iSTEEP
Nonsense Word Fluency

Descriptive Information

Please provide a description of your tool:

The iSTEEP Nonsense Word Fluency task is an assessment of alphabetic principle and letter sound relationships which calls for the student to demonstrate knowledge that words are comprised of letters and sounds as well as applying systematic rules that govern the relationship between letters and phonemes. The nonsense word task requires students to decode novel words. The use of non-words controls for the possibility the student might know a real word from sight. In this task, the student is presented with novel words and must decode the letters/sounds to form words. The student is able to demonstrate knowledge of letter sound correspondence and ability to blend sounds into words.

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

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.

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 those 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 skill deficits 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. Each form contains 135 items.

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
Classification Accuracy Fall
Classification Accuracy Winter
Classification Accuracy Spring

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

DIBELS Oral Reading Fluency

Classification Accuracy

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.

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: 25 Above Benchmark: 53

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 an RTI model.

Cross-Validation

Has a cross-validation study been conducted?

No

If yes,

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

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 - Winter

Reliability

Grade	Grade 1
Rating

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

*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.

Alternate Form: The students in this study included a diverse group of 125 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 Percentage of Students at Each Performance Level for this Sample: Needs Intervention: 21 Below Benchmark: 32 Above Benchmark: 47 Inter-rater Sample Characteristics : The sample of 39 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 Percentage of Students at Each Performance Level for this Sample: Needs Intervention: 19 Below Benchmark: 27 Above Benchmark: 54

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

Study 1: Two alternate forms were administered in a single setting. The scores were used within a correlational analysis. Study 2: 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).

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.

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
Rating

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

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

For concurrent validity the DIBELS Next ORF assessment was used. Empirically, theoretically and as a practical matter, NWF has been shown repeatedly to correlate with ORF. For one predictive validity study, we used the STEEP ORF assessment. Once students have mastered letter sound correspondence, within a reading skill sequence, they have mostly demonstrated the pre-requisites for word reading. Hence, an empirical demonstration of the extent to which NWF predicts ORF provides evidence of the predictive validity of a specific NWF assessment. For a second predictive validity study, we used DIBELS Next ORF as the criterion. From an instructional perspective, Oral Reading Skills would be predicted to emerge following or concurrent with the emergence of skills in letter-sound correspondence (the skill assessed by NWF). Hence, a moderate correlation with ORF would be expected based on early literacy research. A note about the use of the iSTEEP ORF assessment. We understand there may be a concern because of the use of this internal criterion measure. However, it is also the case that just because two assessments are from the same family this does not automatically lead to the conclusion that validity coefficients will be inflated due to shared method variance and item overlap, especially when methods are different and there is no item overlap. We would like to offer additional information about the two major issues with the use of an assessment from the same family, shared method variance and item overlap. First, the methods used by the two assessments are different and method variance is unlikely to play a role in this instance.  By method variance we refer to variance that is attributable to the measurement method rather than to the constructs the measures are assumed to represent.  In terms of the method of assessment, Nonsense Word Fluency involves students reading a list of isolated nonsense words. The words are not real words. With ORF, a student is given a passage of connected text consisting of real words to read and the score is simply the number of words read correctly. Since NWF and ORF are different methods of assessing reading this may help to assuage concerns about method variance. Second, with regard to item overlap—there is no item overlap. Item overlap is not a factor because the two assessments don’t rely on the same item types or content. ORF includes only real words. NWF includes only non-real words. Hence, there is no possible overlap in items.

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

Concurrent Validity Sample The sample included a diverse group of 97 students for one Southern state. 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: 23 Below Benchmark: 51 Above Benchmark: 26 Predicative Validity Sample For the first predictive validity study, the sample included a diverse group of 7657 students from rural, urban and suburban schools across six 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 Percentage of Students at Each Performance Level for this Sample: Needs Intervention: 20 Below Benchmark: 23 Above Benchmark: 57 For the second predictive validity study with DIBELS as the criterion, the sample included a diverse sample of 77 students from one Southern state. 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: 26 Above Benchmark: 54 In summary, in line with TRC requirements, the analyses for both types of validity were conducted on the general population of students which is a sample that is representative of students across all performance levels. Percent of students at each performance level is documented above. The sample for the concurrent validity study was assessed with both measures in January. The assessments for predictive validity with iSTEEP as the criterion occurred in January for the predictor and in April for the criterion. With the predictive validity study using DIBELS as the criterion, NWF assessment was conducted in August and DIBELS was conducted in January.

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

Description of Analysis Procedures for the concurrent validity study: Bivariate correlation between the two measures was used to derive the validity coefficients. Description of Analysis Procedures for the predictive validity study: Bivariate correlation between the two measures was used to derive the validity coefficients.

*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.

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.

The validity coefficients provide moderate support for the use of iSTEEP NWF for early literacy screening of letter sound knowledge.

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.

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

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.