FAST™
Adaptive Reading (aReading)
Summary
FAST™ Adaptive Reading (FAST™ aReading) is a fully automated computer adaptive measure of broad reading ability that is individualized for each student. FAST™ aReading provides a useful estimate of broad reading achievement from kindergarten through twelfth grade. The assessment is online, group administered in 15-30 minutes. The questions and response format used in FAST aReading is substantially similar to many statewide, standardized assessments and assesses Common Core State Standards skills and domains including concepts of print, phonological awareness, phonics, vocabulary, comprehension, orthology, and morphology. Browser-based software adapts and individualizes the assessment for each child so that it essentially functions at the child’s developmental and skill level. The adaptive nature of the test makes it more efficient and more precise than paper-and-pencil assessments.
- Where to Obtain:
- Theodore J. Christ & Colleagues, LLC/FastBridge Learning, LLC
- info@fastbridge.org
- 520 Nicollet Mall, Suite 910, Minneapolis, MN 55402
- 612-254-2534
- 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 Text magnification. o Sound amplification. o Enlarged and printed paper materials are available upon request. o Students with differing needs or disabilities may take computer-adaptive tests such as aReading via a tablet-type device to facilitate screen optimization, magnification, sound amplification, and standard accommodations. o Extended time in aReading and untimed portions of earlyReading. 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:
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- Direct: Computerized
- One-to-one
- Scoring Time:
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- Scoring is automatic
- Scores Generated:
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- Percentile score
- IRT-based score
- Developmental benchmarks
- Administration Time:
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- 23 minutes per student
- Scoring Method:
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- Automatically (computer-scored)
- Technology Requirements:
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- 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 Text magnification. o Sound amplification. o Enlarged and printed paper materials are available upon request. o Students with differing needs or disabilities may take computer-adaptive tests such as aReading via a tablet-type device to facilitate screen optimization, magnification, sound amplification, and standard accommodations. o Extended time in aReading and untimed portions of earlyReading. 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™ Adaptive Reading (FAST™ aReading) is a fully automated computer adaptive measure of broad reading ability that is individualized for each student. FAST™ aReading provides a useful estimate of broad reading achievement from kindergarten through twelfth grade. The assessment is online, group administered in 15-30 minutes. The questions and response format used in FAST aReading is substantially similar to many statewide, standardized assessments and assesses Common Core State Standards skills and domains including concepts of print, phonological awareness, phonics, vocabulary, comprehension, orthology, and morphology. Browser-based software adapts and individualizes the assessment for each child so that it essentially functions at the child’s developmental and skill level. The adaptive nature of the test makes it more efficient and more precise than paper-and-pencil assessments.
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?
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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.
- FAST™ aReading is a computer-adaptive test (CAT), and therefore yields scores based on an IRT logit scale. This type of scale is not useful to most school professionals; in addition, it is difficult to interpret scores on a scale for which everything below the mean value yields a negative number. Therefore, it was necessary to create a FAST aReading scale more similar to existing educational measures. The FAST aReading scale yields scores that are transformed from logits using the following formula: y = 500 + (50*Logit Score) where y is the new FAST aReading scaled score, and Logit Score is the initial FAST aReading theta estimate. Scores were scaled with a lower bound of 350 and a higher bound of 650. The mean value is 500 and the standard deviation is 50.
- 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 aReading is a computer-adaptive measure of broad reading ability that is individualized for each student. FAST aReading provides a useful estimate of broad reading achievement from Kindergarten through twelfth grade. The question-and- response format used in FAST aReading is similar to many statewide, standardized assessments. Browser-based software adapts and individualizes the assessment for each child so that it essentially functions at the child’s developmental and skill level. The adaptive nature of the test makes it more efficient and more precise than paper-and-pencil assessments. The design of FAST aReading has a strong foundation in both research and theory. During the early phases of student reading development, the component processes of reading are most predictive of future reading success (Stanovich, 1981, 1984, 1990; Vellutino & Scanlon, 1987, 1991; Vellutino, Scanlon, Small, & Tanzman, 1991). Indeed, reading disabilities are most frequently associated with deficits in accurate and efficient word identification. Those skills are necessary but not sufficient for reading to occur. After all, reading is comprehending and acquiring information through print. It is not merely rapid word identification or the “barking at words” (Samuels, 2007). As such, a unified reading construct is necessary to enhance the validity of reading assessment and inform balanced instruction throughout the elementary grades. FAST aReading was developed based on a skills hierarchy and unified reading construct (presented later in the technical manual). Each FAST aReading assessment is individualized by the software and, as a result, the information and precision of measurement is optimized regardless of whether a student functions at, above, or significantly below grade level. FAST aReading is intended for use from Kindergarten through twelfth grades for screening. The FAST aReading item bank consists of approximately 2000 items that target the reading domains described in the previous section. Items developed for Kindergarten through grade 5 target Concepts of Print, Phonological Awareness, Phonics, Vocabulary, and Comprehension. Items developed for middle and high school grade levels target Orthography, Morphology, Vocabulary, and Comprehension. Please note, however, that the importance and emphasis on each reading domain will vary across children. FAST aReading item development followed the process and standards presented by Schmeiser and Welch (2006) in the fourth edition of Educational Measurement (Brennan, 2006). Research assistants, teachers from each grade level (1st through 12th), and content experts in the area of reading served as both item writers and reviewers for those items at the Kindergarten through 5th grade level. Items for grades 6 through 12 were constructed to reflect the Common Core State Standards’ (National Governors Association Center for Best Practices & Council of Chief State School Officers, 2010) specifications for various skills of interest, as well as the National Assessment of Educational Progress’ (NAEP, 2011) guidelines for reading assessment items. After items were written at all grade levels, they were reviewed for feasibility, construct relevance, and content balance. A stratified procedure was used to recruit a diverse set of item writers from urban, suburban and rural areas. The item writers wrote, reviewed, and edited assessment materials. Item writing for FAST aReading was a multi-year, collaborative, and iterative process. First the literature on item writing guidelines used when developing assessments was reviewed. Next, the literature on multiple-choice item writing was reviewed. Once the literature was reviewed, the guidelines were applied to FAST aReading to examine relevance and utility. Extensive guidelines and practice were provided to item writers and the process outlined above was followed.
Technical Standards
Classification Accuracy & Cross-Validation Summary
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Legend
Convincing evidence
Partially convincing evidence
Unconvincing evidenceData unavailabledDisaggregated data available
Gates MacGinitie Reading Tests-4th Edition (GMRT-4th.)
Classification Accuracy
- Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
- The criterion measure for the first type of validity analysis (predictive validity) is the Gates MacGinitie Reading Tests-4th Edition (GMRT-4th). The GMRT-4th is a norm-referenced, group administered measure of reading achievement distributed by Riverside Publishing Company. It is designed to provide guidance in planning instruction and intervention and is typically used as a diagnostic tool for general reading achievement, which makes it an appropriate criterion for FAST aReading. Like FAST aReading, the GMRT-4th was normed with students in the pre-reading stages through high school levels. The GMRT-4th was also selected because of its strong criterion validity. Correlations between the GMRT composite score and comprehension and vocabulary subtests of the Iowa Test of Basic Skills and GMRT composite scores across grades is high (.76 and .78 respectively; Morsy, Kieffer, & Snow, 2010). A similar pattern of results were observed between the GMRT and subscales of the California Tests of Basic Skills (.84 and .81 respectively; Morsy et al., 2010). GMRT scores also correlate highly with Comprehensive Tests of Basic Skills vocabulary, comprehension, and composite scores (.72, .79, and. 83 respectively; Morsy et al., 2010). Further, the correlation between GMRT composite scores and reading scores on the Basic Academic Skills Samples were strong as well (.79; Jenkins & Jewell, 1992).
- 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?
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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?
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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 | Grade 1 | Grade 2 | Grade 3 | Grade 4 | Grade 5 |
|---|---|---|---|---|---|
| Criterion measure | Gates MacGinitie Reading Tests-4th Edition (GMRT-4th.) | Gates MacGinitie Reading Tests-4th Edition (GMRT-4th.) | Gates MacGinitie Reading Tests-4th Edition (GMRT-4th.) | Gates MacGinitie Reading Tests-4th Edition (GMRT-4th.) | Gates MacGinitie Reading Tests-4th Edition (GMRT-4th.) |
| Cut Points - Percentile rank on criterion measure | 20 | 20 | 20 | 20 | 20 |
| Cut Points - Performance score on criterion measure | 317.00 | 381.00 | 418.00 | 439.00 | 439.00 |
| Cut Points - Corresponding performance score (numeric) on screener measure | |||||
| Classification Data - True Positive (a) | 21 | 29 | 25 | 27 | 27 |
| Classification Data - False Positive (b) | 12 | 30 | 26 | 18 | 21 |
| Classification Data - False Negative (c) | 2 | 10 | 4 | 4 | 5 |
| Classification Data - True Negative (d) | 81 | 119 | 104 | 107 | 106 |
| Area Under the Curve (AUC) | 0.94 | 0.88 | 0.92 | 0.94 | 0.87 |
| AUC Estimate’s 95% Confidence Interval: Lower Bound | 0.91 | 0.84 | 0.89 | 0.91 | 0.83 |
| AUC Estimate’s 95% Confidence Interval: Upper Bound | 0.97 | 0.92 | 0.95 | 0.97 | 0.91 |
| Statistics | Grade 1 | Grade 2 | Grade 3 | Grade 4 | Grade 5 |
|---|---|---|---|---|---|
| Base Rate | 0.20 | 0.21 | 0.18 | 0.20 | 0.20 |
| Overall Classification Rate | 0.88 | 0.79 | 0.81 | 0.86 | 0.84 |
| Sensitivity | 0.91 | 0.74 | 0.86 | 0.87 | 0.84 |
| Specificity | 0.87 | 0.80 | 0.80 | 0.86 | 0.83 |
| False Positive Rate | 0.13 | 0.20 | 0.20 | 0.14 | 0.17 |
| False Negative Rate | 0.09 | 0.26 | 0.14 | 0.13 | 0.16 |
| Positive Predictive Power | 0.64 | 0.49 | 0.49 | 0.60 | 0.56 |
| Negative Predictive Power | 0.98 | 0.92 | 0.96 | 0.96 | 0.95 |
| Sample | Grade 1 | Grade 2 | Grade 3 | Grade 4 | Grade 5 |
|---|---|---|---|---|---|
| Date | Fall 2010 through Spring 2011 | Fall 2010 through Spring 2011 | Fall 2010 through Spring 2011 | Fall 2010 through Spring 2011 | Fall 2010 through Spring 2011 |
| Sample Size | 116 | 188 | 159 | 156 | 159 |
| Geographic Representation | West North Central (MN) | West North Central (MN) | West North Central (MN) | West North Central (MN) | West North Central (MN) |
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| Race / Ethnicity Unknown | |||||
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| English Language Learner |
Reliability
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Legend
Convincing evidencePartially convincing evidenceUnconvincing evidenceData unavailabledDisaggregated data available
- *Offer a justification for each type of reliability reported, given the type and purpose of the tool.
- FAST aReading is an IRT-based CAT test; as such, a single model-based approach to reliability will be presented.
- *Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
- The reliability results presented below are based on the 2017-2018 norming sample.
- *Describe the analysis procedures for each reported type of reliability.
- Given the adaptive nature of FASTTM aReading tests, a model-based reliability estimate based on the standard error of measurement and test information function of an instrument was computed following Samejima (1994).
*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
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Legend
Convincing evidencePartially convincing evidenceUnconvincing evidenceData unavailabledDisaggregated data available
- *Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
- The criterion measure for the first type of validity analysis (predictive validity) is the Gates MacGinitie Reading Tests-4th Edition (GMRT-4th). The GMRT-4th is a norm-referenced, group administered measure of reading achievement distributed by Riverside Publishing Company. It is designed to provide guidance in planning instruction and intervention and is typically used as a diagnostic tool for general reading achievement, which makes it an appropriate criterion for FAST aReading. Like FAST aReading, the GMRT-4th was normed with students in the pre-reading stages through high school levels. The GMRT-4th was also selected because of its strong criterion validity. Correlations between the GMRT composite score and comprehension and vocabulary subtests of the Iowa Test of Basic Skills and GMRT composite scores across grades is high (.76 and .78 respectively; Morsy, Kieffer, & Snow, 2010). A similar pattern of results were observed between the GMRT and subscales of the California Tests of Basic Skills (.84 and .81 respectively; Morsy et al., 2010). GMRT scores also correlate highly with Comprehensive Tests of Basic Skills vocabulary, comprehension, and composite scores (.72, .79, and. 83 respectively; Morsy et al., 2010). Further, the correlation between GMRT composite scores and reading scores on the Basic Academic Skills Samples were strong as well (.79; Jenkins & Jewell, 1992). The criterion measure for the second type of validity analysis (construct validity) is the Measures of Academic Progress (MAP). MAP is a diagnostic and computer adaptive assessment designed to measure mathematics ability and progress, which makes it an appropriate criterion to FAST aReading when considering construct validity. In addition, MAP is a known psychometrically sound assessment.
- *Describe the sample(s), including size and characteristics, for each validity analysis conducted.
- Validity analyses were conducted on a sample of students from Minnesota. There were 1,382 students in grades 1-5 from two school districts. Students were 70% White, 5% Black, 8% Hispanic, 15% Asian, and 2% other ethnicities. Approximately 16% of students were eligible for free or reduced price lunch, 14% were English language learners, and 10% were receiving special education services.
- *Describe the analysis procedures for each reported type of validity.
- Validity coefficients were calculated by computing Pearson product moment correlations between FAST aReading 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 |
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| Rating | Yes | Yes | Yes | Yes | Yes |
- Have you conducted additional analyses related to the extent to which your tool is or is not biased against subgroups (e.g., race/ethnicity, gender, socioeconomic status, students with disabilities, English language learners)? Examples might include Differential Item Functioning (DIF) or invariance testing in multiple-group confirmatory factor models.
- Yes
- If yes,
- a. Describe the method used to determine the presence or absence of bias:
- Bias was assessed using the logistic regression procedure for detection of uniform and non-uniform differential item functioning (DIF). The advantages of using the logistic regression procedure for DIF detection include being a model-based approach and having the capability to detect both uniform and non-uniform DIF with adequate and equal power; however, the procedure also tends to inflate Type I error rates. As such, an effect size measure developed by Jodoin and Gierl (2001) was computed and evaluated in addition to statistical significance. Jodoin and Gierl present a four-category framework for interpreting the effect size measure, where the four categories are indicative of no, negligible, moderate, and severe DIF.
- b. Describe the subgroups for which bias analyses were conducted:
- There were sufficient data to examine bias in relation to race/ethnicity. The race/ethnicity group comparisons examined were White versus Black, White versus Hispanic, White versus Asian, and White versus Native American.
- 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.
- The results indicate that there is no or negligible DIF for all items examined for all the race/ethnicity comparisons. The items displaying negligible DIF had effect sizes less than or equal to 0.015.
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.
