FastBridge
CBMreading - English

Descriptive Information

Please provide a description of your tool:

FastBridge 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. FastBridge 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

answers@renaissance.com

Address

Renaissance Learning, PO Box 8036, Wisconsin Rapids, WI 54495

Phone Number

(800) 338-4204

Website

https://www.renaissance.com

Initial cost for implementing program:

Cost

Unit of cost

Replacement cost per unit for subsequent use:

Cost

Unit of cost

Duration of license

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.

FastBridge assessments are accessed through an annual subscription using a per-student assessed pricing model with no additional fixed costs. The all-inclusive subscription provides access to all FastBridge reading and math assessments for universal screening, progress monitoring, and diagnostic purposes, including both Computer Adaptive Tests (CATs) and Curriculum-Based Measurements (CBMs). The subscription also includes social-emotional behavior assessment tools (SAEBRS, mySAEBRS), developmental milestones assessments, and both English and Spanish assessments at no extra cost. The fully cloud-based data management and reporting system includes screening, progress monitoring, diagnostic, and impact reports, along with digital record forms for assessment administration. All training manuals and materials are included in the subscription cost, along with embedded online system training modules, access to professional development technicians, ongoing technical support, and Renaissance How-to Webinars available via recording. Administration documents, parent information letters, and training resources are accessible through the software's Training & Resources tab. Optional onsite training packages are available in one-day, two-day, or three-day formats, determined by implementation size and which FastBridge assessments a district intends to use. Any onsite training purchase includes a complimentary online Admin/Manager training session for District Managers and School Managers. Additionally, web-based consultation and training delivered by certified FastBridge trainers is available on an hourly basis. The subscription model allows students to take multiple assessments with no per-assessment fees, includes all updates and new features during the subscription period, and provides year-long technical support with unlimited access to training resources.

Provide information about special accommodations for students with disabilities.

FastBridge provides the following accommodations within the assessment for students with and without disabilities. These accommodations are allowed for both screening and progress monitoring purposes: Magnification (enlarged materials); Sound amplification; Extra breaks as needed; Preferential seating and use of quiet space; Proxy responses; Students with different needs or abilities may use scratch paper FastBridge is committed to supporting student accessibility. The FastBridge student experience has been evaluated against recognized accessibility standards, including WCAG 2.0 and 2.1, and a Voluntary Product Accessibility Template (VPAT®) is available that documents current levels of support. Accessibility considerations continue to be incorporated into ongoing product development as we work to improve access for all learners.

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:

Renaissance Technical Support Staff

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.

Risk benchmarks

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. 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.

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 FastBridge CBMreading measures are analyzed within a classical test theory framework with scores reported in a correct per minute metric. CBMs are unique from other tests in that tests are typically stopped after a set amount of time (usually 1 minute of time), and most students are not expected to complete all of the items on a form within the time limit. As a result, reliability estimates that rely on total scores and that can be formulated within a classical test theory framework are appropriate for CBMs. FastBridge CBMreading reports several different reliability coefficients, including model-based G-coefficients from generalizability theory analyses and alternate forms coefficients, as summarized below. 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.

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

A total of 74,749 US students in grades 1-8 were included in each analysis. Data were collected during the 2024-2025 school year and came from 37 states plus the District of Columbia. Sample sizes by grade are indicated below.

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

Generalizability theory estimates included facets for form, number of days after August 1 the passages were taken, and persons, while alternate forms coefficients were based on the average Pearson product moment correlations between words read correct scores on pairwise combinations of the screening passages given in each season. Generalizability theory estimates ranged from 0.89 to 0.92, while alternate forms estimates ranged from 0.94 to 0.97. These estimates demonstrate that CBMReading has high estimated reliability in grades 1 through 8 based on these two different reliability coefficients. 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.

*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	Provided	Provided	Provided	Provided	Provided	Provided	Provided	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:

Statistical bias was assessed by grade level (1-8) using data from nearly 1.5 million administrations from the 2024-25 school year. An effect size measure was used to evaluate the practical difference between subgroup level AUC scores. This approach was selected over a test of statistical signifance (e.g., DeLong’s Test, chi-squared test), because many of these tests are sensitive to group imbalances (i.e., different counts between risk groups) and large sample sizes, which can lead to increased Type I error rates. Instead, a difference between AUC scores (∆AUC ) was used as an effect size measure to assess practical differences between subgroup AUC scores. A common rule-of-thumb approach to gauge ∆AUC is: negligible (ES <=0.02), small (ES 0.03-0.05), small (ES 0.06-0.10), and large (ES >0.10).

b. Describe the subgroups for which bias analyses were conducted:

The data set was sufficient to examine bias in relation to race/ethnicity by grade, 1 - 8. The race/ethnicity group comparisons examined were White versus African American, White versus Hispanic, White versus Asian, and White versus Other.

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.

Overall ∆AUC never exceeded 0.05 when comparing White vs Black/African American, White vs Hispanic, White vs Asian, or White vs Other students across all grades indicating that the difference in misclassification across subgroups was either small or negligible and bias was minimal. Comparisons between White and Black/African American students are as follows: G1 = 0.005; G2 = 0.011; G3 = 0.024; G4 = 0.021; G5 = 0.026; G6 = 0.043; G7 = 0.047; G8 = 0.046. White and Hispanic/Latino students are as follows: G1 = 0.007; G2 = 0.002; G3 = 0.004; G4 = 0.003; G5 = 0.006; G6 = 0.006; G7 = 0.016; G8 = 0.009. White and Asian students are as follows: G1 = 0.027; G2 = 0.000; G3 = 0.002; G4 = 0.008; G5 = 0.000; G6 = 0.025; G7 = 0.017; G8 = 0.010. White and Other students are as follows: G1 = 0.001; G2 = 0.003; G3 = 0.004; G4 = 0.015; G5 = 0.014; G6 = 0.021; G7 = 0.020; G8 = 0.017.