iSTEEP
Maze Reading
Summary
The iSTEEP Maze assessment is a test of reading comprehension which requires students to read connected text and fill in a missing word. Students use a selected response format to select the word that causes the sentence to make sense. Comprehension skills are required to understand the text and to select an appropriate word.
- Where to Obtain:
- iSTEEP
- support@isteep.com
- 800.881.9142
- www.isteep.com
- Initial Cost:
- $2.00 per student
- Replacement Cost:
- $2.00 per student per Year
- Included in Cost:
- 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.
- Training Requirements:
- Training not required
- Qualified Administrators:
- No minimum qualifications specified.
- Access to Technical 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.
- Assessment Format:
-
- Direct: Computerized
- Scoring Time:
-
- Scoring is automatic
- Scores Generated:
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- Raw score
- Percentile score
- Administration Time:
-
- 3 minutes per group
- Scoring Method:
-
- Automatically (computer-scored)
- Technology Requirements:
-
- Computer or tablet
- Internet connection
- Accommodations:
Descriptive Information
- Please provide a description of your tool:
- The iSTEEP Maze assessment is a test of reading comprehension which requires students to read connected text and fill in a missing word. Students use a selected response format to select the word that causes the sentence to make sense. Comprehension skills are required to understand the text and to select an appropriate word.
ACADEMIC ONLY: What skills does the tool screen?
- Please describe specific domain, skills or subtests:
- BEHAVIOR ONLY: Which category of behaviors does your tool target?
-
- 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
- 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
- Do you provide basis for calculating performance level scores?
-
Yes
- Does your tool include decision rules?
-
Yes
- If yes, please describe.
- Decision rules are available for the screening with the iSTEEP assessment 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 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 insure 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?
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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 the process for determining is low scores is the result of skill or motivation issue.
- 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 three minutes. The score is calculated automatically by the system.
- 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 exemplar 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.
Technical Standards
Classification Accuracy & Cross-Validation Summary
Grade |
Grade 3
|
---|---|
Classification Accuracy Fall | |
Classification Accuracy Winter | |
Classification Accuracy Spring |
Star
Classification Accuracy
- 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 comprehension.
- 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: 23, Below Benchmark: 20, Above Benchmark: 57.
- 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 16% of students were in intervention based on the results of an MTSS process.
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
Evidence | Grade 3 |
---|---|
Criterion measure | Star |
Cut Points - Percentile rank on criterion measure | 20 |
Cut Points - Performance score on criterion measure | 896 |
Cut Points - Corresponding performance score (numeric) on screener measure | 20 |
Classification Data - True Positive (a) | 18 |
Classification Data - False Positive (b) | 7 |
Classification Data - False Negative (c) | 11 |
Classification Data - True Negative (d) | 88 |
Area Under the Curve (AUC) | 0.83 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.74 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.93 |
Statistics | Grade 3 |
---|---|
Base Rate | 0.23 |
Overall Classification Rate | 0.85 |
Sensitivity | 0.62 |
Specificity | 0.93 |
False Positive Rate | 0.07 |
False Negative Rate | 0.38 |
Positive Predictive Power | 0.72 |
Negative Predictive Power | 0.89 |
Sample | Grade 3 |
---|---|
Date | January |
Sample Size | 124 |
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 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. Coefficient Alpha was used to obtain a second estimate of reliability. This provides an estimate of the internal consistency of the assessment.
- *Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
- Grade 3 Maze Alpha : The sample of 787 students was obtained from 3 districts 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: 24, Below Benchmark: 25, Above Benchmark: 51. 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, Percentage of Students at Each Performance Level for this Sample: Needs Intervention: 20, Below Benchmark: 19, Above Benchmark: 61.
- *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. Alpha: Data were collected and item level data were analyzed with Coefficient Alpha.
*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 3
|
---|---|
Rating |
- *Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
- Concurrent 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. Both the iSTEEP Maze and Star Reading were administered in Winter. Predictive: The Mississippi State Test was used as the criterion for predictive validity.
- *Describe the sample(s), including size and characteristics, for each validity analysis conducted.
- Concurrent Validity Sample The sample included a diverse group of 275 students for one Southern state. The sample 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 median Percentage of Students at Each Performance Level for the various Samples ranged as follows: Needs Intervention: 20% of students Below Benchmark: 28% of students Above Benchmark: 52% of students Predictive Validity Sample For the predictive validity study, the sample included a diverse group of 294 students from a suburban school in Mississippi. The sample was representative of students across all performance levels. Both sets of validity 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 meidan Percentage of Students at Each Performance Level for these Samples: Needs Intervention: 21, Below Benchmark: 24, Above Benchmark: 55.
- *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.
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 3
|
---|---|
Rating | 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.
Data Collection Practices
Most tools and programs evaluated by the NCII are branded products which have been submitted by the companies, organizations, or individuals that disseminate these products. These entities supply the textual information shown above, but not the ratings accompanying the text. NCII administrators and members of our Technical Review Committees have reviewed the content on this page, but NCII cannot guarantee that this information is free from error or reflective of recent changes to the product. Tools and programs have the opportunity to be updated annually or upon request.