FastBridge
earlyReading Composite
Summary
FastBridge earlyReading is a brief, reliable, and valid assessment for universal screening up to five tmies per year and weekly progress monitoring used with students in preKindergarten through Grade 1. The earlyReading composite is comprised of four very brief assessments (about 1-2 minutes each). The set of assessments used in the composite varies somewhat across seasons within a grade to best reflect the typical developmental reading progress of students and reliably assess risk. Each individual assessment measures a specific foundational reading skill that provides data for instructional planning and that research indicates is predictive of future reading success.
- Where to Obtain:
- Renaissance Learning
- answers@renaissance.com
- Renaissance Learning, PO Box 8036, Wisconsin Rapids, WI 54495
- (800) 338-4204
- http://www.renaissance.com
- Initial Cost:
- $8.00 per student
- Replacement Cost:
- $8.00 per student per year
- Included in Cost:
- The FastBridge system is provided to customers through an annual subscription that is priced on a per student basis. The subscription rate for school year 2022–23 is $8.00 per student. FastBridge subscriptions are all inclusive providing access to all FastBridge reading, math, and behavior assessments, the data management and reporting system, embedded online training, and client support. The academic assessment suite includes adaptive assessments for reading and math screening as well as curriculum-based measurement for universal screening, progress monitoring and skills diagnostics for K – 12. The behavior suite includes screeners completed by both teachers (K-12) and students (2-12) and a direct behavior rating system for progress monitoring for K – 12. In addition to the online training modules embedded within the FastBridge system, onsite and online training options are also offered. All day-long sessions include 6 hours of content. All sessions are capped at a maximum of 30 participants in order to provide a high-quality learning experience. Concurrent sessions of 30 participants are available. The costs are as follows: 1 Day Onsite is $3250 with a 30-participant maximum; 1 Day Online (three, 2-hour sessions) is $1500 with a 30-participant maximum; 2-hour Online Module is $500 with a 30-participant maximum. Training packages include beginner and advanced levels as well as individual online sessions on specific topics. FastBridge recommends that all new users purchase the 2-day FAST Essentials beginner package. This option includes one day on universal screening and a second day on progress monitoring. Advanced options for FastBridge training include day-long FAST Focus sessions, provided either onsite or online and cover topics such as leader reports, data-based decision making, and using FastBridge with special populations. Finally, single-topic sessions selected from the FastBridge module library are available for 2-hour online webinars. FastBridge trainings are provided by highly trained veteran educators who are expert with not only FastBridge features but also how to use the data to support student leaning.
- The FastBridge system is a fully cloud-based system, and therefore computer and Internet access are required for full use of the application. Some of the assessments are computer-administered and others are teacher-administered. A paraprofessional can administer the assessment as a Group Proctor in the FastBridge system. There are embedded online training courses included in the platform and these include certification tests. The courses require between 15 and 30 minutes each to complete. The number of assessments that a teacher needs to administer varies by grade level and so total training time will vary. The system allows for the following accommodations to support accessibility for students with documented disabilities: • Text magnification • Sound amplification • Enlarged and printed paper materials are available upon request • Extended time on selected assessments (FastBridge adaptive assessments are untimed, thus, students take as much time as needed) • Extra breaks (the adaptive assessments can be paused for breaks) • Preferential seating • Small group or individual sessions • Proxy responses • Scratch paper on selected subtests
- Training Requirements:
- Less than 1 hour of training
- Qualified Administrators:
- No minimum qualifications specified.
- Access to Technical Support:
- Users have access to professional development technicians, as well as ongoing technical support.
- Assessment Format:
-
- One-to-one
- Scoring Time:
-
- Scoring is automatic
- Scores Generated:
-
- Raw score
- Percentile score
- Developmental benchmarks
- Composite scores
- Subscale/subtest scores
- Administration Time:
-
- 7 minutes per student
- Scoring Method:
-
- Automatically (computer-scored)
- Technology Requirements:
-
- Computer or tablet
- Internet connection
- Accommodations:
- The FastBridge system is a fully cloud-based system, and therefore computer and Internet access are required for full use of the application. Some of the assessments are computer-administered and others are teacher-administered. A paraprofessional can administer the assessment as a Group Proctor in the FastBridge system. There are embedded online training courses included in the platform and these include certification tests. The courses require between 15 and 30 minutes each to complete. The number of assessments that a teacher needs to administer varies by grade level and so total training time will vary. The system allows for the following accommodations to support accessibility for students with documented disabilities: • Text magnification • Sound amplification • Enlarged and printed paper materials are available upon request • Extended time on selected assessments (FastBridge adaptive assessments are untimed, thus, students take as much time as needed) • Extra breaks (the adaptive assessments can be paused for breaks) • Preferential seating • Small group or individual sessions • Proxy responses • Scratch paper on selected subtests
Descriptive Information
- Please provide a description of your tool:
- FastBridge earlyReading is a brief, reliable, and valid assessment for universal screening up to five tmies per year and weekly progress monitoring used with students in preKindergarten through Grade 1. The earlyReading composite is comprised of four very brief assessments (about 1-2 minutes each). The set of assessments used in the composite varies somewhat across seasons within a grade to best reflect the typical developmental reading progress of students and reliably assess risk. Each individual assessment measures a specific foundational reading skill that provides data for instructional planning and that research indicates is predictive of future reading success.
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?
- August - November, December - mid-March, Mid-March - July
- 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:
- Less than 1 hour of training
- 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?
- No
- 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:
- Users have access to professional development technicians, as well as ongoing technical support.
Scoring
- Do you provide basis for calculating performance level scores?
-
Yes
- Does your tool include decision rules?
- 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.
- For screening, students complete four brief assessments. Each earlyReading assessment produces a total correct or corrects per minute score. These scores are combined using a two-stage weighting procedure to generate the earlyReading composite score, the primary screening score. The weighting procedure was designed to optimize prediction of end of grade broad reading achievement, in Kindergarten and Grade 1. The weighting also results in a scale that enables direct comparison of composite scores across season within grade. The composite score in the fall of Kindergarten includes: Concepts of Print, Onset Sounds, Letter Sounds, and Letter Naming. The composite score for winter includes Onset Sounds, Letter Sounds, Word Segmenting and Nonsense Words. The composite score for spring includes: Letter Sounds, Word Segmenting, Nonsense Words, and Sight Words (50). The Decodable Words assessment score may be used in place of Nonsense Words for computing any of the composite scores specified. The composite score in the fall of Grade 1 includes: Word Segmenting, Nonsense Words, Sight Words (150), and Sentence Reading. The composite score for winter includes: Word Segmenting, Nonsense Words, Sight Words (150), and CBMreading. The composite score for spring includes: Word Segmenting, Nonsense Words, Sight Words (150), and CBMreading. The Decodable Words assessment score may be used in place of Nonsense Words for computing any of the composite scores specified.
- 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.
- FastBridge earlyReading is an evidence-based assessment suite used to screen and monitor students’ progress in both a unified and skill-based approach in prekindergarten – Grade 1. The earlyReading composite score (as described above) is a combination of scores from four individual assessments. The combination of assessments varies somewhat across seasons and grades. The overall composite score is the primary indicator of reading competence and is compared to research-based, empirically derived performance benchmarks. These benchmarks result in four performance levels: high risk, some risk, low risk, and advanced. For students at risk, the individual assessments provide input for additional risk assessment and instructional planning in four domains: concepts of print, phonemic awareness, phonics, and decoding. The set of earlyReading assessments that form the composite also provide input for personalized and classroom instruction plans described in the Screening-to-Intervention (S2i) report. Additional earlyReading assessments not contained in the composite are available for further diagnostic evaluation.
Technical Standards
Classification Accuracy & Cross-Validation Summary
Grade |
Kindergarten
|
Grade 1
|
---|---|---|
Classification Accuracy Fall | ||
Classification Accuracy Winter | ||
Classification Accuracy Spring |
GRADE (Group Reading Assessment and Diagnostic Evaluation)
Classification Accuracy
- Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
- The GRADE (Group Reading Assessment and Diagnostic Evaluation) is a diagnostic reading test that that determines what developmental skills PreK-12 students have mastered and where students need instruction or intervention. The GRADE is a paper and pencil test that can take 50-90 minutes to complete. The GRADE comprises two levels with 10 parallel forms per level. Grade-based norms are provided fall and spring.
- 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).
- Cut points were selected by optimizing sensitivity, and then balancing sensitivity with specificity using methods presented in Silberglitt and Hintze (2005). The cut points were derived for the 20th percentile
- 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?
-
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.
Star Early Literacy
Classification Accuracy
- Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
- Renaissance Star Early Literacy is a comprehensive computer adaptive assessment for PreK-3 students that helps teachers identify child levels of literacy development. The assessment measures a child’s command of 41 different sets of skills in ten key literacy sub-domains. Each assessment takes about 15 minutes. Star Early Literacy provides teachers with the immediate feedback needed to monitor skill development, focus teaching or identify children who need special attention. Star Early Literacy was developed completely, independent from Fastbridge earlyReading; Fastbridge was developed at the University of Minnesota and Star was developed at Renaissance Learning. Star Early Literacy serves as a good criterion measure because, like Fastbridge earlyReading, it assesses broad reading achievement using content aligned to state and national learning standards and has been highly rated by NCII as a reliable and valid measure of reading achievement.
- 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.
- earlyReading assessments were administered for screening during the fall and winter seasons. The grade 1 Star Early Literacy spring score was used as the criterion measure for the predictive (fall and winter) validity measure. Kindergarten used concurrent measures to examine classification accuracy because sufficient spring samples were lacking. Kindergarten Star Early Literacy fall scores served as the criterion measure for Kindergarten Fastbridge earlyReading fall scores, while Kindergarten winter scores worked as the criterion measure for Kindergarten Fastbridge earlyReading scores.
- 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).
- Cut points were selected by optimizing sensitivity, and then balancing sensitivity with specificity using methods presented in Silberglitt and Hintze (2005). The 11th national percentile is the criterion measure cut point for grade 1, while the 17th percentile is the cut point for kindergarten. The cut points between the 10th and 20th national percentile contrasts high risk students against some and low risk students from the sample.
- 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.
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 - Fall
Evidence | Kindergarten | Grade 1 |
---|---|---|
Criterion measure | Star Early Literacy | Star Early Literacy |
Cut Points - Percentile rank on criterion measure | 17 | 11 |
Cut Points - Performance score on criterion measure | ||
Cut Points - Corresponding performance score (numeric) on screener measure | 30 | 26 |
Classification Data - True Positive (a) | 33 | 103 |
Classification Data - False Positive (b) | 18 | 89 |
Classification Data - False Negative (c) | 9 | 13 |
Classification Data - True Negative (d) | 58 | 217 |
Area Under the Curve (AUC) | 0.84 | 0.86 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.77 | 0.82 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.91 | 0.90 |
Statistics | Kindergarten | Grade 1 |
---|---|---|
Base Rate | 0.36 | 0.27 |
Overall Classification Rate | 0.77 | 0.76 |
Sensitivity | 0.79 | 0.89 |
Specificity | 0.76 | 0.71 |
False Positive Rate | 0.24 | 0.29 |
False Negative Rate | 0.21 | 0.11 |
Positive Predictive Power | 0.65 | 0.54 |
Negative Predictive Power | 0.87 | 0.94 |
Sample | Kindergarten | Grade 1 |
---|---|---|
Date | 2021-22 | 2021-22 |
Sample Size | 118 | 422 |
Geographic Representation | Pacific (CA) West North Central (MN) |
Pacific (CA) West North Central (MN) |
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 | Kindergarten | Grade 1 |
---|---|---|
Criterion measure | Star Early Literacy | Star Early Literacy |
Cut Points - Percentile rank on criterion measure | 17 | 11 |
Cut Points - Performance score on criterion measure | ||
Cut Points - Corresponding performance score (numeric) on screener measure | 44.5 | 34 |
Classification Data - True Positive (a) | 30 | 96 |
Classification Data - False Positive (b) | 33 | 45 |
Classification Data - False Negative (c) | 5 | 28 |
Classification Data - True Negative (d) | 59 | 200 |
Area Under the Curve (AUC) | 0.79 | 0.85 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.70 | 0.81 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.88 | 0.90 |
Statistics | Kindergarten | Grade 1 |
---|---|---|
Base Rate | 0.28 | 0.34 |
Overall Classification Rate | 0.70 | 0.80 |
Sensitivity | 0.86 | 0.77 |
Specificity | 0.64 | 0.82 |
False Positive Rate | 0.36 | 0.18 |
False Negative Rate | 0.14 | 0.23 |
Positive Predictive Power | 0.48 | 0.68 |
Negative Predictive Power | 0.92 | 0.88 |
Sample | Kindergarten | Grade 1 |
---|---|---|
Date | 2021-22 | 2021-22 |
Sample Size | 127 | 369 |
Geographic Representation | Pacific (CA) West North Central (MN) |
Pacific (CA) West North Central (MN) |
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 | Kindergarten | Grade 1 |
---|---|---|
Criterion measure | GRADE (Group Reading Assessment and Diagnostic Evaluation) | GRADE (Group Reading Assessment and Diagnostic Evaluation) |
Cut Points - Percentile rank on criterion measure | 15 | 15 |
Cut Points - Performance score on criterion measure | 52.00 | 45.00 |
Cut Points - Corresponding performance score (numeric) on screener measure | ||
Classification Data - True Positive (a) | 14 | 8 |
Classification Data - False Positive (b) | 24 | 11 |
Classification Data - False Negative (c) | 2 | 1 |
Classification Data - True Negative (d) | 172 | 104 |
Area Under the Curve (AUC) | 0.95 | 0.99 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.93 | 0.99 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.97 | 1.00 |
Statistics | Kindergarten | Grade 1 |
---|---|---|
Base Rate | 0.08 | 0.07 |
Overall Classification Rate | 0.88 | 0.90 |
Sensitivity | 0.88 | 0.89 |
Specificity | 0.88 | 0.90 |
False Positive Rate | 0.12 | 0.10 |
False Negative Rate | 0.13 | 0.11 |
Positive Predictive Power | 0.37 | 0.42 |
Negative Predictive Power | 0.99 | 0.99 |
Sample | Kindergarten | Grade 1 |
---|---|---|
Date | 2012-13 | 2012-13 |
Sample Size | 212 | 124 |
Geographic Representation | West North Central (MN) | West North Central (MN) |
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 |
Kindergarten
|
Grade 1
|
---|---|---|
Rating |
- *Offer a justification for each type of reliability reported, given the type and purpose of the tool.
- Test-retest reliability assess the consistency of scores from repeated administrations of the same test form as can happen when a test administration is spoiled, and the same form needs to be readministered. Because the FastBridge earlyReading composite score is comprised of four separates assessments some of which are timed and some untimed, a confirmatory factor model-based approach produces an estimate of stability of the composite score from a single administration. This reliability coefficient is analogous to the tau equivalent measurement model.
- *Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
- Test-retest reliability was based on students who completed the FastBridge earlyReading composite twice within 60 days. The sample was distributed across 20 states. The model-based reliability was derived from a national sample of students screened using the FastBridge earlyReading composite in the fall of 2018. The sample consisted of more than 94,000 students in Kindergarten and more than 72,000 in Grade 1 with 51% male, 71% white, 6% African American, 12% Hispanic, 5% Asian and 5% other race/ethnicity.
- *Describe the analysis procedures for each reported type of reliability.
- Test-retest reliability coefficients were estimated from the Pearson correlation between two administrations of the same earlyReading composite test forms. 95% confidence intervals were computed using the z-transformation method. Model-based reliability coefficients were derived from factor loadings using a confirmatory factor model in which the four subtests were regressed onto a single factor model. Reliability is ratio of the sum of the squared factor loadings (true score variance) to the total variance (sum of squared loadings plus error variance).
*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 |
Kindergarten
|
Grade 1
|
---|---|---|
Rating |
- *Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
- The criterion measure for predictive validity analyzed in Kindergarten is the GRADE. The GRADE is a diagnostic reading test that that determines what developmental skills PreK-12 students have mastered and where students need instruction or intervention. The GRADE is a paper and pencil test that can take 50-90 minutes to complete. The GRADE comprises two levels with 10 parallel forms per level. Grade-based norms are provided fall and spring. The criterion measure for concurrent validity analyzed in Kindergarten is Renaissance Star Early Literacy. Renaissance Star Early Literacy is a comprehensive computer adaptive assessment for PreK-3 students that helps teachers identify child levels of literacy development. The assessment measures a child’s command of 41 different sets of skills in ten key literacy sub-domains. Each assessment takes about 15 minutes. Star Early Literacy provides teachers with the immediate feedback needed to monitor skill development, focus teaching or identify children who need special attention. Star Early Literacy was developed completely, independent from Fastbridge earlyReading; Fastbridge was developed at the University of Minnesota and Star was developed at Renaissance Learning. Star Early Literacy serves as a good criterion measure because, like Fastbridge earlyReading, it assesses broad reading achievement using content aligned to state and national learning standards and has been highly rated by NCII as a reliable and valid measure of reading achievement. The criterion measure for both types of validity analyzes (concurrent and predictive) in Grade 1 is the NWEA MAP Growth K-2 reading assessment. MAP Growth K-2 is a computer adaptive test that indicates a student's general reading ability.
- *Describe the sample(s), including size and characteristics, for each validity analysis conducted.
- Predictive analyses in Kindergarten with GRADE were conducted on a sample of 173 students from Minnesota. Concurrent validity for Kindergarten scores with Star Early Literacy was conducted on a sample of students from Minnesota and California. There were 112 Kindergarten students from a single school in California and six Kindergarten students from a single school in Minnesota. Concurrent and predictive analyses in Grade 1 with MAP Growth K-2 were conducted on a sample of 463 and 167 students respectively from four states: MI, WI, MN, and MO.
- *Describe the analysis procedures for each reported type of validity.
- Validity coefficients were calculated by computing Pearson product moment correlations between FastBridge earlyReading Composite and the criterion measure. Confidence intervals represent 95% confidence intervals.
*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.
- 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 |
Kindergarten
|
Grade 1
|
---|---|---|
Rating | 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.
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.