Star CBM
Passage Oral Reading (formerly CES Standard Reading Passages)

Descriptive Information

Please provide a description of your tool:

The Star CBM Passage Oral Reading measures (formerly Children’s Educational Services’ Standard Reading Passages) include grade-level passages for teachers and other school personnel to use in screening to establish student achievement in reading, to set goals for those students, to monitor their progress, and to evaluate the effectiveness of instruction for the purpose of modifying instruction when indicated. The essential procedures were developed by researchers at the University of Minnesota beginning in 1977 and the years following. The reading passages were initially written in 1988 and disseminated as the Standard Reading Passages by Children’s Educational Services. In 2019, those passages were acquired by Renaissance Learning and incorporated into Star Curriculum Based Measurement as the Passage Oral Reading measures.

Is your tool designed to measure progress towards an end-of-year goal (e.g., oral reading fluency) or progress towards a short-term skill (e.g., letter naming fluency)?

End-year goal
Short-term skill

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 dimensions does the tool assess?

Reading

Global Indicator of Reading Competence
Listening Comprehension
Vocabulary
Phonemic Awareness
Decoding
Passage Reading
Word Identification
Comprehension

Spelling & Written Expression

Global Indicator of Spelling Competence
Global Indicator of Writting Expression Competence

Mathematics

Global Indicator of Mathematics Comprehension
Early Numeracy
Mathematics Concepts
Mathematics Computation
Mathematics Application
Fractions
Algebra

Other

Please describe specific domain, skills or subtests:

BEHAVIOR ONLY: Please identify which broad domain(s)/construct(s) are measured by your tool and define each sub-domain or sub-construct.

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

Acquisition and Cost Information

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:

BEHAVIOR ONLY: What is the administration format?

Direct observation
Rating scale
Checklist
Performance measure
Other

If other, please specify:

BEHAVIOR ONLY: What is the administration setting?

General education classroom
Special education classroom
School office
Recess
Lunchroom
Home
Other

If other, please specify:

Does the program require technology?

Yes

If yes, what technology is required to implement your program? (Select all that apply)

Computer or tablet
Internet connection
Other technology (please specify)

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:

ACADEMIC ONLY: What are the discontinue rules?

No discontinue rules provided
Basals
Ceilings
Other

If other, please specify:

Time

Training & Scoring

Training

Is training for the administrator required?

Yes

Describe the time required for administrator training, if applicable:

Less than one 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?

Yes

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

BEHAVIOR ONLY: What types of scores result from the administration of the assessment?

Score

Observation	Behavior Rating
Frequency Duration Interval Latency	Raw score

Conversion

Observation	Behavior Rating
Rate Percent	Standard score Subscale/ Subtest Composite Stanine Percentile ranks Normal curve equivalents IRT based scores

Interpretation

Observation	Behavior Rating
Error analysis Peer comparison Rate of change	Dev. benchmarks Age-Grade equivalent

How are scores calculated?

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

If other, please specify:

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 correctly per minute

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.

Count of number of words read correctly in one minute of reading aloud. Note that the score may be adjusted as a result of equating forms to ensure difficulty is consistent within grade.

Do you provide basis for calculating slope (e.g., amount of improvement per unit in time)?

Yes

ACADEMIC ONLY: Do you provide benchmarks for the slopes?

Yes

ACADEMIC ONLY: Do you provide percentile ranks for the slopes?

No

What is the basis for calculating slope and percentile scores?

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

Describe the tool’s approach to progress monitoring, behavior samples, test format, and/or scoring practices, including steps taken to ensure that it is appropriate for use with culturally and linguistically diverse populations and students with disabilities.

Tool uses standard GOM approach to progress monitoring. Twenty passages at the same difficulty level are available for use in repeated 1 minute samples of reading aloud from text. Testers use standard instructions to students and follow along on a duplicate passage marking incorrectly read words and coding errors, if desired. Subsequent to each reading, the tester counts the number of words correct and incorrect and enters those scores into the Edcheckup on line system. In addition, testers are encouraged to rate the degree of prosody evident in the student’s oral reading of the passage. In constructing the passages an effort has been made to minimize passage content requiring background knowledge specific to locale and culture. The names of characters have been drawn from a variety of ethnicities. In addition, passages comprise content from a very broad range of experience common to students in the USA. The comprehensiveness is good in that it reduces bias associated with particular regions and cultures in the US. At the same time, we recognize that it is not possible to avoid cultural and linguistic bias from passages.(We believe that, since the PM system is individually-referenced, the relevant data for decision making is growth on the passages. With repeated measurements across time the effects of cultural and linguistic bias become less relevant to the question of whether the student is improving in reading English.

Rates of Improvement and End of Year Benchmarks

Is minimum acceptable growth (slope of improvement or average weekly increase in score by grade level) specified in your manual or published materials?

Yes

If yes, specify the growth standards:

Our growth standards are derived from a sample of 2007 students enrolled in grades 1 to 6 who were progress monitored on a weekly basis during the school year. The sample included 228 students in grade 1, 418 students in grade 2, 493 students in grades 3, 353 students in grade 4, 332 students in grade 5, and 183 students in grade 6. The average number of progress monitoring passages administered to these students was 16.5 (SD=6.3). To specify "rates of improvement" for Words Read Correctly we calculated the slope for each student. We then developed percentiles for Words Read Correctly for each grade level. In the table below we provide the 25th, 50, and 75th percentiles at each grade, 1 through 6 (see table below). Slopes associated with the 75th percentile are 1.6 at grade 1, 1.6 at grade 2, 1.4 at grade 3, 1.2 at grade 4, 1.4 at grade 5, and 1.3 at grade 6.

Are benchmarks for minimum acceptable end-of-year performance specified in your manual or published materials?

No

If yes, specify the end-of-year performance standards:

What is the basis for specifying minimum acceptable growth and end of year benchmarks?

Norm-referenced
Criterion-referenced
Other

If other, please specify:

False

National representation (check all that apply):

Northeast:

New England

Middle Atlantic

Midwest:

East North Central

West North Central

South:

South Atlantic

East South Central

West South Central

West:

Mountain

Pacific

Local representation (please describe, including number of states)

Date

2014-15 SY

Size

Gender (Percent)

Male

53.1

Female

46.9

Unknown

SES indicators (Percent)

Eligible for free or reduced-price lunch

72.2

Other SES Indicators

Race/Ethnicity (Percent)

White, Non-Hispanic

40.1

Black, Non-Hispanic

29.7

Hispanic

14.4

American Indian/Alaska Native

5.3

Asian/Pacific Islander

9.9

Other

Unknown

Disability classification (Please describe)

First language (Please describe)

Language proficiency status (Please describe)

Do you provide, in your user’s manual, norms which are disaggregated by race or ethnicity? If so, for which race/ethnicity?

White, Non-Hispanic
Black, Non-Hispanic
Hispanic
American Indian/Alaska Native
Asian/Pacific Islander
Other
Unknown

If criterion-referenced, describe procedure for specifying criterion for adequate growth and benchmarks for end-of-year performance levels.

Describe any other procedures for specifying adequate growth and minimum acceptable end of year performance.

Reliability

Grade	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6
Rating		d	d	d	d	d

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

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

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

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

*In the table(s) below, report the results of the reliability analyses described above (e.g., model-based evidence, internal consistency or inter-rater reliability coefficients). Include detail about the type of reliability data, statistic generated, and sample size and demographic information.

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)?

Yes

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

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
Rating	d	d	d	d	d	d

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

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

The Measures of Academic Progress (MAP) was used as the outcome measure. Published by the NWEA the MAP is regarded as a highly valid and reliable measure of broad reading ability. The NWEA website states, “Our tools are trusted by educators in 140 countries and more than half the schools in the US” which indicates it can be considered an excellent outcome measure for classification studies on the Oral Reading measure studied here. See https://www.nwea.org/normative-data-rit-scores/ for more information. The MAP is an external measure. A second criterion used in our analysis is the Minnesota Comprehensive Assessment (MCA) and reading. The MCA is the state accountability test for Minnesota and has been established by the Minnesota Department of Education to be a highly reliable and valid measure or reading. See http://education.state.mn.us/MDE/dse/test/mn/Tech/ for more technical information. The MCA is an external measure.

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

For the Concurrent and Predictive validity analyses for Passage Reading and MAP there was a total sample of 9,410 students (grades 1-6). Demographic data indicated 48.4% of the sample was female, 12.4% was special education, 24.0% received Title services, 7.5% was served in a gifted program, 38.2% received free or reduced lunch, and 5.1% received ELL service. Ethnic percentages for this sample were 1.3% for American Indian, 4.9% for Asian American, 10.3% for Hispanic American, 7.7% for Black American, and 75.8% for White American. For the Concurrent and Predictive validity analyses for Passage Reading and MCA there was a total sample of 11,094 students (grades 3-6). Demographic data indicated 48.2% of the sample was female, 12.4% was special education, 27.2% received Title services, 9.3% was served in a gifted program, 27.6% received free or reduced lunch, and 7.7% received ELL service. Ethnic percentages for this sample were 2.6% for American Indian, 4.0% for Asian American, 9.4% for Hispanic American, 12.2% for Black American, and 71.8% for White American.

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

Two types of validity analysis were conducted; Concurrent and Predictive. The Concurrent study used Pearson Product Moment Correlational analysis to examine the relationship between Passage Reading (Words Read Correctly) and the MAP and the MCA. All measures were administered in the Spring of 2017. The Predictive study used Pearson Product Moment Correlational analysis to examine the relationship between Passage Reading (Words Read Correctly) and the MAP and the MCA. Passage Reading was administered in the Winter of 2017 and the criterion measures of MAP and MCA were administered in the Spring of 2017, approximately three months later.

*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.

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.

Validity coefficients for both concurrent and predictive validity are typically high. The median correlation coefficient for concurrent validity is .73 and is .70 for predictive validity.

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

Yes

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

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

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:

First, the authors conducted a measurement invariance analysis using invariance testing in multiple-group confirmatory factor models. Second, the authors fit several regression models in which the spring benchmark progress monitoring score was regressed on a score on an external standardized measure of broad reading ability, The Measures of Academic Progress (MAP). In addition to the spring MAP assessment score, the authors included various demographic variables in the model to estimate main effects and potential interaction effects between the demographic variables and the MAP score.

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

The subgroups for the measurement invariance analysis were formed based on students' race/ethnicity and included White students, African American students, Asian students, Hispanic students, and American Indian students. The subgroups used for the regression analysis were formed based on demographic factors including ethnicity, free and reduced lunch eligibility, and English Language Learner (ELL) status.

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.

Measurement Invariance Analysis Results: Overall, every ethnic group’s model-fit well. All relative fit indices (CFI, TLI) were above .98, which indicates very good model fit, given that a value over .90 is suggested to be a reasonably good fit for CFI and TLI (Hu & Bentler, 1998). In addition, the 90 percent confidence interval for RMSEA indicates very good model fit, given that a value below or at .05 is considered a very close approximate fit (Browne & Cudeck, 1993). These results show that all CBM-R assessments appeared to function equally well as one factor for all ethnic groups. For the first three comparisons (White vs. African American/Asian/Hispanic), the configural (equal structure) model had a good fit, and thus a series of model constraints were then applied in successive models to examine potential decrease in model fit. Two nested models were compared in model fit based on chi-square and degree of freedom differences at α= .05. The full metric invariance model fit well; but resulted in a marginally significant decrease in fit (chi-square difference) relative to the configural model. The partial metric invariance model (freeing just one loading), however, did not result in a significant decrease in fit, which indicates that CBM-R measures seem to be related to the factor equivalently between White and other groups. The full scalar model fit well; but also resulted in a marginally significant decrease in fit relative to the partial metric model. However, the partial scalar model (freeing just one intercept) did not result in a significant decrease in fit, which means that both ethnic groups (with the same level of reading) are expected to perform on CBM-R assessments in a very similar way. In case of the comparison between White and American Indian, both the full metric invariance model and the full scalar model did not result in a significant decrease in fit, which indicates that the same latent factor was being measured for the two groups and they have exactly the same expected performance on CBM-R if their levels are the same. These results suggest that the same structure (configural invariance) and the same latent factor (full/partial metric invariance) were being measured in each ethnic group. In addition, the fact that the partial or full scalar invariance held indicates that White and other ethnic groups (with the same level of reading) have almost the same expected performance on CBM-R. In conclusion, there was no evidence on structural/measurement invariance (i.e., test bias) between White and other ethnic groups, meaning that CBM-R appears to be an unbiased measure among different ethnic groups. Test bias (measurement invariance) analysis results using invariance testing in multiple-group confirmatory factor models. Tables with detailed results from these analyses are available from the Center upon request. Regression Analysis Results: The authors interpreted any main effects associated with the demographic variables, or interaction effects between the demographic variables and the MAP assessment score as evidence of bias in passages (analogous to differential item functioning). Most P-values exceed the .001 level of significance. Tables with detailed results from these analyses are available from the Center upon request.

Sensitivity: Reliability of Slope

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

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

Describe the sample, including size and characteristics. Please provide documentation showing that the sample was composed of students in need of intensive intervention. A sample of students with intensive needs should satisfy one of the following criteria: (1) all students scored below the 30th percentile on a local or national norm, or the sample mean on a local or national test fell below the 25th percentile; (2) students had an IEP with goals consistent with the construct measured by the tool; or (3) students were non-responsive to Tier 2 instruction. Evidence based on an unknown sample, or a sample that does not meet these specifications, may not be considered.

Total students in subject sample was 2029. The percentage of students that were American Indian was 5.3%, for African American was 29.7%, for Asian American was 9.9%, for Hispanic American was 14.4%, for White American was 40.1%. 47% of the sample was female. 18.8% of the sample were students with disabilities.

Describe the frequency of measurement (for each student in the sample, report how often data were collected and over what span of time).

Describe the analysis procedures.

In our reliability of slope analysis we used Latent Growth Modeling (LGM) to estimate the reliability of longitudinal weekly growth data as demonstrated by Yeo, Kim, Branum-Martin, Wayman, and Espin (2011). These researchers point out, "The feature of LGM that treats time as an independent variable at each occasion makes it possible to estimate the reliability of longititudinal data such as CBM data" (p. 276). An important conclusion of their study was, “ a crucial advantage of LGM is that reliability estimated by LGM takes into account the developmental trajectories at the individual level of analysis (Tisak & Tisak, 2000)” (p. 287). The reliabilities for 9 weekly assessments at each grade level, grades 1-6, are presented in the table below. For each grade level (and the entire sample) we report sample sizes, means, model-implied observed score variance, measurement error variance, observed variance - error variance, SEM, reliability for each assessment, and the median reliability for each grade level. The range of median reliability coefficients for weekly progress monitoring probes across the six grades levels was .73 to .89 with a median of .81.

In the table below, report reliability of the slope (e.g., ratio of true slope variance to total slope variance) by grade level (if relevant).

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 of the slope data that is disaggregated by subgroups (e.g., race/ethnicity, gender, socioeconomic status, students with disabilities, English language learners)?

No

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

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.

Sensitivity: Validity of Slope

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

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

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

The Measures of Academic Progress (MAP) was used as the outcome measure. Published by the NWEA the MAP is regarded as a highly valid and reliable measure of broad reading ability. The NWEA website states, “Our tools are trusted by educators in 140 countries and more than half the schools in the US” which indicates it can be considered an excellent outcome measure for classification studies on the Oral Reading measure studied here. See https://www.nwea.org/normative-data-rit-scores/ for more information. The MAP is an external measure and was administered in the fall and spring of the 2016-17 school year.

Describe the sample(s), including size and characteristics. Please provide documentation showing that the sample was composed of students in need of intensive intervention. A sample of students with intensive needs should satisfy one of the following criteria: (1) all students scored below the 30th percentile on a local or national norm, or the sample mean on a local or national test fell below the 25th percentile; (2) students had an IEP with goals consistent with the construct measured by the tool; or (3) students were non-responsive to Tier 2 instruction. Evidence based on an unknown sample, or a sample that does not meet these specifications, may not be considered.

The sample of students used in the validity of slope analysis are students in need of intensive intervention. All 229 students scored below the 20th percentile on MAP Reading in the fall of the school year. The demographic characteristics of the sample were: Free and Reduced Lunch: 38% Special Education: 21% Title I Service: 50% Female: 42%, Male: 58% English Language Learners: 9% American Indian students: 4% Asian American students: 4% Hispanic American students: 14% Black American students: 7% White American students: 71%

Describe the frequency of measurement (for each student in the sample, report how often data were collected and over what span of time).

Students in the validity of slope sample (N=229) were progress monitored on a weekly basis during the 2016-17 school year. The average number of weekly data points for the Words Read Correctly measure was 18.3 (SD = 6.1). The range for frequency of measurement was from 10 weeks to 28 weeks.

Describe the analysis procedures for each reported type of validity.

Three types of analysis were used to validate the weekly slope of Words Read Correctly. 1. Pearson Correlation: Correlating Weekly slope of Words Read Correctly with performance on MAP Reading in the Spring. 2. Pearson Correlation: Correlating Weekly slope of Words Read Correctly with the increase from fall to spring on the MAP Reading RIT score. 3. Partial Correlation: Correlating Weekly slope of Words Read Correctly with performance on MAP Reading in the Spring and controlling for initial level of MAP Reading performance in the fall.

In the table below, report predictive validity of the slope (correlation between the slope and achievement outcome) by grade level (if relevant).
NOTE: The TRC suggests controlling for initial level when the correlation for slope without such control is not adequate.

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

Manual cites other published validity studies:

No

Provide citations for additional published studies.

Describe the degree to which the provided data support the validity of the tool.

All correlation coefficients reported were statistically significant. Data indicates that weekly slope for Words Read Correctly over the school year is significantly related to the external criterion measure of MAP Reading, which was measured in the fall and spring of the school same year.

Do you have validity of the slope data that is disaggregated by subgroups (e.g., race/ethnicity, gender, socioeconomic status, students with disabilities, English language learners)?

No

If yes, fill in data for each subgroup with disaggregated validity of the slope data.

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

Manual cites other published validity studies:

No

Provide citations for additional published studies.

Alternate Forms

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

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

Describe the sample for these analyses, including size and characteristics:

To explore alternative forms of the progress monitoring tool, the authors fit an analysis of variance by grade in which words read correctly (for students’ first passage) was regressed on the passage id. The analysis was conducted at each grade level on a sample of students meeting the criteria for needing intensive intervention (below the 20th percentile). An anova model comparing mean words read correctly by passage id, was compared against a null model with an intercept only. The authors used an adjusted critical p-value (for fitting the analyses by grade for grades 1 through 6) of 0.008 (0.05/6). The results indicate no significant differences among the alternate forms of the passages at each grade level and are presented below. Additional Evidence: Grade n Res, Sum of Sqs DF Sum of Sqs Statistic p Value 1 59 122.4 14 27.78 0.73 0.73 2 1049 54947.6 19 1969.78 1.94 0.01 3 915 154835 20 3978.55 1.15 0.29 4 913 298397 19 10234.2 1.61 0.05 5 831 284776 19 13077 1.96 0.01 6 534 209160 19 9366.12 1.21 0.24 Evidence of controlled difficulty for the passages used for progress monitoring at each grade was also obtained through use of the Flesch-Kinkaid Grade Level readability formula and the Lexile Framework for Reading (Metametrics, 2002). Both analyses indicate the passages were placed at appropriate grade levels. At grade 1 the average Flesch readability was 1.6 and Lexile was 272. At grade 2 the average Flesch readability was 2.4 and Lexile was 397. At grade 3 the average Flesch readability was 3.3 and Lexile was 511. At grade 4 the average Flesch readability was 4.2 and Lexile was 656. At grade 5 the average Flesch readability was 5.8 and Lexile was 759. At grade 6 the average Flesch readability was 6.9 and Lexile was 850.

What is the number of alternate forms of equal and controlled difficulty?

20 alternate forms.

If IRT based, provide evidence of item or ability invariance

If computer administered, how many items are in the item bank for each grade level?

If your tool is computer administered, please note how the test forms are derived instead of providing alternate forms:

Decision Rules: Setting & Revising Goals

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

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

In your manual or published materials, do you specify validated decision rules for how to set and revise goals?

No

If yes, specify the decision rules:

What is the evidentiary basis for these decision rules?
NOTE: The TRC expects evidence for this standard to include an empirical study that compares a treatment group to a control and evaluates whether student outcomes increase when decision rules are in place.

Decision Rules: Changing Instruction

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

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

In your manual or published materials, do you specify validated decision rules for when changes to instruction need to be made?

No

If yes, specify the decision rules:

What is the evidentiary basis for these decision rules?
NOTE: The TRC expects evidence for this standard to include an empirical study that compares a treatment group to a control and evaluates whether student outcomes increase when decision rules are in place.