleFull bubbleFull bubbleFull bubbleFull bubble

Type of Validity

Age or Grade

Test or Criterion

n (range)

Coefficient

Information (including normative data)/Subjects

range

median

Predictive

First

Spring Grade 2 CAT Reading Comprehension Test

167

NR

0.63

Baker & Smith (2001). Participants were students in grades 1 through 3 who were administered both sets of tests over a number of academic years. The number of students represented in the grade 1 correlation for OSA is lower than the other grade and assessment combinations “because only one year of students were administered the fluency measures in the spring of first grade and subsequently the OSA reading test in the spring of grade 3.” (p. 320)

Predictive

First

Spring Grade 3 OSA Reading Test

36

NR

0.63

Concurrent

Second

Spring Grade 2 CAT Reading Comprehension Test

275

NR

0.73

Predictive

Second

Spring Grade 3 OSA Reading Test

194

NR

0.72

Concurrent

Third

Spring Grade 3 OSA Reading Test

172

NR

0.76

Concurrent

First

SAT-10

4973

NR

0.82

Baker et al. (2008)

Concurrent

Second

SAT-10

4826

NR

0.80

Concurrent

Third

SAT-10

4696

NR

0.67

Predictive

First

End of 1st SAT-10

4973

NR

0.72

Predictive

First

End of 2nd SAT-10

2417

0.63 - 0.72

0.68 

Predictive

Second

End of 2nd SAT-10

4826

0.72 - 0.79

0.76

Predictive

Second

End of 3rd SAT-10

2367

0.58 - 0.63

0.63

Predictive

Third

End of 3rd SAT-10

4696

0.65 - 0.68

0.67

Concurrent

Third

NC End of Grade reading test

38

NR

0.73

Barger (2003). Participants were from one school in North Carolina. Twenty-seven of the students scored high enough on the end of grade assessment to be considered at grade level.

Concurrent

Third

FCAT-SSS Reading

1102

NR

0.70

Buck & Torgeson (2003). Participants were at 13 schools in one Florida school district. Only 1% of the students were considered limited English proficient, and 19% were identified as exceptional students under IDEA.

Concurrent

Third

FCAT-NRT Reading

1102

NR

0.74

Concurrent

First

TOWRE - PDE

213

NR

0.77

Burke & Hagan-Burke (2007). Participants were from a public primary school in semirural northeast Georgia and came from middle- to lower-middle-class families.

Concurrent

First

TOWRE - SWE

213

NR

0.92

Concurrent

First

TOWRE - PDE

162

NR

0.81

Burke, Hagan-Burke, Kwok, & Parker (2009). Participants were 218 kindergarteners at a rural primary school in northern Georgia.

Concurrent

First

TOWRE - SWE

162

NR

0.89

Predictive

First

Middle of 2nd WRMT-R (PC)

162

NR

0.61

Concurrent

Second

WRMT-R (PC)

162

NR

0.69

Predictive

First

Third grade WIAT-II Reading Comprehension

35

NR

0.66

Munger & Blachman (2013). Participants were first grade students from a small, urban elementary school located in the Northeastern United States.

Predictive

First

Third grade GRADE Reading Comprehension

35

NR

0.72

Predictive

First

Third grade NYSELA3

35

 NR

0.56

Predictive

First

End of 1st Group Reading Assessment and Diagnostic Evaluation

1027 - 1224

0.59 - 0.67

0.63

Riedel (2007). Participants were students in Memphis who attended one of 26 schools with a Reading Excellence Act grant and participated in REA-related assessments. Students receiving special education services were not included, and data from students classified as English language learners were analyzed separately.

Predictive

First

End 2nd TerraNova

891 - 1054

0.49 - 0.54

0.52

Concurrent

First

Broad Reading Cluster

86

0.72-0.75

0.74

Roberts et al. (2005). Coefficients are for individual passages.

Concurrent

First

Broad Reading Cluster

86

NR

0.76

Predictive

Third

FCAT-SSS

16539 - 16908

0.66 - .71

0.68

Roehrig, Petscher,  Nettles, Hudson, & Torgesen (2008). Participants were students enrolled in Florida Reading First schools. Students were divided into two cohorts for cross-validation purposes. Data for each cohort is reported here separately.

Predictive

Third

SAT-10

16539 - 16908

0.68 - 0.71

0.69

Predictive

First

End of 1st ITBS Reading Total

2588

NR

0.69

Schilling, Carlisle, Scott, & Zeng (2007). Participants were 2,588 first graders, 2,437 second graders, and 2,527 third graders who took the ITBS and a similar number who took DIBELS at each grade level at 49 schools at nine school districts in Michigan. Sixteen percent had limited English proficiency, and 8.5% of students had disabilities.

Concurrent

First

ITBS Read. Total

2588

NR

0.75

Concurrent

First

End 1st ITBS Voc

2588

NR

0.61

Predictive

First

End of 1st ITBS Comprehension

2588

NR

0.69

Concurrent

First

ITBS Comp

2588

NR

0.74

Predictive

First

End of 1st ITBS Word Analysis

2588

NR

0.61

Concurrent

First

ITBS Word Analysis

2588

NR

0.69

Predictive

First

End of 1st ITBS Language

2588

NR

0.63

Concurrent

First

ITBS Language

2588

NR

0.71

Discriminant

First

End of 1st ITBS Listening

2588

0.31 - 0.34

0.33

Predictive

Second

End of 2nd ITBS Reading Total

2437

0.69 - 0.75

0.72

Concurrent

Second

ITBS Read. Total

2437

NR

0.75

Predictive

Second

End 2nd ITBS Voc

2437

0.61 - 0.65

0.63

Concurrent

Second

ITBS Vocabulary

2437

NR

0.75

Predictive

Second

End of 2nd ITBS Comprehension

2437

0.68 - 0.75

0.72

Concurrent

Second

ITBS Comp.

2437

NR

0.75

Predictive

Second

End of 2nd ITBS Word Analysis

2437

0.59 - 0.63

0.61

Concurrent

Second

ITBS Word An.

2437

NR

0.62

Predictive

Second

END of 2nd ITBS Language

2437

0.59 - 0.65

0.62

Concurrent

Second

ITBS Language

2437

NR

0.64

Discriminant

Second

End of 2nd ITBS Listening

2437

0.29 - 0.33

0.33

Predictive

Third

End of 2nd ITBS Reading Total

2527

0.65 - 0.67

0.66

Concurrent

Third

ITBS Read. Total

2527

NR

0.65

Predictive

Third

End of 2nd ITBS Voc

2527

0.57 - 0.58

0.58

Concurrent

Third

ITBS Vocabulary

2527

NR

0.56

Predictive

Third

End of 2nd ITBS Comprehension

2527

0.63 - 0.65

0.64

Concurrent

Third

ITBS Comp.

2527

NR

0.63

Predictive

Third

End of 2nd ITBS Word Analysis

2527

0.63 - 0.65

0.64

Concurrent

Third

ITBS Word An.

2527

NR

0.63

Predictive

Third

End of 2nd ITBS Language

2527

0.67 - 0.69

0.68

Concurrent

Third

ITBS Language

2527

NR

0.68

Discriminant

Third

End of 2nd ITBS Listening

2527

0.36 - 0.37

0.37

Concurrent

Third

4Sight

401

0.67 - 0.71

0.69

Shapiro, Solari, & Petscher (2008). Participants were from six elementary schools in three Pennsylvania districts.

Predictive

Third

Middle of third 4Sight

401

NR

0.66

Predictive

Third

Middle of third PA System of School Assessment

401

NR

0.67

Concurrent

Third

PA System of School Assessment

401

NR

0.68

Concurrent

Fourth

4Sight

394

0.66 - 0.67

0.67

Predictive

Fourth

Middle of 4Sight

394

NR

0.66

Predictive

Fourth

PA System of School Assessment

394

NR

0.64

Concurrent

Fourth

PA System of School Assessment

394

NR

0.68

Concurrent

Fifth

4Sight

205

0.66 - 0.70

0.68

Predictive

Fifth

PA System of School Assessment

205

NR

0.73

Concurrent

Fifth

PA System of School Assessment

205

NR

0.76

Predictive

Third

End of 3rd CO State Assess. Prog. Read.

52

0.73 - 0.80

0.77

Shaw & Shaw (2002). Participants were third-grade students at a Colorado elementary school.

Concurrent

Third

CSAP Reading

52

NR

0.80

Predictive

Third

Beginning of 4th Ohio Proficiency Test

318

NR

0.65

Vandermeer, Lentz, & Stollar (2005). Participants were from three elementary schools in a suburban school district in southwest Ohio. All students were included in this study except those identified with significant cognitive disabilities. Students with an Individualized Education Program were provided allowable accommodations.

Concurrent

Fourth

Ohio Proficiency Test

318

NR

0.65

Concurrent

Third

Arizona Instrument to Measure Standards

241

NR

0.74

Wilson (2005). Participants were 241 third-grade students with both AIMS and ORF scores available from three schools that received a Reading First grant. Of these students, 65 were identified as English language learners.

Predictive

Third

End of Third CSAP

82

NR

0.70

Wood (2006). Participants were in a public elementary school in a middle-class neighborhood in northern Colorado. All available students whose primary language was English were tested. Seven students received special education services at the third-grade level, 10 students received special education services at the fourth-grade level, and nine students received services at the fifth-grade level.

Predictive

Fourth

End of 4th CSAP

101

NR

0.67

Predictive

Fifth

End of 5th CSAP

98

NR

0.75

Concurrent

First

DIBELS RTF

213

NR

0.69

Burke & Hagan-Burke (2007).

Predictive

First

Middle of 2nd ORF

162

NR

0.81

Burke, Hagan-Burke, Kwok, & Parker (2009).

Predictive

First

End of First NWF

938

NR

0.69

Harn, Stoolmiller, & Chard (2008). 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. There was also an additional independent set of 109 students from the first district.

Predictive

First

End of First NWF

109

NR

0.62

Predictive

First

End of First ORF

938

NR

0.91

Predictive

First

End of First ORF

109

NR

0.85

Concurrent

First

DIBELS RTF

191

NR

0.31

Pressley, Hilden, & Shankland (2005). Participants were 191 third grade students in four schools in a small school district in a Midwest urban area.

Predictive

Third

Early winter ORF

16539 - 16908

0.90 - 0.91

0.91

Roehrig, Petscher,  Nettles, Hudson, & Torgesen (2008).

Predictive

Third

Late winter ORF

16539 - 16908

0.88 - 0.92

0.91

Predictive

Third

Middle of third ORF

401

NR

0.94

Shapiro, Solari, & Petscher (2008).

Predictive

Fourth

Middle of 4th ORF

394

NR

0.93

Predictive

Fifth

Middle of fifth ORF

205

NR

0.92

Predictive

Fifth

Middle of fifth ORF

205

NR

0.70

Predictive

Third

Middle of 3rd ORF

52

NR

0.91

Shaw & Shaw (2002).

Predictive

Third

End of 3rd ORF

52

0.89 - 0.93

0.91

 

Predictive Validity of the Slope of Improvement

Grade12345
RatingEmpty bubbleEmpty bubbleEmpty bubbledashdash

Type of Validity

Age or Grade

Test or Criterion

n (range)

Coefficient Range

Coefficient Median

Predictive, Pearson r

Middle to end of grade 1

End of grade 1 SAT10

4,973

 

0.62

Beginning to end of grade 2

End of grade 2 SAT10

4,826

 

0.50

Middle of grade 1 to end of grade 2

End of grade 2 SAT 10

2,417

 

0.36

Additional variance explained by slope, after controlling for initial level of performance

Middle of grade 1 to end of grade 2

End of Grade 2 SAT10

2,417

 

10%

Beginning of grade 2 to end of grade 3

End of Grade 3 OSRA

2,367

 

3%

Information (including normative data) / Subjects:

Baker, S. K., Smolkowski, K., Katz, R., Fien, H., Seeley, J. R., Kame’enui, E. J., & Thomas Beck, C. (2008). Reading fluency as a predictor of reading proficiency in low-performing, high-poverty schools. School Psychology Review, 37(1) 18 – 37.

Subjects included first through third grade students in the first two years of Oregon Reading First implementation. Median benchmark reading scores across two years (i.e., five data points from the middle of grade 1 to end of grade 2, and six data points from the beginning of grade 2 to end of grade 3) were used to calculate slope. The analysis focused on the additional variance in the outcome measure that was explained by slope of ORF performance after accounting for initial performance level.

The sample included students from 34 schools in 16 school districts located throughout the state of Oregon. Half of the schools were in large urban settings and the rest were approximately equally divided between midsize cities and rural areas. 10% of the students received special education services and 32% were English learners. 68% of English learners were Latino students, the remaining were Asian, American Indian, and Hawaiian Pacific Islanders. 69% of students at Oregon Reading First schools qualified for free or reduced cost lunch program, and 27% did not pass minimum proficiency standard on the Oregon Statewide Reading Assessment.

 

Bias Analysis Conducted

Grade12345
RatingNoNoNoNoNo

Disaggregated Reliability and Validity Data

Grade12345
RatingNoNoNoNoNo

Alternate Forms

Grade12345
RatingEmpty bubbleEmpty bubbleEmpty bubbleEmpty bubbleEmpty bubble

What is the number of alternate forms of equal and controlled difficulty?

26 alternate forms are available in grade 1; 29 alternate forms are available in each grade 2 - 5.

Form construction: Readability formulas were used to assist in creating alternate forms. First, short passages of the approximate correct difficulty were written. Then these passages were edited for grammar and content. The Spache readability metric was used to revise and refine the passages to achieve a Spache readability statistic that was the end of the grade the passage was intended for, or the beginning of the next grade. If the Spache index indicated a passage was too difficult, difficult words were replaced by easier words, and long sentences were broken up into shorter sentences. If passages were too easy, the opposite approach was taken (Good & Kaminski, 2002).

Nine different readability formulas were then applied to determine which passages would be benchmark passages, which would be progress monitoring passages, and what order the passages would be presented in. Within a grade, passages were rank ordered by relative difficulty by determining the average readability z score for each passage. The rank-ordered set of passages was split into thirds. The middle three passages from each third were chosen as benchmark passages and randomly assigned to the beginning, middle or end of year so that each benchmark assessment period had passages from the “easy”, “middle” and “difficult” groups. A stratified random sampling procedure was then used to determine the order of the remaining progress monitoring passages (Good & Kaminski, 2002).

Stoolmiller, Biancarosa & Fien (2013) report an alternate form reliability in second grade of 0.92 to 0.93 across three benchmark passages. In addition, our own internal investigation has shown that alternate-form reliability for benchmark passages is quite good:

Grade 1: 0.94 to 0.95

Grade 2: 0.93

Grade 3: 0.90 to 0.93

Grade 4: 0.84 to 0.92

Grade 5: 0.93

 

Rates of Improvement Specified

Grade12345
RatingEmpty bubbleEmpty bubbleEmpty bubbleEmpty bubbleEmpty bubble

What is the basis for specifying minimum acceptable growth?
Norm-referenced, Criterion-referenced and other: Initial-skill norm groups

Description of normative sample:

Representation: National

Date: 2013-14 school year

Number of states: 49

Size:

Grade

1

2

3

4

5

56,779

49,142

31,798

21,793

17,760


Regions: All (as defined by NCES: Northeast 14.1%, Midwest 19.9%, South 36.7%, West 29.3%)

Gender, SES, Race/ethnicity, ELL, Disability classification: unavailable.

Criterion-referenced Rates of Improvement

The minimal improvement is specified as the change between benchmarks within a year. For students who earn scores in the low risk range, adequate growth will maintain their low risk status. For students who earn scores in the some- or at-risk range, reducing their risk status would indicate adequate progress. In other words, adequate growth is (a) maintenance of low risk status, OR movement from: (b) at-risk to some-risk; (c) at-risk to low-risk; or (d) some-risk to low-risk within one benchmark assessment period. See GOM 7 for the benchmark goals and indicators of risk for a specific grade and time of year.

For example, the specified rate of improvement from beginning to end of grade 2 = (EOY benchmark – BOY benchmark)/number of weeks = (96-41)/30=1.83. Thus, benchmark grade 2 students need to improve by 1.83 words per week on ORF to remain on track from the beginning to end of grade 2.

Initial skill-based Norm-referenced Rates of Improvement

An alternative, and more precise standard for rates of improvement utilizes growth percentiles. These percentiles were determined separately for groups of students who performed similarly on the initial measurement of the skill. Growth percentiles were determined separately for each initial raw score by aggregating rates of growth for all students in the same grade in the DIBELS Data System who scored within ±0.5 SEM of that raw score in each norm group (Kennedy, Cummings, Bauer Schaper, & Stoolmiller, 2015).

For example, consider a second grade student who had an ORF score of 20 correctly read words at the beginning of the year. Growth at the 80th percentile (compared to other second grade students that scored within 0.5 SEM of 20 words per minute at the beginning of the year) means this student would read 74 words correctly per minute at the end of second grade. This represents growth of 54 words, or approximately 1.8 words per week. These Zones of Growth percentiles allow educators to set realistic, fine-tuned goals for individual students based on the performance of students with a similar initial skill level. The DIBELS Data System provides tools that help educators select growth goals that are average (50th percentile), above average (65th percentile), or ambitious (80th percentile) for any given initial score. Examples for every 10 initial raw scores from 10 to 140 are presented for grades 1 – 5 in the tables below.

Zones of Growth goals are available for the predominant measures in each grade. Zones of growth tools are available for ORF from the middle to end of first grade, and from the beginning to end of second – sixth grades.

DIBELS 6th Edition Oral Reading Fluency Grade 1 Zones of Growth Examples

 

End of Year ORF Score

Weekly Growth Estimate

Middle of Year ORF score

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

10

25

30

37

1.0

1.3

1.8

20

43

48

54

1.5

1.9

2.3

30

56

62

70

1.7

2.1

2.7

40

67

73

80

1.8

2.2

2.7

50

75

80

87

1.7

2.0

2.5

60

82

87

94

1.5

1.8

2.3

70

90

96

102

1.3

1.7

2.1

80

97

102

109

1.1

1.5

1.9

90

106

112

118

1.1

1.5

1.9

100

115

121

129

1.0

1.4

1.9

110

124

131

139

0.9

1.4

1.9

120

133

139

146

0.9

1.3

1.7

130

141

146

154

0.7

1.1

1.6

140

147

153

163

0.5

0.9

1.5

 

DIBELS 6th Edition Oral Reading Fluency Grade 2 Zones of Growth Examples

 

End of Year ORF Score

Weekly Growth Estimate

Beginning of Year ORF score

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

10

39

46

56

1.0

1.2

1.5

20

59

65

74

1.3

1.5

1.8

30

77

83

91

1.6

1.8

2.0

40

88

94

101

1.6

1.8

2.0

50

96

102

109

1.5

1.7

2.0

60

104

110

118

1.5

1.7

1.9

70

112

119

128

1.4

1.6

1.9

80

121

129

136

1.4

1.6

1.9

90

130

137

145

1.3

1.6

1.8

100

137

144

152

1.2

1.5

1.7

110

144

151

161

1.1

1.4

1.7

120

152

160

171

1.1

1.3

1.7

130

155

164

174

0.8

1.1

1.5

140

164

173

184

0.8

1.1

1.5

 

DIBELS 6th Edition Oral Reading Fluency Grade 3 Zones of Growth Examples

 

End of Year ORF Score

Weekly Growth Estimate

Beginning of Year ORF score

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

10

27

32

41

0.6

0.7

1.0

20

43

48

57

0.8

0.9

1.2

30

60

66

73

1.0

1.2

1.4

40

73

79

86

1.1

1.3

1.5

50

83

89

96

1.1

1.3

1.5

60

93

98

106

1.1

1.3

1.5

70

102

107

114

1.1

1.2

1.5

80

110

116

124

1.0

1.2

1.5

90

119

125

133

1.0

1.2

1.4

100

128

134

141

0.9

1.1

1.4

110

136

142

149

0.9

1.1

1.3

120

143

149

156

0.8

1.0

1.2

130

150

156

163

0.7

0.9

1.1

140

157

163

173

0.6

0.8

1.1

 

DIBELS 6th Edition Oral Reading Fluency Grade 4 Zones of Growth Examples

 

End of Year ORF Score

Weekly Growth Estimate

Beginning of Year ORF score

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

10

24

29

35

0.5

0.6

0.8

20

38

42

48

0.6

0.7

0.9

30

51

56

62

0.7

0.9

1.1

40

66

70

77

0.9

1.0

1.2

50

76

82

88

0.9

1.1

1.3

60

90

95

102

1.0

1.2

1.4

70

100

105

112

1.0

1.2

1.4

80

108

114

122

0.9

1.1

1.4

90

117

123

131

0.9

1.1

1.4

100

127

134

144

0.9

1.1

1.5

110

138

146

154

0.9

1.2

1.5

120

149

157

166

1.0

1.2

1.5

130

159

166

176

1.0

1.2

1.5

140

170

178

188

1.0

1.3

1.6

 

DIBELS 6th Edition Oral Reading Fluency Grade 5 Zones of Growth Examples

 

End of Year ORF Score

Weekly Growth Estimate

Beginning of Year ORF score

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

Average Growth (50th %ile)

Above Average Growth (65th %ile)

Ambitious Growth (80th %ile)

10

21

25

32

0.4

0.5

0.7

20

34

37

44

0.5

0.6

0.8

30

47

52

58

0.6

0.7

0.9

40

59

64

72

0.6

0.8

1.1

50

70

76

84

0.7

0.9

1.1

60

82

88

95

0.7

0.9

1.2

70

94

100

106

0.8

1.0

1.2

80

105

111

117

0.8

1.0

1.2

90

112

117

124

0.7

0.9

1.1

100

121

127

133

0.7

0.9

1.1

110

131

135

141

0.7

0.8

1.0

120

138

142

150

0.6

0.7

1.0

130

145

151

158

0.5

0.7

0.9

140

152

159

165

0.4

0.6

0.8

 

End-of-Year Benchmarks

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Benchmark goals for ORF are available in both criterion- and norm-referenced forms. Criterion-referenced benchmark goals have been re-calculated for grades 1 – 3 based on new data and analysis. End-of-year benchmark goals for ORF at the end of each grade are:

                Grade 1: 47

                Grade 2: 96

                Grade 3: 110

                Grade 4: 114

                Grade 5: 127

Oral Reading Fluency cut points for risk and benchmark goals are summarized in the table below for the beginning, middle, and end of the school year in grades 1 – 5.

Summary of DIBELS 6th Edition Oral Reading Fluency Criterion Referenced Benchmarks and Cut Points for Risk

Grade

Time of Year

Cut points

At Risk

Some Risk

Low Risk

1

Middle

0 – 12

13 – 18

≥ 19

End

0 – 30

31 - 46

≥ 47

Beginning

0 – 27

28 – 40

≥ 41

Middle

0 – 54

55 – 75

≥ 76

End

0 – 74

75 – 95

≥ 96

Beginning

0 – 56

57 – 71

≥ 72

Middle

0-75 76-88 ≥89

 

End 

0-96

97-109

≥110

 

Summary of DIBELS 6th Edition Oral Reading Fluency Norm Referenced Benchmarks and Cut Points for Risk

Grade

Time of Year

Cut points

Type

Below 20th percentile

20th – 39th percentile

40th percentile and above

4

Beginning

≤ 70

71 - 92

≥ 93

Historical norm-referenced
(Hasbrouck & Tindal, 1992)

Middle

≤ 82

83 - 104

≥ 105

End

≤ 95

96 - 117

≥ 118

5

Beginning

≤ 80

81 - 103

≥ 104

Middle

≤ 93

94 - 114

≥ 115

End

≤ 102

103 - 123

≥ 124

1

Middle

≤ 13

14 - 22

≥ 23

Norm-referenced
(40th percentile = benchmark goal and 20th percentile = cut point for at-risk; Cummings, Otterstedt, Kennedy, Baker, & Kame'enui, 2011)

End

≤ 27

28 - 47

≥ 48

2

Beginning

≤ 27

28 - 42

≥ 43

Middle

≤ 52

53 - 74

≥ 75

End

≤ 67

68 - 89

≥ 90

3

Beginning

≤ 52

53 - 73

≥ 74

Middle

≤ 66

67 - 88

≥ 89

End

≤ 84

85 - 103

≥ 104

4

Beginning

≤ 65

66 - 85

≥ 86

Middle

≤ 83

84 - 102

≥ 103

End

≤ 93

94 - 113

≥ 114

5

Beginning

≤ 81

82 - 106

≥ 107

Middle

≤ 93

94 - 117

≥ 118

End

≤ 104

105 - 126

≥ 127

Procedure for specifying criterion-referenced benchmarks, grades 1 - 3:

Procedures for determining benchmarks and cut points for risk for grades 1 - 3 are fully specified in Smolkowski and Cummings (2015).

Criterion measures included the Stanford Achievement Test – 10th Edition (SAT10) administered at the end of first and second grades, and the Oregon state assessment administered at the end of third grade. Oral Reading Fluency was administered at the beginning of grades 2 and 3 and the middle and end of grades 1 through 3. ROC curves were generated and the area under curve, A, was calculated at each time point. The benchmark standard and cut point for risk were only set for those time points in which A was at or above 0.75.  Benchmark and cut scores were chosen based on sensitivity at or above 0.80. In other words, the benchmark score was defined as the lowest score where sensitivity exceeded 0.80. Values of A, the decision threshold (i.e., score), sensitivity, specificity, negative and positive predictive values, base rate, and the proportion of students who screened positive are reported in the table below. These statistics were defined for students at risk (below the 20th normative percentile) and students at benchmark (40th normative percentile and above) (Smolkowski and Cummings, 2015).

Procedure for specifying norm-referenced benchmarks:

Norm-referenced cut points and benchmarks are defined as the 20th and 40th percentiles, respectively. Procedures are fully specified in Cummings et al. (2011).

Description of norm-sample for norm-referenced benchmarks and cut points for risk:

Representation: National

Date: 2009-10 school year

Number of students:

Grade

Beginning of Year

Middle of Year

End of Year

1

n/a

660,404

651,275

2

637,017

615,480

608,782

3

523,144

502,368

496,638

4

346,306

325,664

323,097

5

288,493

264,345

264,536

Number of States: 50

Regions: Percent of schools in each region

Grade

Northeast

Midwest

South

West

1

15.72

36.97

27.25

30.06

2

15.53

26.52

27.26

30.69

3

13.15

26.01

26.26

34.58

4

11.75

31.54

17.67

39.04

5

10.25

31.12

15.27

43.37

Gender: Average school-level percent

Grade

Male

Female

Not reported

1

51.0

47.6

1.4

2

50.8

48.0

1.2

3

50.8

48.1

1.1

4

50.8

47.9

1.3

5

50.9

47.8

1.3

SES: Average school-level percent eligible for free/reduced price lunch

Grade

Percent eligible for F/R Lunch

1

52.5

2

53.5

3

54.2

4

53.1

5

53.3

Race ethnicity: Average school-level percent:

 

Grade

Race/ethnicity

1

2

3

4

5

American Indian/ Alaskan Native

2.4

2.6

2.9

3.1

3.3

Asian/ Pacific Islander

3.3

3.1

3.0

3.2

3.3

Hispanic

14.0

14.0

14.8

14.9

19.8

Black

14.6

15.2

14.6

11.0

10.1

White

63.8

63.5

63.2

65.9

65.6

Hawaiian Native/ Pacific Islander

0.3

0.3

0.3

0.3

0.4

Two or more races

3.0

2.8

2.6

2.7

2.8

Unknown

1.4

1.2

1.1

1.3

1.3

ELL: unknown

Disability classification: unknown

Sensitive to Student Improvement

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1. Describe evidence that the monitoring system produces data that are sensitive to student improvement (i.e., when student learning actually occurs, student performance on the monitoring tool increases on average).

Baker et al. (2008) showed that the effect of ORF slope in both second and third grade was significantly different from zero (t = 22.69 and 8.17, respectively). There was also significant variability in ORF slope (t = 32.97 and 29.74, respectively) which may be attributable to differences in instruction. Cummings, Stoolmiller, et al. (under review) also demonstrated that ORF slope/gains across a school year could serve as indicators of student improvement. In this paper, multilevel ORF gains were used as a means for schools to engage in evaluation of instructional programs.

Decision Rules for Changing Instruction

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Does your manual or published materials specify validated decision rules for when changes to instruction need to be made?

Yes.

Specify the decision rules:

A change in instruction is warranted if a student’s performance falls below the aim line between the beginning and end of year benchmark scores eight consecutive times. The DIBELS Data System progress monitoring graph uses color coding to indicate when a change of instruction should occur.

Decisions regarding whether or not to modify instruction focus on three key pieces of data: the goal (either criterion- or norm-referenced, as specified in GOM 6 and GOM 7), a line (the aim line) connecting students’ initial status to said goal, and students’ progress monitoring data between those two points. With DIBELS 6th edition, student progress can be monitored using either paper/pencil graphs or the University of Oregon DIBELS Data System (for an example, see https://dibels.uoregon.edu/docs/reports/StudentProgressMonitoringGraph_DIBELS6th_Example.pdf). Currently, the decision rule for making changes to instruction focuses on the number of  consecutive data points that fall below the aim line. Once eight consecutive data are below the aim line, school team members should review the student's instructional program and consider adjusting instruction.

What is the evidentiary basis for these decision rules?

These rules are based on the recommendations in a comprehensive review of research on CBM decision rules (Ardoin et al., 2013), which suggest that the relative instability of any given ORF score suggests that eight or more data points may be necessary to yield valid and reliable outcomes.

Decision Rules for Increasing Goals

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Does your manual or published materials specify validated decision rules for when changes to increase goals?

Yes.

Specify the decision rules:

Decisions regarding when to increase goals are based on the same three key pieces of data reported in GOM 9: the goal, the aim line, and students’ progress monitoring data between those two points. The decision rule for making changes to student goals focuses on the number of consecutive data points above the aim line. Once eight consecutive data points are above the aim line, school team members should review the student’s goal and consider making it more ambitious.

What is the evidentiary basis for these decision rules?

These rules are based on and consistent with the recommendations in a comprehensive review of research on CBM decision rules (Ardoin et al., 2013), which suggest that the relative instability of any given ORF score suggests that 8 or more data points may be necessary to yield valid and reliable outcomes.

Improved Student Achievement

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Improved Teacher Planning

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