FastBridge
CBMreading - English

Descriptive Information

Please provide a description of your tool:

FAST™ CBMreading is a version of Curriculum Based Measurement of Oral Reading (CBM-R), which was originally developed to index the level and rate of reading achievement. FAST™ CBMreading is used to screen and monitor student progress in reading competency in the primary grades (1-8). Students read aloud for one minute from grade-level or instructional-level passages (three passages per assessment). The words read correct per minute functions as a robust indicator of reading and a sensitive indicator of intervention effects.

The tool is intended for use with the following grade(s).

Preschool / Pre - kindergarten
Kindergarten
First grade
Second grade
Third grade
Fourth grade
Fifth grade
Sixth grade
Seventh grade
Eighth grade
Ninth grade
Tenth grade
Eleventh grade
Twelfth grade

The tool is intended for use with the following age(s).

0-4 years old
5 years old
6 years old
7 years old
8 years old
9 years old
10 years old
11 years old
12 years old
13 years old
14 years old
15 years old
16 years old
17 years old
18 years old

The tool is intended for use with the following student populations.

Students in general education
Students with disabilities
English language learners

ACADEMIC ONLY: What skills does the tool screen?

Reading

Phonological processing:

RAN
Memory
Awareness
Letter sound correspondence
Phonics
Structural analysis

Word ID

Accuracy
Speed

Nonword

Accuracy
Speed

Spelling

Accuracy
Speed

Passage

Accuracy
Speed

Reading comprehension:

Multiple choice questions
Cloze
Constructed Response
Retell
Maze
Sentence verification
Other (please describe):

Listening comprehension:

Multiple choice questions
Cloze
Constructed Response
Retell
Maze
Sentence verification
Vocabulary
Expressive
Receptive

Mathematics

Global Indicator of Math Competence

Accuracy
Speed
Multiple Choice
Constructed Response

Early Numeracy

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Concepts

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Computation

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematic Application

Accuracy
Speed
Multiple Choice
Constructed Response

Fractions/Decimals

Accuracy
Speed
Multiple Choice
Constructed Response

Algebra

Accuracy
Speed
Multiple Choice
Constructed Response

Geometry

Accuracy
Speed
Multiple Choice
Constructed Response

Other (please describe):

Please describe specific domain, skills or subtests:

BEHAVIOR ONLY: Which category of behaviors does your tool target?

Internalizing
Externalizing
Internalizing and Externalizing

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

info@fastbridge.org

Address

150 South Fifth Street Suite 600 Minneapolis, MN 55402

Phone Number

6122542534

Website

www.fastbridge.org

Initial cost for implementing program:

Cost

$7.50

Unit of cost

student

Replacement cost per unit for subsequent use:

Cost

$7.50

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.

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 $7.50 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.

Provide information about special accommodations for students with disabilities.

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 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

Administration

BEHAVIOR ONLY: What type of administrator is your tool designed for?

General education teacher
Special education teacher
Parent
Child
External observer
Other

If other, please specify:

What is the administration setting?

Direct observation
Rating scale
Checklist
Performance measure
Questionnaire
Direct: Computerized
One-to-one
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)

Computer or tablet
Internet connection
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?

Individual
Small group   If small group, n=
Large group   If large group, n=
Computer-administered
Other

If other, please specify:

What is the administration time?

Time in minutes

3

per (student/group/other unit)

student

Additional scoring time:

Time in minutes

per (student/group/other unit)

ACADEMIC ONLY: What are the discontinue rules?

No discontinue rules provided
Basals
Ceilings
Other

If other, please specify:

Students read for one minute. Discontinue early is student gets first ten words wrong.

Are norms available?

Yes

Are benchmarks available?

Yes

If yes, how many benchmarks per year?

3

If yes, for which months are benchmarks available?

August - November, December - mid-March, Mid-March - July

BEHAVIOR ONLY: Can students be rated concurrently by one administrator?

If yes, how many students can be rated concurrently?

Training & Scoring

Training

Is training for the administrator required?

Yes

Describe the time required for administrator training, if applicable:

Less than 1 hour of training

Please describe the minimum qualifications an administrator must possess.

No minimum qualifications

Are training manuals and materials available?

Yes

Are training manuals/materials field-tested?

No

Are training manuals/materials included in cost of tools?

Yes

If No, please describe training costs:

Can users obtain ongoing professional and technical support?

Yes

If Yes, please describe how users can obtain support:

Users have access to professional development technicians, as well as ongoing technical support.

Scoring

How are scores calculated?

Manually (by hand)
Automatically (computer-scored)
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?

Age norms
Grade norms
Classwide norms
Schoolwide norms
Stanines
Normal curve equivalents

What types of performance level scores are available?

Raw score
Standard score
Percentile score
Grade equivalents
IRT-based score
Age equivalents
Stanines
Normal curve equivalents
Developmental benchmarks
Developmental cut points
Equated
Probability
Lexile score
Error analysis
Composite scores
Subscale/subtest scores
Other

If other, please specify:

Words read correct per minute

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 read three passages aloud, each for one minute. Each passage results in four scores: total words read, number of word reading errors, words read correctly per minute (total words read – errors), and the percent of words read correctly. The median of the three words correct per minute scores is used as the overall screening score for the identification of risk for reading difficulties. Word reading errors include omissions, insertions, substitutions, and mispronunciations.

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 CBMreading is an evidence-based assessment used to screen and monitor students’ progress in reading achievement in the primary grades (1-8). It can be used as a screener on its own or paired with aReading. For screening CBMreading scores are compared to research-based, empirically derived performance benchmarks. These benchmarks result in four performance levels: high risk, some risk, low risk, and advanced. Further assessment and intervention are recommended for students in the high risk and some risk categories. When paired with aReading, the two assessments are used to provide personalized and classroom instruction plans in the Screening-to-Intervention (S2i) report. aReading is an adaptive and standards-aligned reading measure that provides highly reliable estimates of a student’s overall reading competence. CBMreading is administered individually to each student. The examiner places a printed passage in front of the student, gives brief instructions, and then begins the timer as the student begins to read the passage aloud. The examiner record word reading errors in the system using a digital record form. At the end of one minute the examiner records the last word read. The system automatically computes the CBMreading scores including word correct per minute and accuracy (see scoring structure above). CBMreading passages were developed according to very stringent passage development criteria that controlled linguistic complexity, word decodability, sentence length, and vocabulary. Passages were developed in consultation with educators and content experts. Passage writers participated in a rigorous passage development workshop which included sensitivity and bias guidelines published in the Standards for Educational and Psychological Testing (AERA/APA/NCME, 2014). The goal was to develop passages that were statistically equivalent within grade and were not confounded with a student’s background knowledge. Narratives were selected as the genre for CBMreading passages because they provide the flexibility to select situations and events that are familiar to most students (Schank & Ableson, 1977; Trabasso & Stein, 1997). Following initial passage development, all passages were field tested. After each of the three rounds of field-testing passages that that had linguistic issues based on those analyses and input from educators in the schools were edited and retested. The researchers further consulted with experts to decrease the amount of culturally biased material (e.g. first names of characters in the stories) in the assessment. A word bank containing phonetically regular decodable words was developed. The words were defined based on the word structure suggested by Hiebert and Fisher (2007) and with the word difficulty developed by Menon and Hiebert (1999). Words that were classified as falling into lower levels of difficulty were considered appropriate to use in passage development while words falling into higher levels of difficulty were not included. High frequency word lists were used to design reading passages for students with lower levels of reading. In addition, the rubric prohibited the use of predictable writing (e.g. rhyming, repeated phrases or patterns, alliteration) so that students would need to rely on decoding skills rather than literary clues and cultural context.

Classification Accuracy & Cross-Validation Summary

Grade	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Classification Accuracy Fall
Classification Accuracy Winter
Classification Accuracy Spring

Test of Silent Reading Efficiency and Comprehension (TOSREC)

Classification Accuracy

Select time of year

Fall

Winter

Spring

Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.

The Test of Silent Reading Efficiency and Comprehension (TOSREC) is a brief, group or individually administered test of reading that assesses silent reading of connected text for comprehension. The test can be used for both screening and progress monitoring. The TOSREC measures silent reading speed and accuracy, and comprehension. Respondents are given three minutes to read and verify the truthfulness of as many sentences as possible.

Do the classification accuracy analyses examine concurrent and/or predictive classification?

Concurrent
Predictive

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.

Fall

Winter

Spring

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?

Concurrent
Predictive

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

Fall

Winter

Spring

Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.

NWEA MAP is a comprehensive computer-adaptive academic screener that assesses reading skills aligned to state standards.

Do the classification accuracy analyses examine concurrent and/or predictive classification?

Concurrent
Predictive

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.

Both CBMreading and NWEA MAP reading were administered concurrently in the fall, winter, and spring. Because both assessments are used to identify students at risk for reading difficulties the concurrent evaluation of classification accuracy is appropriate.

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 the criterion measure (MAP reading) was selected to classify students as in need of intensive intervention. Students scoring at or below the 20th percentile were identified as needing intensive intervention. Thus, the analyses contrasted students at high risk vs students at low to moderate risk.

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.

Fall

Winter

Spring

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?

Concurrent
Predictive

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	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Criterion measure	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth
Cut Points - Percentile rank on criterion measure	15	15	15	15	15	15	15	15
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	15	45.5	76	104	132	122	144	121
Classification Data - True Positive (a)	25	139	235	178	196	92	46	26
Classification Data - False Positive (b)	62	130	251	202	311	106	128	30
Classification Data - False Negative (c)	8	31	59	43	45	20	13	7
Classification Data - True Negative (d)	86	677	1145	820	793	525	158	117
Area Under the Curve (AUC)	0.76	0.91	0.90	0.88	0.84	0.91	0.80	0.91
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.68	0.89	0.88	0.86	0.82	0.88	0.74	0.86
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.84	0.93	0.92	0.90	0.87	0.93	0.87	0.96

Statistics	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Base Rate	0.18	0.17	0.17	0.18	0.18	0.15	0.17	0.18
Overall Classification Rate	0.61	0.84	0.82	0.80	0.74	0.83	0.59	0.79
Sensitivity	0.76	0.82	0.80	0.81	0.81	0.82	0.78	0.79
Specificity	0.58	0.84	0.82	0.80	0.72	0.83	0.55	0.80
False Positive Rate	0.42	0.16	0.18	0.20	0.28	0.17	0.45	0.20
False Negative Rate	0.24	0.18	0.20	0.19	0.19	0.18	0.22	0.21
Positive Predictive Power	0.29	0.52	0.48	0.47	0.39	0.46	0.26	0.46
Negative Predictive Power	0.91	0.96	0.95	0.95	0.95	0.96	0.92	0.94

Sample	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Date	2018-19	2018-19	2018-19	2018-19	2018-19	2018-19	2018-19	2018-19
Sample Size	181	977	1690	1243	1345	743	345	180
Geographic Representation	East North Central (WI) West North Central (MN)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (MN, MO)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Winter

Evidence	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Criterion measure	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth
Cut Points - Percentile rank on criterion measure	15	15	15	15	15	15	15	15
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	59.5	65	103	125	151	145	150	138
Classification Data - True Positive (a)	49	126	175	167	186	100	30	13
Classification Data - False Positive (b)	74	81	199	182	305	156	67	14
Classification Data - False Negative (c)	10	22	42	45	45	21	8	4
Classification Data - True Negative (d)	144	478	819	765	753	491	118	64
Area Under the Curve (AUC)	0.83	0.90	0.88	0.88	0.83	0.87	0.83	0.90
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.78	0.88	0.86	0.85	0.80	0.83	0.75	0.84
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.88	0.93	0.91	0.90	0.86	0.90	0.90	0.97

Statistics	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Base Rate	0.21	0.21	0.18	0.18	0.18	0.16	0.17	0.18
Overall Classification Rate	0.70	0.85	0.80	0.80	0.73	0.77	0.66	0.81
Sensitivity	0.83	0.85	0.81	0.79	0.81	0.83	0.79	0.76
Specificity	0.66	0.86	0.80	0.81	0.71	0.76	0.64	0.82
False Positive Rate	0.34	0.14	0.20	0.19	0.29	0.24	0.36	0.18
False Negative Rate	0.17	0.15	0.19	0.21	0.19	0.17	0.21	0.24
Positive Predictive Power	0.40	0.61	0.47	0.48	0.38	0.39	0.31	0.48
Negative Predictive Power	0.94	0.96	0.95	0.94	0.94	0.96	0.94	0.94

Sample	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Date	2018-19	2018-19	2018-19	2018-19	2018-19	2018-19	2018-19	2018-19
Sample Size	277	707	1235	1159	1289	768	223	95
Geographic Representation	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (IA, MN, MO, NE)	East North Central (WI) West North Central (MN, MO, NE)	East North Central (WI) West North Central (MO)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Spring

Evidence	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Criterion measure	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth	NWEA MAP Growth
Cut Points - Percentile rank on criterion measure	15	15	15	15	15	15	15	15
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	60	90	122	146	163	158	165	166
Classification Data - True Positive (a)	49	103	145	179	180	49	33	9
Classification Data - False Positive (b)	74	87	223	275	280	57	73	10
Classification Data - False Negative (c)	10	18	38	43	50	11	8	2
Classification Data - True Negative (d)	144	390	664	680	765	266	121	41
Area Under the Curve (AUC)	0.83	0.91	0.86	0.85	0.85	0.89	0.79	0.92
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.78	0.88	0.83	0.82	0.83	0.85	0.71	0.84
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.88	0.93	0.89	0.87	0.88	0.94	0.86	1.00

Statistics	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Base Rate	0.21	0.20	0.17	0.19	0.18	0.16	0.17	0.18
Overall Classification Rate	0.70	0.82	0.76	0.73	0.74	0.82	0.66	0.81
Sensitivity	0.83	0.85	0.79	0.81	0.78	0.82	0.80	0.82
Specificity	0.66	0.82	0.75	0.71	0.73	0.82	0.62	0.80
False Positive Rate	0.34	0.18	0.25	0.29	0.27	0.18	0.38	0.20
False Negative Rate	0.17	0.15	0.21	0.19	0.22	0.18	0.20	0.18
Positive Predictive Power	0.40	0.54	0.39	0.39	0.39	0.46	0.31	0.47
Negative Predictive Power	0.94	0.96	0.95	0.94	0.94	0.96	0.94	0.95

Sample	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Date	2018-19	2018-19	2018-19	2018-19	2018-19		2018-19	2018-19
Sample Size	277	598	1070	1177	1275	383	235	62
Geographic Representation	East North Central (WI) West North Central (MN, NE)	East North Central (WI) West North Central (IA, MN, NE)	East North Central (WI) West North Central (IA, KS, MN, NE)	East North Central (WI) West North Central (IA, KS, MN, NE)	East North Central (WI) West North Central (IA, MN, NE)	East North Central (WI) West North Central (IA, MN, NE)	East North Central (WI) West North Central (MN)	East North Central (WI)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Reliability

Grade	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Rating

*Offer a justification for each type of reliability reported, given the type and purpose of the tool.

The first type of reliability evidence we present is alternate-form reliability. Alternate-form reliability is an appropriate measure of reliability for CBMreading because different three passages are used in screening, thus, consistency in the rank order of scores over forms (passages) is important. The results presented below are median correlations between students’ scores on the three screening passages. The second type of reliability evidence we present is inter-rater reliability. Inter-rater reliability is an appropriate measure of reliability for the use of FastBrigde CBMreading because teachers listen to students and evaluate their oral reading fluency, including accuracy, so consistency across teachers (raters) is important. For Grades 7 & 8 test-retest reliability coefficients were computed using scores from the fall and winter universal screening administrations. Test-retest reliability is appropriate because the same reading passages are used in each screening period. It provides an index of the stability of the rank ordering of the students in a classroom or grade.

*Describe the sample(s), including size and characteristics, for each reliability analysis conducted.

Alternate-form reliability: 2018-19 fall screening scores of students across 20 states was used for this analysis. Inter-rater Reliability: Approximately 1,900 students in grades 1-6 (see table below for student N by grade level). Students came from three samples, one from Minnesota, one from Georgia, and one from New York. Test-retest reliability was derived from 2018-19 fall and winter screening scores of students who were retested within a 14-day window. Data are based on students across multiple states.

*Describe the analysis procedures for each reported type of reliability.

Inter-rater reliability coefficients were estimated by calculating the median percent agreement between two teachers scores for each student. Confidence intervals represent 95% confidence intervals. Alternate-form reliability coefficients were estimated by calculating the Pearson product moment correlations between scores for each combination of passages. The coefficients below represent the median of those correlations. Confidence intervals represent 95% confidence intervals. Test-retest reliability was computed from the Pearson correlation between the two administration..

*In the table(s) below, report the results of the reliability analyses described above (e.g., internal consistency or inter-rater reliability coefficients).

Type of	Subgroup	Informant	Age / Grade	Test or Criterion	n	Median Coefficient	95% Confidence Interval Lower Bound	95% Confidence Interval Upper Bound

Results from other forms of reliability analysis not compatible with above table format:

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

Do you have reliability data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?

No

If yes, fill in data for each subgroup with disaggregated reliability data.

Type of	Subgroup	Informant	Age / Grade	Test or Criterion	n	Median Coefficient	95% Confidence Interval Lower Bound	95% Confidence Interval Upper Bound

Results from other forms of reliability analysis not compatible with above table format:

Manual cites other published reliability studies:

No

Provide citations for additional published studies.

Validity

Grade	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Rating

*Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.

The criterion measure in Grades 1 - 6 for both types of validity analyzes (concurrent and predictive) is the oral reading fluency measure that is a part of the AIMSweb system. The measure is an appropriate criterion because is measures a construct hypothesized to be related to FastBridge CBMreading. The criterion measure in Grades 7 & 8 for both types of validity analyzes (concurrent and predictive) is NWEA MAP reading assessment. The MAP reading assessment is appropriate because it provides a broad indicator of overall reading ability.

*Describe the sample(s), including size and characteristics, for each validity analysis conducted.

Concurrent and predictive analyses with AIMSweb oral reading fluency measure were conducted on a sample of students from Minnesota. There were approximately 220 students in each of grades 1-6. Concurrent and predictive analyses NWEA MAP were conducted on a sample of students from across five state: MN, WI, NE, IA, and MO. There were 345 and 180 students for concurrent validity in Grades 7 and 8 respectively, and. 193 and 62 for predictive validity.

*Describe the analysis procedures for each reported type of validity.

Validity coefficients were calculated by computing Pearson product moment correlations between FastBridge CBMreading and the criterion measures. 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.

The validity coefficients provide moderate to strong evidence for the use of FAST™ CBMreading as a measure of CBM-R.

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	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Rating	No	No	No	No	No	No	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.