FastBridge
earlyMath Composite

Summary

FAST™ earlyMath is an evidence-based assessment used for universal screening in grades PreK-1 with the option to do so up to five times per year, or for frequent progress monitoring at any grade. Each assessment is designed to be highly efficient and inform instruction. The FAST™ earlyMath assessments are comprised of 14 sub-tests. Of those sub-tests, FastBridge Learning provides recommendations for specific combinations of up to four sub-tests to be given per benchmark period. This composite varies from fall, winter, or spring per grade level to best match math skill development and reliably assess performance. The composite is typically completed in 5-10 minutes per student. The remaining assessments may be used as needed to further evaluate skill deficits. Results help identify student risk while informing instruction.

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:
FAST™ earlyMath is an evidence-based assessment used for universal screening in grades PreK-1 with the option to do so up to five times per year, or for frequent progress monitoring at any grade. Each assessment is designed to be highly efficient and inform instruction. The FAST™ earlyMath assessments are comprised of 14 sub-tests. Of those sub-tests, FastBridge Learning provides recommendations for specific combinations of up to four sub-tests to be given per benchmark period. This composite varies from fall, winter, or spring per grade level to best match math skill development and reliably assess performance. The composite is typically completed in 5-10 minutes per student. The remaining assessments may be used as needed to further evaluate skill deficits. Results help identify student risk while informing instruction.
The tool is intended for use with the following grade(s).
selected Preschool / Pre - kindergarten
selected Kindergarten
selected First grade
not selected Second grade
not selected Third grade
not selected Fourth grade
not selected Fifth grade
not selected Sixth grade
not selected Seventh grade
not selected Eighth grade
not selected Ninth grade
not selected Tenth grade
not selected Eleventh grade
not selected Twelfth grade

The tool is intended for use with the following age(s).
not selected 0-4 years old
selected 5 years old
selected 6 years old
selected 7 years old
not selected 8 years old
not selected 9 years old
not selected 10 years old
not selected 11 years old
not selected 12 years old
not selected 13 years old
not selected 14 years old
not selected 15 years old
not selected 16 years old
not selected 17 years old
not selected 18 years old

The tool is intended for use with the following student populations.
selected Students in general education
selected Students with disabilities
selected English language learners

ACADEMIC ONLY: What skills does the tool screen?

Reading
Phonological processing:
not selected RAN
not selected Memory
not selected Awareness
not selected Letter sound correspondence
not selected Phonics
not selected Structural analysis

Word ID
not selected Accuracy
not selected Speed

Nonword
not selected Accuracy
not selected Speed

Spelling
not selected Accuracy
not selected Speed

Passage
not selected Accuracy
not selected Speed

Reading comprehension:
not selected Multiple choice questions
not selected Cloze
not selected Constructed Response
not selected Retell
not selected Maze
not selected Sentence verification
not selected Other (please describe):


Listening comprehension:
not selected Multiple choice questions
not selected Cloze
not selected Constructed Response
not selected Retell
not selected Maze
not selected Sentence verification
not selected Vocabulary
not selected Expressive
not selected Receptive

Mathematics
Global Indicator of Math Competence
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Early Numeracy
selected Accuracy
selected Speed
selected Multiple Choice
not selected Constructed Response

Mathematics Concepts
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematics Computation
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematic Application
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Fractions/Decimals
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Algebra
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Geometry
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

not selected Other (please describe):

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

Where to obtain:
Email Address
answers@renaissance.com
Address
Renaissance Learning, PO Box 8036, Wisconsin Rapids, WI 54495
Phone Number
(800) 338-4204
Website
http://www.renaissance.com
Initial cost for implementing program:
Cost
$8.00
Unit of cost
student
Replacement cost per unit for subsequent use:
Cost
$8.00
Unit of cost
student
Duration of license
year
Additional cost information:
Describe basic pricing plan and structure of the tool. Provide information on what is included in the published tool, as well as what is not included but required for implementation.
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.
Provide information about special accommodations for students with disabilities.
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

Administration

BEHAVIOR ONLY: What type of administrator is your tool designed for?
not selected General education teacher
not selected Special education teacher
not selected Parent
not selected Child
not selected External observer
not selected Other
If other, please specify:

What is the administration setting?
not selected Direct observation
not selected Rating scale
not selected Checklist
not selected Performance measure
not selected Questionnaire
not selected Direct: Computerized
selected One-to-one
not selected 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)
selected Computer or tablet
selected Internet connection
not selected 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?
selected Individual
not selected Small group   If small group, n=
not selected Large group   If large group, n=
not selected Computer-administered
not selected Other
If other, please specify:

What is the administration time?
Time in minutes
7
per (student/group/other unit)
student

Additional scoring time:
Time in minutes
per (student/group/other unit)

ACADEMIC ONLY: What are the discontinue rules?
not selected No discontinue rules provided
not selected Basals
not selected Ceilings
selected Other
If other, please specify:
Some subtests are timed.


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.
selected 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

How are scores calculated?
not selected Manually (by hand)
selected Automatically (computer-scored)
not selected 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?
not selected Age norms
selected Grade norms
not selected Classwide norms
not selected Schoolwide norms
not selected Stanines
not selected Normal curve equivalents

What types of performance level scores are available?
selected Raw score
not selected Standard score
selected Percentile score
not selected Grade equivalents
not selected IRT-based score
not selected Age equivalents
not selected Stanines
not selected Normal curve equivalents
selected Developmental benchmarks
not selected Developmental cut points
not selected Equated
not selected Probability
not selected Lexile score
not selected Error analysis
selected Composite scores
selected Subscale/subtest scores
not selected Other
If other, please specify:

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.
For screening, students complete three brief assessments. Each FastBridge earlyMath assessment produces a total correct or corrects per minute score. These scores are combined using a two-stage weighting procedure to generate the FastBridge earlyMath composite score, the primary screening score. The weighting procedure was designed to optimize prediction of end of grade broad math 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: Match Quantity, Number Sequence, and Numeral ID. The composite score for winter includes: Decomposing, Number Sequence, and Numeral ID. The composite score for spring includes: Decomposing, Number Sequence, and Numeral ID. The composite score in the fall of Grade 1 includes: Decomposing, Number Sequence, and Numeral ID. The composite score for winter includes: Decomposing, Number Sequence, and Place Value. The composite score for spring includes: Decomposing, Place Value, and Story Problems. NOTE: Decomposing, Number Sequence, and Numeral ID in Grade 1 use larger numbers than the Kindergarten version to reflect grade level expectations.
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 earlyMath 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 earlyMath composite score (as described above) is a combination of scores from three individual assessments. The combination of assessments varies somewhat across seasons and grades. The overall composite score is the primary indicator of math 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 FastBridge earlyMath assessments that form the composite also provide input for personalized and classroom instruction plans described in the Screening-to-Intervention (S2i) report. Additional FastBridge earlyMath 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 Unconvincing evidence Convincing evidence
Classification Accuracy Winter Partially convincing evidence Partially convincing evidence
Classification Accuracy Spring Convincing evidence Convincing evidence
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available

GMADE (Group Mathematics Assessment and Diagnostic Evaluation)

Classification Accuracy

Select time of year
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
The GMADE (Group Mathematics Assessment and Diagnostic Evaluation) is a diagnostic math test that that determines what developmental skills PreK-12 students have mastered and where students need instruction or intervention. The GMADE is a paper and pencil test that can take 50-90 minutes to complete. The GMADE comprises two levels with 10 parallel forms per level. Grade-based norms are provided fall and spring.
Do the classification accuracy analyses examine concurrent and/or predictive classification?

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,
Select time of year.
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
Do the cross-validation analyses examine concurrent and/or predictive classification?

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.

NWEA MAP Growth

Classification Accuracy

Select time of year
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
The NWEA MAP Growth assessment in mathematics is a computer-adaptive test administered in the fall, winter, and spring for universal screening. The content includes the following domains with 6 - 8 items per domain: operations and algebraic thinking, number and operations, measurement and data, and geometry. Students complete 43 items.
Do the classification accuracy analyses examine concurrent and/or predictive classification?

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).
The 15th national percentile on MAP Growth was used to divide the sample into a high risk and a moderate to low risk group. The earlyMath composite cut-points were derived by optimizing specificity and sensitivity using Youden’s J index. The analyses were repeated for each grade and season.
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.
The data were derived from universal screening at each grade level and season in districts implementing MTSS. Although, the information regarding the specific intervention was not available for these analyses, most students scoring in the high risk range were assigned to some form of intensive intervention.

Cross-Validation

Has a cross-validation study been conducted?
No
If yes,
Select time of year.
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
Do the cross-validation analyses examine concurrent and/or predictive classification?

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 Math

Classification Accuracy

Select time of year
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
Renaissance Star Math is a computer adaptive math assessment designed to monitor student growth and mastery of concepts in numeracy, algebra, geometry, and statistics in grades PreK-12. Star Math serves three purposes. First, it provides educators with quick and accurate estimates of students’ instructional math levels. Second, it assesses math levels relative to national norms. Third, it provides the means for tracking growth in a consistent manner longitudinally for all students. This is especially helpful to school- and district-level administrators. Star Math was developed completely, independent from Fastbridge earlyMath; Fastbridge was developed at the University of Minnesota and Star was developed at Renaissance Learning. Star Math serves as a good criterion measure because, like Fastbridge earlyMath, it assesses broad math achievement using content aligned to state and national learning standards and has been highly rated by NCII as a reliable and valid measure of math achievement.
Do the classification accuracy analyses examine concurrent and/or predictive classification?

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.
earlyMath assessments were administered for screening during the fall, winter, and spring seasons. The Star Math spring score was used as the criterion measure for both predictive (fall and winter) and concurrent (spring only) validity measures.
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 criterion measure cut point was the 20th national percentile. The cut point at the 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,
Select time of year.
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
Do the cross-validation analyses examine concurrent and/or predictive classification?

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 NWEA MAP Growth Star Math
Cut Points - Percentile rank on criterion measure 15 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 30 7
Classification Data - True Positive (a) 17 57
Classification Data - False Positive (b) 66 57
Classification Data - False Negative (c) 6 12
Classification Data - True Negative (d) 170 271
Area Under the Curve (AUC) 0.80 0.88
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.68 0.84
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.91 0.91
Statistics Kindergarten Grade 1
Base Rate 0.09 0.17
Overall Classification Rate 0.72 0.83
Sensitivity 0.74 0.83
Specificity 0.72 0.83
False Positive Rate 0.28 0.17
False Negative Rate 0.26 0.17
Positive Predictive Power 0.20 0.50
Negative Predictive Power 0.97 0.96
Sample Kindergarten Grade 1
Date 2018-19 2021-22
Sample Size 259 397
Geographic Representation East North Central (MI) 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 NWEA MAP Growth Star Math
Cut Points - Percentile rank on criterion measure 15 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 52 38
Classification Data - True Positive (a) 29 59
Classification Data - False Positive (b) 54 60
Classification Data - False Negative (c) 9 10
Classification Data - True Negative (d) 174 219
Area Under the Curve (AUC) 0.87 0.89
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.81 0.84
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.93 0.93
Statistics Kindergarten Grade 1
Base Rate 0.14 0.20
Overall Classification Rate 0.76 0.80
Sensitivity 0.76 0.86
Specificity 0.76 0.78
False Positive Rate 0.24 0.22
False Negative Rate 0.24 0.14
Positive Predictive Power 0.35 0.50
Negative Predictive Power 0.95 0.96
Sample Kindergarten Grade 1
Date 2018-19 2021-22
Sample Size 266 348
Geographic Representation East North Central (MI) 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 Grade 1
Criterion measure NWEA MAP Growth NWEA MAP Growth Star Math
Cut Points - Percentile rank on criterion measure 15 15 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 62 61 51.5
Classification Data - True Positive (a) 21 39 57
Classification Data - False Positive (b) 27 64 43
Classification Data - False Negative (c) 5 14 12
Classification Data - True Negative (d) 194 207 261
Area Under the Curve (AUC) 0.88 0.86 0.90
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.80 0.80 0.85
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.96 0.91 0.94
Statistics Kindergarten Grade 1 Grade 1
Base Rate 0.11 0.16 0.18
Overall Classification Rate 0.87 0.76 0.85
Sensitivity 0.81 0.74 0.83
Specificity 0.88 0.76 0.86
False Positive Rate 0.12 0.24 0.14
False Negative Rate 0.19 0.26 0.17
Positive Predictive Power 0.44 0.38 0.57
Negative Predictive Power 0.97 0.94 0.96
Sample Kindergarten Grade 1 Grade 1
Date 2018-19 2018-19 2021-22
Sample Size 247 324 373
Geographic Representation East North Central (MI) East North Central (MI) 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      

Reliability

Grade Kindergarten
Grade 1
Rating Convincing evidence Convincing evidence
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available
*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 earlyMath 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 earlyMath composite in the fall of 2017. The sample consisted of more than 46,000 students in Kindergarten and more than 43,000 in Grade 1 with 52% male, 66% white, 6% African American, 12% Hispanic, 9% Asian and 7% 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 earlyMath 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). 95% confidence intervals were computed using the z-transformation method.

*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)?

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 Kindergarten
Grade 1
Rating Convincing evidence Convincing evidence
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available
*Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
The NWEA MAP Growth K-2 assessment in mathematics is a computer-adaptive test administered in the fall, winter, and spring for universal screening. The content includes the following domains with 6 - 8 items per domain: operations and algebraic thinking, number and operations, measurement and data, and geometry. Students complete 43 items.
*Describe the sample(s), including size and characteristics, for each validity analysis conducted.
The sample was comprised of students from several school districts in Michigan. For both grades a total of about 300 students completed both assessments.
*Describe the analysis procedures for each reported type of validity.
Validity coefficients were calculated by computing Pearson product moment correlations between FastBridge earlyMath Composite scale score and MAP Growth RIT score. Predictive validity was based on winter earlyMath scores and spring MAP Growth scores. 95% confidence intervals were computed using the z-transformation method.

*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

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