FAST™
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:
- 2013
- info@fastbridge.org
- 520 Nicollet Mall, Suite 910, Minneapolis, MN 55402
- 6122542534
- www.fastbridge.org
- Initial Cost:
- $7.00 per student
- Replacement Cost:
- $7.00 per student per year
- Included in Cost:
- FAST™ assessments are accessed through an annual subscription offered by FastBridge Learning, priced on a “per student assessed” model. The subscription rate for school year 2017–18 is $7.00 per student. There are no additional fixed costs. FAST subscriptions are all inclusive providing access to: all FAST reading and math assessments for universal screening, progress monitoring and diagnostic purposes including Computer Adaptive Testing and Curriculum-Based Measurement; Behavior and Developmental Milestones assessment tools; the FAST data management and reporting system; embedded online system training for staff; and basic implementation and user support. In addition to the online training modules embedded within the FAST application, FastBridge Learning offers onsite training options. One, two, and three day packages are available. Packages are determined by implementation size and which FAST assessments (e.g., reading, math, and/or behavior) a district intends to use: 1-day package: $3,000.00; 2-day package: $6,000.00; 3-day package: $9,000.00. Any onsite training purchase also includes a complimentary online Admin/Manager training session (2 hours) for users who will be designated as District Managers and/or School Managers in FAST. Additionally, FastBridge offers web-based consultation and training delivered by certified FAST trainers. The web-based consultation and training rate is $200.00/hour.
- The FAST™ application is a fully cloud-based system, and therefore computer and Internet access are required for full use of the application. Teachers will require less than one hour of training on the administration of the assessment. A paraprofessional can administer the assessment as a Group Proctor in the FAST™ application. The application allows for the following accommodations to support accessibility for culturally and linguistically diverse populations: o Enlarged and printed paper materials are available upon request. o Extended time in untimed portions of earlyMath. o Extra breaks as needed. o Preferential seating and use of quiet space. o Proxy responses. o Use of scratch paper. o As part of item development, all items were reviewed for bias and fairness.
- 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 FAST™ application is a fully cloud-based system, and therefore computer and Internet access are required for full use of the application. Teachers will require less than one hour of training on the administration of the assessment. A paraprofessional can administer the assessment as a Group Proctor in the FAST™ application. The application allows for the following accommodations to support accessibility for culturally and linguistically diverse populations: o Enlarged and printed paper materials are available upon request. o Extended time in untimed portions of earlyMath. o Extra breaks as needed. o Preferential seating and use of quiet space. o Proxy responses. o Use of scratch paper. o As part of item development, all items were reviewed for bias and fairness.
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.
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?
- September, December, and May
- 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.
- Each FAST™ earlyMath subtest produces a raw score. The primary score for each subtest is the number of items correct and/or the number of items correct per minute. These raw scores are used to generate percentile ranks. The best estimate of students’ early mathematics skills is the FAST™ earlyMath composite score. The composite score consists of multiple subtest scores administered during a universal screening period. The FAST™ earlyMath composite scores were developed as optimal predictors of spring broad math achievement in Kindergarten and First Grade. A select set of individual subtest scores were weighted to optimize the predictive relationship between FAST™ earlyMath and broad math achievement scores. Subtests were selected to assess skill in all three domains of early numeracy (i.e., Number, Relations, and Operations) in each screening period. Consistent with theory and evidence, the subtests were selected to emphasize the Number domain in Kindergarten and Operations in First Grade. The individual subtest scores were weighted to optimize the predictive relationship between FAST™ earlyMath and broad math achievement. The weighting is specific to each season. It is important to emphasize that the weighting is influenced by the possible score range, as well as the value of the skill. For example, Number Identification is an important skill with a score range of 0 to 60 (or more) numbers per minute. This represents a broad range of possible scores with benchmark scores that are fairly high (e.g., benchmarks for fall, winter, and spring might be 10, 23, and 35, respectively). In contrast, Match Quantity has a score range from 0 to 12 and benchmarks are relatively low in value (e.g., benchmarks might be 7, 10 and 12, respectively). As a result of both the score range and the relative value of Match Quantity to overall early math performance, the subtest score is more heavily weighted in the composite score.
- 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.
- 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.
Technical Standards
Classification Accuracy & Cross-Validation Summary
Grade |
Kindergarten
|
Grade 1
|
---|---|---|
Classification Accuracy Fall |
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Classification Accuracy Winter |
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Classification Accuracy Spring |
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GMADE (Group Mathematics 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 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.
- 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.
Classification Accuracy - Spring
Evidence | Kindergarten | Grade 1 |
---|---|---|
Criterion measure | GMADE (Group Mathematics Assessment and Diagnostic Evaluation) | GMADE (Group Mathematics Assessment and Diagnostic Evaluation) |
Cut Points - Percentile rank on criterion measure | 15 | 15 |
Cut Points - Performance score on criterion measure | 54.00 | 21.00 |
Cut Points - Corresponding performance score (numeric) on screener measure | ||
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) | 0.89 | 0.93 |
AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.84 | 0.89 |
AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.94 | 0.97 |
Statistics | Kindergarten | Grade 1 |
---|---|---|
Base Rate | ||
Overall Classification Rate | ||
Sensitivity | ||
Specificity | ||
False Positive Rate | ||
False Negative Rate | ||
Positive Predictive Power | ||
Negative Predictive Power |
Sample | Kindergarten | Grade 1 |
---|---|---|
Date | ||
Sample Size | ||
Geographic Representation | East North Central (IL, IN, WI) Middle Atlantic (PA) Mountain (CO, MT) New England (MA, VT) Pacific (OR) West North Central (IA) |
East North Central (IN) Middle Atlantic (NY) New England (MA, VT) West North Central (IA, 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 |
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- *Offer a justification for each type of reliability reported, given the type and purpose of the tool.
- The first type of reliability evidence we present is test-retest reliability. Test-retest reliability assesses the consistency in FAST™ earlyMath composite scores over a 2-3 week period of time. The second type of reliability evidence we present is internal consistency reliability.
- *Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
- Approximately 80 students in first grade. Students came from Minnesota. Internal consistency reliability of the FASTTM earlyMath Composite was computed based on the 2017-2018 norming sample.
- *Describe the analysis procedures for each reported type of reliability.
- Test-retest reliability coefficients were estimated by calculating the median percent agreement between two teachers scores for each student. Confidence intervals represent 95% confidence intervals. Internal consistency reliability coefficients for the FASTTM earlyMath Composite were calculated following Feldt and Brennan (1989), where the reliability coefficient of a composite is a function of the subtest reliabilities, the subtest variances, and the correlations between the subtests. The coefficients below are the median coefficient within a grade level across screening periods.
*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 |
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- *Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
- 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.
- *Describe the sample(s), including size and characteristics, for each validity analysis conducted.
- Concurrent and predictive analyses with GMADE were conducted on a sample of students from Minnesota. There were 305 students in grades K-1.
- *Describe the analysis procedures for each reported type of validity.
- Validity coefficients were calculated by computing Pearson product moment correlations between FAST™ earlyMath 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)?
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 |
Kindergarten
|
Grade 1
|
---|---|---|
Rating | Not Provided | Not Provided |
- 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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