iSTEEP
Oral Reading Fluency

Descriptive Information

Please provide a description of your tool:

The iSTEEP Oral Reading Fluency assessment is a direct measure of fluency. Reading fluency is the ability to read accurately, quickly and with expression. Fluent readers recognize words automatically and don’t struggle with decoding. Reading fluency is important because it provides a bridge between word recognition and comprehension. The ORF assessment asks students to read a passage carefully selected to be at grade level.

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

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

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

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

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

Students in general education
Students with disabilities
English language learners

ACADEMIC ONLY: What skills does the tool screen?

Reading

Phonological processing:

RAN
Memory
Awareness
Letter sound correspondence
Phonics
Structural analysis

Word ID

Accuracy
Speed

Nonword

Accuracy
Speed

Spelling

Accuracy
Speed

Passage

Accuracy
Speed

Reading comprehension:

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

Listening comprehension:

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

Mathematics

Global Indicator of Math Competence

Accuracy
Speed
Multiple Choice
Constructed Response

Early Numeracy

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Concepts

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Computation

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematic Application

Accuracy
Speed
Multiple Choice
Constructed Response

Fractions/Decimals

Accuracy
Speed
Multiple Choice
Constructed Response

Algebra

Accuracy
Speed
Multiple Choice
Constructed Response

Geometry

Accuracy
Speed
Multiple Choice
Constructed Response

Other (please describe):

Please describe specific domain, skills or subtests:

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

Internalizing
Externalizing
Internalizing and Externalizing

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

Acquisition and Cost Information

Where to obtain:

Email Address

support@isteep.com

Address

Phone Number

800.881.9142

Website

www.isteep.com

Initial cost for implementing program:

Cost

$2.00

Unit of cost

Student

Replacement cost per unit for subsequent use:

Cost

$2.00

Unit of cost

Student

Duration of license

Year

Additional cost information:

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

iSTEEP provides pricing options that range from $2.00/student for early literacy screening up to $8/student for a comprehensive “Pro” package. The “Pro” package includes access to the full iSTEEP program which includes benchmarking assessments, screening assessments, an adaptive diagnostic, and progress monitoring for both reading and math. A writing component and behavior component is also included. All assessments are computer based meaning the computer will automatically time the assessments, calculate the scores, and enter the scores into the system.

Provide information about special accommodations for students with disabilities.

Administration

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

General education teacher
Special education teacher
Parent
Child
External observer
Other

If other, please specify:

What is the administration setting?

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

If other, please specify:

Does the tool require technology?

Yes

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

Computer or tablet
Internet connection
Other technology (please specify)

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

What is the administration context?

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

If other, please specify:

Computer assisted.

What is the administration time?

Time in minutes

1

per (student/group/other unit)

student

Additional scoring time:

Time in minutes

0

per (student/group/other unit)

student

ACADEMIC ONLY: What are the discontinue rules?

No discontinue rules provided
Basals
Ceilings
Other

If other, please specify:

Are norms available?

Yes

Are benchmarks available?

Yes

If yes, how many benchmarks per year?

3

If yes, for which months are benchmarks available?

Fall, Winter, Spring

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

If yes, how many students can be rated concurrently?

Training & Scoring

Training

Is training for the administrator required?

No

Describe the time required for administrator training, if applicable:

Minimal time is required. There are quick demo videos and coach cards available to help walk users through the process.

Please describe the minimum qualifications an administrator must possess.

No minimum qualifications

Are training manuals and materials available?

Yes

Are training manuals/materials field-tested?

Yes

Are training manuals/materials included in cost of tools?

Yes

If No, please describe training costs:

Can users obtain ongoing professional and technical support?

Yes

If Yes, please describe how users can obtain support:

Implementation Packages are available for 24/7 online access to professional development training and resources. Complimentary training sessions are also released throughout the year.

Scoring

How are scores calculated?

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

If other, please specify:

Do you provide basis for calculating performance level scores?

Yes

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

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

What types of performance level scores are available?

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

If other, please specify:

Does your tool include decision rules?

Yes

If yes, please describe.

Decision rules are available for screening with iSTEEP assessments and determining need for Tier 1, Tier 2 or Tier 3 intervention. Beyond that, an optional protocol is offered for deeper data analysis and decision making. With the optional process, screening is the first step in a multiple gating process. After screening students receive a second assessment to determine if the student’s deficit is due to skill or performance problems (can’t do or wont’ do). This assessment provides an additional check on the student’s initial screening score. Conceptually, this assessment could be construed as a type of test retest reliability for students with skill deficits. The goal is identifying students with skill deficits and then the students with skill deficits move on to the next step which is a survey level assessment to determine grade and skill level in reading (this latter step is not considered screening but is part of intervention planning). Further, the STEEP process recommends that initial selection of students in the screening process be based upon a dual standard. In addition to being “low” with respect to benchmarks, we recommend that students also be in the lowest X% of the class. We typically recommend that X=16%. This helps districts to begin with students most in need and it helps to ensure only true positives become the target of intervention. Districts, depending on their intervention resources and goals, can set their own percentage of students for initial intervention. This percentage can be changed as a school is able to accommodate less or more students for intervention. Over identifying students for intervention can be a very significant problem for districts that lack the resources to deliver interventions for high numbers of students who may not truly need intervention. The STEEP data management system will automatically list students who meet the dual criteria of bottom X% (user specifies X) and below benchmark to facilitate decision making.

Can you provide evidence in support of multiple decision rules?

Yes

If yes, please describe.

The STEEP protocol was evaluated in the following article: VanDerHeyden AM, Witt JC, Gilbertson DA. Multi-year evaluation of the effects of a response to intervention (RTI) model on identification of children for special education. Journal of School Psychology. 2007;45:225–256. This article provides a comprehensive evaluation of the various decision rules. Other research has been conducted on separate decision rules such as the process for determining if low scores are the result of a skill deficit or lack of motivation.

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

This assessment yields a score representing the number correct in one minute. The score is calculated automatically by the system by subtracting responses with errors from the total responses produced by the student.

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

The assessment contains representative exemplars for the skill. Test stimuli are reviewed by content experts to ensure the items are well suited for this skill and does not contain irrelevant difficulty. The probes have been reviewed for ethnic and gender bias.

Classification Accuracy & Cross-Validation Summary

Grade	Grade 1	Grade 2	Grade 3
Classification Accuracy Fall
Classification Accuracy Winter
Classification Accuracy Spring

DIBELS Oral Reading Fluency Grade 1

Classification Accuracy

Select time of year

Fall

Winter

Spring

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

The criterion measure was DIBELS Next Oral Reading Fluency which is completely independent of iSTEEP.

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

Concurrent
Predictive

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

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

We used the 20th percentile on the criterion and on the predictor measure as the cut points. This cut-point was chosen because there is wide agreement that students below the 20th percentile need intensive intervention because, without such intervention, the students are unlikely to accomplish subsequent literacy goals. This cut-point also appears to align with the goals of NCII. We contrasted only two groups: students at high risk vs low risk. The analyses were performed using ROC analysis. Crosstabs were used to generate a 2 X 2 table (confusion matrix) to yield the classification data. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors, were as follows: (a) Below 20th Percentile: Needs Intervention, (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention, (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention, Percentage of Students at Each Performance Level for this Sample: Needs Intervention: 20, Below Benchmark: 28, Above Benchmark: 52.

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

Yes

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

Approximately 20% of the students had been placed in intervention using screening within and RTI model.

Cross-Validation

Has a cross-validation study been conducted?

No

If yes,

Select time of year.

Fall

Winter

Spring

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

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

Concurrent
Predictive

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

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

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

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

---

DIBELS Oral Reading Fluency Grade 2

Classification Accuracy

Select time of year

Fall

Winter

Spring

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

The criterion measure was DIBELS Next Oral Reading Fluency which is completely independent of iSTEEP. It is a standard test of oral reading fluency.

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

Concurrent
Predictive

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

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

We used the 20th percentile on the criterion and on the predictor measure as the cut points. This cut-point was chosen because there is wide agreement that students below the 20th percentile need intensive intervention because, without such intervention, the students are unlikely to accomplish subsequent literacy goals. This cut-point also appears to align with the goals of NCII. We contrasted only two groups: students at high risk vs low risk. The analyses were performed using ROC analysis. Crosstabs were used to generate a 2 X 2 table (confusion matrix) to yield the classification data. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors, were as follows: (a) Below 20th Percentile: Needs Intervention, (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention, (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention, Percentage of Students at Each Performance Level for this Sample: Needs Intervention: 22, Below Benchmark: 24, Above Benchmark: 56.

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

Yes

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

Approximately 20% were involved in intervention but the exact nature of the intervention was indicated.

Cross-Validation

Has a cross-validation study been conducted?

No

If yes,

Select time of year.

Fall

Winter

Spring

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

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

Concurrent
Predictive

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

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

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

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

---

Star Grade 3

Classification Accuracy

Select time of year

Fall

Winter

Spring

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

The Star Assessment was used as the criterion in this study. This assessment purports to be a broad measure of reading that incorporates multiple skills, including comprehensive. Star Reading is described as a computer-adaptive assessment for assessing student achievement in reading. It purports fulfill a variety of functions including: interim assessment, screening, standards benchmarking. Several studies and the NCII tools chart suggest Star Reading valid and reliable.

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

Concurrent
Predictive

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

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

We used the 20th percentile on the criterion and on the predictor measure as the cut points. This cut-point was chosen because there is wide agreement that students below the 20th percentile need intensive intervention because, without such intervention, the students are unlikely to accomplish subsequent literacy goals. This cut-point also appears to align with the goals of NCII. We contrasted only two groups: students at high risk vs low risk. The analyses were performed using ROC analysis. Crosstabs were used to generate a 2 X 2 table (confusion matrix) to yield the classification data. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors, were as follows: (a) Below 20th Percentile: Needs Intervention, (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention, (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention, Percentage of Students at Each Performance Level for this Sample: Needs Intervention: 22, Below Benchmark: 31, Above Benchmark: 47.

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

Yes

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

Approximately 20% of students were in intervention.

Cross-Validation

Has a cross-validation study been conducted?

No

If yes,

Select time of year.

Fall

Winter

Spring

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

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

Concurrent
Predictive

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

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

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

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

---

Classification Accuracy - Fall

Evidence	Grade 2	Grade 3
Criterion measure	DIBELS Oral Reading Fluency Grade 2	Star Grade 3
Cut Points - Percentile rank on criterion measure	20	20
Cut Points - Performance score on criterion measure	37	896
Cut Points - Corresponding performance score (numeric) on screener measure	33	59
Classification Data - True Positive (a)	37	42
Classification Data - False Positive (b)	8	41
Classification Data - False Negative (c)	9	20
Classification Data - True Negative (d)	151	173
Area Under the Curve (AUC)	0.93	0.84
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.88	0.80
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.97	89.00

Statistics	Grade 2	Grade 3
Base Rate	0.22	0.22
Overall Classification Rate	0.92	0.78
Sensitivity	0.80	0.68
Specificity	0.95	0.81
False Positive Rate	0.05	0.19
False Negative Rate	0.20	0.32
Positive Predictive Power	0.82	0.51
Negative Predictive Power	0.94	0.90

Sample	Grade 2	Grade 3
Date	August	August
Sample Size	205	276
Geographic Representation	West South Central (LA)	West South Central (LA)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Winter

Evidence	Grade 1
Criterion measure	DIBELS Oral Reading Fluency Grade 1
Cut Points - Percentile rank on criterion measure	20
Cut Points - Performance score on criterion measure	20
Cut Points - Corresponding performance score (numeric) on screener measure	22
Classification Data - True Positive (a)	16
Classification Data - False Positive (b)	5
Classification Data - False Negative (c)	3
Classification Data - True Negative (d)	71
Area Under the Curve (AUC)	0.95
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.91
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.99

Statistics	Grade 1
Base Rate	0.20
Overall Classification Rate	0.92
Sensitivity	0.84
Specificity	0.93
False Positive Rate	0.07
False Negative Rate	0.16
Positive Predictive Power	0.76
Negative Predictive Power	0.96

Sample	Grade 1
Date	January
Sample Size	95
Geographic Representation	West South Central (LA)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Reliability

Grade	Grade 1	Grade 2	Grade 3
Rating

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

Justification: Alternate form reliability provides an indication of the consistency of a student’s score at two different points in time. It also provides an indicator of the consistency of response to different items which is partially dependent of the equivalence of the forms. Justification: Inter-rater. The consistency of student scores can be influenced by examiner error. Inter-rater reliability provides an estimate of the extent to which student scores contain error related to the examiner.

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

Grade 1 ORF Inter-rater: The sample of 53 students was obtained from a large urban district in Louisiana. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors were as follows: (a) Below 20th Percentile: Needs Intervention (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention The Percentage of Students at Each Performance Level for this Sample were as follows: Needs Intervention: 22 Below Benchmark: 21 Above Benchmark: 57 Alternative Form: The students in this study included a diverse group of 166 students from an urban school in Louisiana. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors were as follows: (a) Below 20th Percentile: Needs Intervention (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention The Percentage of Students at Each Performance Level for this Sample were as follows: Needs Intervention: 26 Below Benchmark: 29 Above Benchmark: 45 Grade 2 ORF Inter-rater : The sample of 44 students was obtained from a large urban district in Louisiana. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors, were as follows: (a) Below 20th Percentile: Needs Intervention (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention The Percentage of Students at Each Performance Level for this Sample were as follows: Needs Intervention: 17 Below Benchmark: 24 Above Benchmark: 59 Alternative Form: The students in this study included a diverse group of 271 students from suburban and urban schools in Louisiana. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors were as follows: (a) Below 20th Percentile: Needs Intervention (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention The Percentage of Students at Each Performance Level for this Sample were as follows: Needs Intervention: 19 Below Benchmark: 32 Above Benchmark: 49 Grade 3 ORF Inter-rater : The sample of 50 students was obtained from a large urban district in Louisiana. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors were as follows: (a) Below 20th Percentile: Needs Intervention (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention The Percentage of Students at Each Performance Level for this Sample were as follows: Needs Intervention: 24 Below Benchmark: 24 Above Benchmark: 52 Alternative Form: The students in this study included a diverse group of 426 students from suburban and urban schools in 3 states. The analyses were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors, were as follows: (a) Below 20th Percentile: Needs Intervention (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention The Percentage of Students at Each Performance Level for this Sample were as follows: Needs Intervention: 20 Below Benchmark: 21 Above Benchmark: 59

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

Alternate Form Two alternate forms were administered in a single setting. The scores were used within a correlational analysis. Inter-Rater Audio recordings were made of student responses during a single assessment. Two different experienced assessors then independently scored each recording. The two scoring protocols were examined for agreement on a word-by-word basis. The analysis of agreement consisted of dividing the total number of agreements by the number of agreements plus disagreements.

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

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

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

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

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

No

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

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

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

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

Validity

Grade	Grade 1	Grade 2	Grade 3
Rating

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

For grades 1-2 the grade level DIBELS Next ORF assessment was used for concurrent validity and the iSTEEP Maze was used for predictive validity. The rationale for the selection of these criterion measures follows. For concurrent validity the DIBELS Next ORF assessment was used. Both the STEEP and DIBELS ORF purport to measure the same skills. The iSTEEP Maze Assessment was used. Maze is a multiple-choice cloze assessment where, words are replaced with three words inside parentheses. One of these words is correct. Given the theoretical and empirical linkage between fluency and comprehension, showing a relationship between fluency and the subsequent development of basic comprehension skills would support the validity of the ORF assessment. We acknowledge the use of a criterion that is not external to the iSTEEP system may cause concern. However maze and ORF are different ways of assessing reading which may help to assuage concerns about method variance. Also, item overlap is minimal in that the two assessments don’t rely on the same item types. The ORF assessment was administered within the second and third week of January and the Maze assessment was administered within the first two weeks of May. For Grade 3, the Star Assessment was used for concurrent validity. This assessment purports to be a broad measure of reading that incorporates multiple skills, including comprehension. Star Reading is described as a computer-adaptive assessment for assessing student achievement in reading. It purports fulfill a variety of functions including: interim assessment, screening, standards benchmarking. Several studies and the NCII tools chart suggest Star Reading valid and reliable. Both the iSTEEP ORF and Star Reading were administered in Winter. The criterion used for the predictive validity study was the Benchmark Assessment System (BAS, Fountas and Pinnell, 2016) The BAS is designed to evaluate student reading and comprehension ability and determine each student’s instructional level. Studies on the reliability of this measure indicate median reliability of .94. The authors report concurrent validity coefficients using external measures ranging from the mid .60’s to the mid .90’s. Compton, Fuchs, Fuchs, Fuchs, Bouton, Gilbert, Barquero, Cho, E., & Crouch, (2010) reported concurrent validity coefficients with WIF and ORF measures in .70’s and .80’s. The BAS was an appropriate criterion in that it incorporates both reading and comprehension and the iSTEEP ORF assessment assesses oral reading fluency. Logically and theoretically the development of reading comprehension would be predicted by reading fluency. The iSTEEP ORF was administered in Winter and the BAS was administered in Spring. Additional validity measures added after interim review First Grade: The Group Reading Assessment and Diagnostic Evaluation (GRADE) assessment was used in a concurrent validity study. Both the STEEP ORF and GRADE assess important early literacy skills. Second grade: The Word Identification subtest from the Woodcock Reading Mastery Test was used in a concurrent validity study. Both the WRMT and the iSTEEP ORF measure word reading skills. Third Grade: The Word Identification subtest from the Woodcock Reading Mastery Test was used in a concurrent validity study. Both the WRMT and the iSTEEP ORF measure word reading skills. References Fountas IC, Pinnell GS. (2016) Field Study of Reliability and Validity of the Benchmark Assessment Systems I and 2. Portsmouth: Heinemann Compton, D. L., Fuchs, D., Fuchs, L. S., Bouton, B., Gilbert, J. K., Barquero, L. A., Cho, E., & Crouch, R. C. (2010). Selecting At-Risk First-Grade Readers for Early Intervention: Eliminating False Positives and Exploring the Promise of a Two-Stage Gated Screening Process. Journal of educational psychology, 102(2), 327–340.

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

Grade 1 Concurrent Validity with DIBELS Next The sample included a diverse group of 95 students for one Southern state. The sample was representative of students across all performance levels (see additional details below). Concurrent Validity with GRADE. The sample included a diverse group of 73 students for one Southern state. The sample was representative of students across all performance levels (see additional details below). Predicative Validity Sample with iSTEEP Maze For the predictive validity study, the sample included a diverse group of 1672 students from rural, urban and suburban schools across six states. The sample was representative of students across all performance levels (see additional details below). Grade 2 Concurrent Validity Sample with DIBELS Next ORF The sample included a diverse group of 111 students for one midwestern state. The sample was representative of students across all performance levels (see additional details below). Predicative Validity Sample with iSTEEP Maze For the predictive validity study, the sample included a diverse group of 2874 students from rural, urban and suburban schools across four states. The sample was representative of students across all performance levels (see additional details below). Concurrent Validity Study with Woodcock Reading Mastery Test (Word Identification) This sample included a diverse group of 111 students for one mid-western state. The sample was representative of students across all performance levels (see additional details below). Grade 3 Concurrent Validity Sample with Star The sample included a diverse group of 294 students from one Southern state. The sample was representative of students across all performance levels (see additional details below). Predicative Validity Sample with Benchmark Assessment System For the predictive validity study, the sample included a diverse group of 416 students from one midwestern state. The sample was representative of students across all performance levels (see additional details below). Concurrent Validity Study with Woodcock Reading Mastery Test This study included a diverse group of 50 students. The sample was representative of students across all performance levels (see additional details below). For all Grades The analyses listed above were performed on a sample of students that was representative of students across all performance levels. The performance level descriptors for the iSTEEP assessments, were as follows: (a) Below 20th Percentile: Needs Intervention (b) Between 20th and 40th Percentile: Below Benchmark, May need individual intervention (c) Above 40th Percentile: Above Benchmark, Unlikely to Need Individual Intervention Across all validity analyses the Percentage of Students at Each Performance Level for the various Samples ranged as follows: Needs Intervention: 18-24% of students Below Benchmark: 21-31% of students Above Benchmark: 49-61% of students

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

For both the concurrent and predictive validity samples, the scores from the iSTEEP screener and the criterion were subjected to analysis using bi-variate correlational analysis.

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

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

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

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

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

Validity coefficients are within an acceptable range given the expected relationship with the criterion measures.

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

No

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

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

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

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

Bias Analysis

Grade	Grade 1	Grade 2	Grade 3
Rating	No	No	No

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

No

If yes,

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

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

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