Istation’s Indicators of Progress (ISIP)
Advanced Reading
Summary
ISIP Advanced Reading (ISIP AR) is a web based computer adaptive assessment intended for students in Grade 4 through Grade 8 and can be administered simultaneously to an entire classroom in approximately 30 minutes. There is no additional scoring time required for the assessment. Teachers can be trained on ISIP AR through either a webinar or an in-person training session. Training takes between 1 and 4 hours. All training materials are online and are created by Istation. Reports are available for both individual and groups of students indicating single administration results and comparisons of results over time. All reports include student scaled scores and tier levels based on student percentiles.
- Where to Obtain:
- Istation
- info@istation.com
- 8150 North Central Expressway, Suite 2000, Dallas, TX, 75206
- (866) 883-READ
- www.istation.com
- Initial Cost:
- $5.95 per student
- Replacement Cost:
- $5.95 per student per year
- Included in Cost:
- ISIP AR is purchased as a yearly subscription. ISIP AR assessment packages includes online assessment, data hosting, reporting, teacher resources, online training center, user guides and manuals. In-person training conducted by a professional development specialist cost is $2800 per specialist per day. Computers and/or tablets are needed to implement this assessment, as well as internet access. ISIP AR can be used on many different technology platforms including desktops, laptops, and tablets.
- Appropriate accommodations are provided during ISIP assessments for students who are receiving support services, including those who have an Individual Education or 504 Plan, or who qualify as English Language learners. These accommodations support students’ access to the content of the assessment by reducing or eliminating the effects of the disability or limitation but do not change the content of the assessment. ISIP assessments provide people with disabilities access that is comparable to access for non-impaired people — with the exception of a totally blind or totally deaf disabled person. Administrators with manager accounts can assign accommodations to students in the Istation report and Management Portal.
- Training Requirements:
- 1-4 hours of training
- Qualified Administrators:
- Paraprofessional
- Access to Technical Support:
- By email and phone (M-F 7am-6:30pm) CST)
- Assessment Format:
-
- Performance measure
- Direct: Computerized
- One-to-one
- Scoring Time:
-
- Scoring is automatic
- Scores Generated:
-
- Raw score
- Percentile score
- IRT-based score
- Lexile score
- Composite scores
- Subscale/subtest scores
- Administration Time:
-
- 30 minutes per student/group
- Scoring Method:
-
- Automatically (computer-scored)
- Technology Requirements:
-
- Computer or tablet
- Internet connection
- Other technology :
- Accommodations:
- Appropriate accommodations are provided during ISIP assessments for students who are receiving support services, including those who have an Individual Education or 504 Plan, or who qualify as English Language learners. These accommodations support students’ access to the content of the assessment by reducing or eliminating the effects of the disability or limitation but do not change the content of the assessment. ISIP assessments provide people with disabilities access that is comparable to access for non-impaired people — with the exception of a totally blind or totally deaf disabled person. Administrators with manager accounts can assign accommodations to students in the Istation report and Management Portal.
Descriptive Information
- Please provide a description of your tool:
- ISIP Advanced Reading (ISIP AR) is a web based computer adaptive assessment intended for students in Grade 4 through Grade 8 and can be administered simultaneously to an entire classroom in approximately 30 minutes. There is no additional scoring time required for the assessment. Teachers can be trained on ISIP AR through either a webinar or an in-person training session. Training takes between 1 and 4 hours. All training materials are online and are created by Istation. Reports are available for both individual and groups of students indicating single administration results and comparisons of results over time. All reports include student scaled scores and tier levels based on student percentiles.
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?
- 12
- If yes, for which months are benchmarks available?
- Entire year; January through December
- 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?
- Yes
- Describe the time required for administrator training, if applicable:
- 1-4 hours of training
- Please describe the minimum qualifications an administrator must possess.
- Paraprofessional
- 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:
- By email and phone (M-F 7am-6:30pm) CST)
Scoring
- Do you provide basis for calculating performance level scores?
-
Yes
- Does your tool include decision rules?
-
No
- If yes, please describe.
- Can you provide evidence in support of multiple decision rules?
-
No
- If yes, please describe.
- 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.
- Ability scores are estimated using Bayesian EAP with an informative prior under a 2 PL unidimensional IRT model. Reported scale scores are generated through a linear transformation of the raw IRT-based ability scores. An overall ability is estimated after all of the appropriate sub-contents are measured based on the responses from all 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.
- Ability scale scores are compared to cut-points determined from nationally representative norming sample to classify students into one out of three instructional tiers. The data used for the calibration was based on an ethnically diverse regional sample including urban and suburban students of varied ability and backgrounds. Annual reviews of item parameters, scoring, scaling, and the setting of cut-points is practiced for ISIP AR.
Technical Standards
Classification Accuracy & Cross-Validation Summary
Grade |
Grade 4
|
Grade 5
|
Grade 6
|
Grade 7
|
Grade 8
|
---|---|---|---|---|---|
Classification Accuracy Fall | |||||
Classification Accuracy Winter | |||||
Classification Accuracy Spring |
MAP Reading
Classification Accuracy
- Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
- MAP Reading is a computer adaptive assessment of reading ability. It is similar to ISIP AR in the fact that each student receives a set of items that is optimal for the student’s ability level. ISIP AR and MAP are independent to each other.
- 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).
- Classification accuracy analyses were performed to determine ISIP AR using MAP as the criterion assessments. 20th percentile are used for both measures and it is a cut point for intensive need. The data were collected in 2015-16 school year from urban districts in the State of Texas.
- Were the children in the study/studies involved in an intervention in addition to typical classroom instruction between the screening measure and outcome assessment?
-
No
- If yes, please describe the intervention, what children received the intervention, and how they were chosen.
Cross-Validation
- Has a cross-validation study been conducted?
-
Yes
- If yes,
- Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
- MAP Reading is a computer adaptive assessment of reading ability. It is similar to ISIP AR in the fact that each student receives a set of items that is optimal for the student’s ability level. ISIP AR and MAP are independent to each other.
- 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).
- Cross-validation analyses were performed to determine ISIP AR using MAP as the criterion assessments. 20th percentile are used for both measures and it is a cut point for intensive need. The data were collected in 2015-16 school year from urban districts in the State of Texas.
- Were the children in the study/studies involved in an intervention in addition to typical classroom instruction between the screening measure and outcome assessment?
-
No
- If yes, please describe the intervention, what children received the intervention, and how they were chosen.
Classification Accuracy - Fall
Evidence | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Criterion measure | MAP Reading | MAP Reading | MAP Reading | MAP Reading | MAP Reading |
Cut Points - Percentile rank on criterion measure | 20 | 20 | 20 | 20 | 20 |
Cut Points - Performance score on criterion measure | 188 | 195 | 201 | 204 | 207 |
Cut Points - Corresponding performance score (numeric) on screener measure | 1689 | 1783 | 1858 | 1989 | 2059 |
Classification Data - True Positive (a) | |||||
Classification Data - False Positive (b) | |||||
Classification Data - False Negative (c) | |||||
Classification Data - True Negative (d) | |||||
Area Under the Curve (AUC) | 0.90 | 0.92 | 0.90 | 0.83 | 0.82 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.88 | 0.90 | 0.89 | 0.81 | 0.79 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.91 | 0.93 | 0.92 | 0.85 | 0.85 |
Statistics | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Base Rate | |||||
Overall Classification Rate | |||||
Sensitivity | |||||
Specificity | |||||
False Positive Rate | |||||
False Negative Rate | |||||
Positive Predictive Power | |||||
Negative Predictive Power |
Sample | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Date | October, 2015 | October, 2015 | October, 2015 | October, 2015 | October, 2015 |
Sample Size | |||||
Geographic Representation | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) |
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 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Criterion measure | MAP Reading | MAP Reading | MAP Reading | MAP Reading | MAP Reading |
Cut Points - Percentile rank on criterion measure | 20 | 20 | 20 | 20 | 20 |
Cut Points - Performance score on criterion measure | 194 | 200 | 204 | 207 | 209 |
Cut Points - Corresponding performance score (numeric) on screener measure | 1738 | 1812 | 1880 | 2010 | 2082 |
Classification Data - True Positive (a) | |||||
Classification Data - False Positive (b) | |||||
Classification Data - False Negative (c) | |||||
Classification Data - True Negative (d) | |||||
Area Under the Curve (AUC) | 0.93 | 0.93 | 0.86 | 0.82 | 0.83 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.91 | 0.92 | 0.84 | 0.80 | 0.80 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.94 | 0.94 | 0.88 | 0.85 | 0.85 |
Statistics | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Base Rate | |||||
Overall Classification Rate | |||||
Sensitivity | |||||
Specificity | |||||
False Positive Rate | |||||
False Negative Rate | |||||
Positive Predictive Power | |||||
Negative Predictive Power |
Sample | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Date | January, 2016 | January, 2016 | January, 2016 | January, 2016 | January, 2016 |
Sample Size | |||||
Geographic Representation | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) |
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 - Spring
Evidence | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Criterion measure | MAP Reading | MAP Reading | MAP Reading | MAP Reading | MAP Reading |
Cut Points - Percentile rank on criterion measure | 20 | 20 | 20 | 20 | 20 |
Cut Points - Performance score on criterion measure | 196 | 202 | 206 | 208 | 209 |
Cut Points - Corresponding performance score (numeric) on screener measure | 1776 | 1936 | 1897 | 2031 | 2105 |
Classification Data - True Positive (a) | |||||
Classification Data - False Positive (b) | |||||
Classification Data - False Negative (c) | |||||
Classification Data - True Negative (d) | |||||
Area Under the Curve (AUC) | 0.92 | 0.89 | 0.86 | 0.81 | 0.79 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.91 | 0.87 | 0.83 | 0.78 | 0.75 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.93 | 0.91 | 0.88 | 0.84 | 0.84 |
Statistics | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Base Rate | |||||
Overall Classification Rate | |||||
Sensitivity | |||||
Specificity | |||||
False Positive Rate | |||||
False Negative Rate | |||||
Positive Predictive Power | |||||
Negative Predictive Power |
Sample | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Date | June, 2016 | June, 2016 | June, 2016 | June, 2016 | June, 2016 |
Sample Size | |||||
Geographic Representation | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) |
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 |
Cross-Validation - Fall
Evidence | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Criterion measure | MAP Reading | MAP Reading | MAP Reading | MAP Reading | MAP Reading |
Cut Points - Percentile rank on criterion measure | 20 | 20 | 20 | 20 | 20 |
Cut Points - Performance score on criterion measure | 188 | 195 | 201 | 204 | 207 |
Cut Points - Corresponding performance score (numeric) on screener measure | 1689 | 1783 | 1858 | 1989 | 2059 |
Classification Data - True Positive (a) | |||||
Classification Data - False Positive (b) | |||||
Classification Data - False Negative (c) | |||||
Classification Data - True Negative (d) | |||||
Area Under the Curve (AUC) | 0.90 | 0.92 | 0.90 | 0.83 | 0.82 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.88 | 0.90 | 0.89 | 0.81 | 0.79 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.91 | 0.93 | 0.92 | 0.85 | 0.85 |
Statistics | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Base Rate | |||||
Overall Classification Rate | |||||
Sensitivity | |||||
Specificity | |||||
False Positive Rate | |||||
False Negative Rate | |||||
Positive Predictive Power | |||||
Negative Predictive Power |
Sample | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Date | October, 2015 | October, 2015 | October, 2015 | October, 2015 | October, 2015 |
Sample Size | |||||
Geographic Representation | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) |
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 |
Cross-Validation - Winter
Evidence | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Criterion measure | MAP Reading | MAP Reading | MAP Reading | MAP Reading | MAP Reading |
Cut Points - Percentile rank on criterion measure | 20 | 20 | 20 | 20 | 20 |
Cut Points - Performance score on criterion measure | 194 | 200 | 204 | 207 | 209 |
Cut Points - Corresponding performance score (numeric) on screener measure | 1738 | 1812 | 1880 | 2010 | 2082 |
Classification Data - True Positive (a) | |||||
Classification Data - False Positive (b) | |||||
Classification Data - False Negative (c) | |||||
Classification Data - True Negative (d) | |||||
Area Under the Curve (AUC) | 0.93 | 0.93 | 0.86 | 0.82 | 0.83 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.91 | 0.92 | 0.84 | 0.80 | 0.80 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.94 | 0.94 | 0.88 | 0.85 | 0.85 |
Statistics | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Base Rate | |||||
Overall Classification Rate | |||||
Sensitivity | |||||
Specificity | |||||
False Positive Rate | |||||
False Negative Rate | |||||
Positive Predictive Power | |||||
Negative Predictive Power |
Sample | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Date | January, 2016 | January, 2016 | January, 2016 | January, 2016 | January, 2016 |
Sample Size | |||||
Geographic Representation | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) |
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 |
Cross-Validation - Spring
Evidence | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Criterion measure | MAP Reading | MAP Reading | MAP Reading | MAP Reading | MAP Reading |
Cut Points - Percentile rank on criterion measure | 20 | 20 | 20 | 20 | 20 |
Cut Points - Performance score on criterion measure | 196 | 202 | 206 | 208 | 209 |
Cut Points - Corresponding performance score (numeric) on screener measure | 1776 | 1936 | 1897 | 2031 | 2105 |
Classification Data - True Positive (a) | |||||
Classification Data - False Positive (b) | |||||
Classification Data - False Negative (c) | |||||
Classification Data - True Negative (d) | |||||
Area Under the Curve (AUC) | 0.92 | 0.89 | 0.86 | 0.81 | 0.79 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.91 | 0.87 | 0.83 | 0.78 | 0.75 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.93 | 0.91 | 0.88 | 0.84 | 0.84 |
Statistics | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Base Rate | |||||
Overall Classification Rate | |||||
Sensitivity | |||||
Specificity | |||||
False Positive Rate | |||||
False Negative Rate | |||||
Positive Predictive Power | |||||
Negative Predictive Power |
Sample | Grade 4 | Grade 5 | Grade 6 | Grade 7 | Grade 8 |
---|---|---|---|---|---|
Date | June, 2016 | June, 2016 | June, 2016 | June, 2016 | June, 2016 |
Sample Size | |||||
Geographic Representation | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) | West South Central (TX) |
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 4
|
Grade 5
|
Grade 6
|
Grade 7
|
Grade 8
|
---|---|---|---|---|---|
Rating |
- *Offer a justification for each type of reliability reported, given the type and purpose of the tool.
- Cronbach’s (1951) coefficient alpha is typically used as an indicator of reliability across test items within a testing instance. However, Cronboch’s Alpha is not appropriate for any IRT based measure because alpha assumes that all students in the testing instance respond to a common set of items. Due to its very nature, students taking a CAT-based assessment, such as ISIP Advanced Reading, will receive a custom set of items based on their initial estimates of ability and response patterns. Thus, students do not respond to a common set of items. The IRT analogue to classical internal consistency is marginal reliability (Bock & Mislevy, 1982) and thus applied to ISIP Advanced Reading. Marginal reliability is a method of combining the variability in estimating abilities at different points on the ability scale into a single index. Like Cronbach’s alpha, marginal reliability is a unitless measure bounded by 0 and 1, and it can be used with Cronbach’s alpha to directly compare the internal consistencies of classical test data to IRT-based test data. ISIP Advanced Reading has a stopping criteria based on minimizing the standard error of the ability estimate. As such, the lower limit of the marginal reliability of the data for any testing instance of ISIP Advanced Reading will always be approximately 0.90.
- *Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
- Sample derived from the total population of students using the ISIP AR assessment throughout the 2014-2015 school year. Large sample size ranges from 83,621 to 226,558 students across the United States.
- *Describe the analysis procedures for each reported type of reliability.
- Istation derived IRT-based reliability from Classical Test Theory standpoint to Item Response Theory.
*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:
- Provide citations for additional published studies.
- Mathes, P. (2016). Istation’s Indicators of Progress (ISIP) Advanced Reading: Technical Report. Retrieved from https://www.istation.com/Content/downloads/studies/ar_technical_report.pdf
- 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:
- Provide citations for additional published studies.
Validity
Grade |
Grade 4
|
Grade 5
|
Grade 6
|
Grade 7
|
Grade 8
|
---|---|---|---|---|---|
Rating | d | d | d | d | d |
- *Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
- Predictive validity The Kansas Assessment Program (KAP) was developed by the Center for Educational Testing and Evaluation (CETE), part of the University of Kansas’ Achievement and Assessment Institute. The content of all KAP tests and tools is derived from Kansas’ approved content standards for English language arts, science, mathematics, and social studies. KAP field tests its test questions to ensure appropriate fairness and difficulty. The Georgia Milestones Assessment System (Georgia Milestones) is a comprehensive summative assessment program that spans from 3rd grade through high school. Georgia Milestones measures how well students have learned the knowledge and skills outlined in the state-adopted content standards in English language arts (ELA), mathematics, science, and social studies. The Colorado Measures of Academic Success (CMAS) is Colorado’s standards-based assessment. The English Language Arts/Literacy (ELA) is a mandatory state assessment administered at the end of each school year between the months of March and May. The State of Texas Assessments of Academic Readiness (STAAR) is the testing program for students in Texas public schools. STAAR Reading is the assessment used to determine whether students are successful in meeting the reading standards of their current grade and able to make academic progress from year to year. Concurrent validity Gray Oral Reading Test-4 (GORT-4) is a standardized assessment that helps identify school-age children who are below their peers in oral reading proficiency, accuracy, fluency and comprehension. It diagnoses specific reading strengths and weaknesses, and document student reading growth as a result of special intervention. It is one of the most widely used measures of oral reading fluency and comprehension in the United States. The Woodcock–Johnson Tests of Achievement (WJ-III) is a standardized achievement battery first developed in 1977 by Richard Woodcock and Mary E. Bonner Johnson. It is a comprehensive instrument that may be administered to children from age two to the oldest adults (with norms utilizing individuals in their 90s). Wechsler Individual Achievement Test-II (WIAT-II; Wechsler, 2005) it a standardized test. It assesses the academic achievement of children, adolescents, college students and adults, age 4 through 85. The test enables the assessment of a broad range of academics skills or only a particular area of need. The WIAT-II is a revision of the original WIAT (The Psychological Corporation), and includes additional measures. There are four basic scales: reading, math, writing, and oral language.
- *Describe the sample(s), including size and characteristics, for each validity analysis conducted.
- Predictive validity KAP-ELA: sample is derived from urban school districts in the state of Kansas. Sample size ranges from n=1,031 to 1,365. SS_ELA: sample is derived from urban school districts in the state of Georgia. Sample size ranges from n=185 to 365. CMAS: sample is derived from urban school districts in the state of Colorado. Sample size ranges from n=37 to 3,877. STAAR: sample is derived from urban school districts in the northeast area of the state of Texas. Sample size ranges from n=3,877 to 2,647. Samples have different background and knowledge. Concurrent validity The GORT-4, WJ-III, and WIAT-II sample is derived from two large Texas independent school districts. Sample size ranges from n=86 to 138. Samples have different background and knowledge across all performance levels.
- *Describe the analysis procedures for each reported type of validity.
- Predictive validity KAP-ELA: sample is derived from urban school districts in the state of Kansas. Sample size ranges from n=1,031 to 1,365. SS_ELA: sample is derived from urban school districts in the state of Georgia. Sample size ranges from n=185 to 365. CMAS: sample is derived from urban school districts in the state of Colorado. Sample size ranges from n=37 to 3,877. STAAR: sample is derived from urban school districts in the northeast area of the state of Texas. Sample size ranges from n=3,877 to 2,647. Samples have different background and knowledge. Concurrent validity The GORT-4, WJ-III, and WIAT-II sample is derived from two large Texas independent school districts. Sample size ranges from n=86 to 138. Samples have different background and knowledge across all performance levels.
*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:
- Yes
- Provide citations for additional published studies.
- Mathes, P. (2016). Istation’s Indicators of Progress (ISIP) Advanced Reading: Technical Report. Retrieved from https://www.istation.com/Content/downloads/studies/ar_technical_report.pdf
- Describe the degree to which the provided data support the validity of the tool.
- Predictive validity: the state tests are used for our predictive validity. Concurrent validity: the standardized tests are used for our concurrent validity.
- Do you have validity data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?
- Yes
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:
- Provide citations for additional published studies.
Bias Analysis
Grade |
Grade 4
|
Grade 5
|
Grade 6
|
Grade 7
|
Grade 8
|
---|---|---|---|---|---|
Rating | Yes | Yes | Yes | Yes | Yes |
- 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.
- Yes
- If yes,
- a. Describe the method used to determine the presence or absence of bias:
- Differential Item Functioning (DIF) analysis was conducted by grade level (4 - 8) using logistic regression DIF detection analysis by difR package in R software.
- b. Describe the subgroups for which bias analyses were conducted:
- Four DIF factors were investigated: socioeconomic status, gender, race/ethnicity, and special education students.
- 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.
- Using Zumbo & Thomas (ZT) DIF criterion, results showed 97% displayed as A item (negligible or non-significant DIF effect), 2% displayed as B item (slightly to moderate DIF effect), and only 1% displayed as C item (moderate to large DIF effect) across grade level.
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.