easyCBM
Proficient Reading (formerly Reading Comprehension)

Descriptive Information

Please provide a description of your tool:

easyCBM is a web-based assessment system that includes both benchmarking and progress monitoring assessments combined with a comprehensive array of reports. The assessments in easyCBM are general outcome curriculum-based measures, of CBMs, which are standardized measures that sample from a year's worth of curriculum to assess the degree to which students have mastered the skills and knowledge deemed critical at each grade level. All easyCBM reading measures, in which the Reading Comprehension measure is included, have been developed with reference to the report of the National Reading Panel and developed using using Item Response Theory (IRT). In Grades 2–8, easyCBM provides three Reading Comprehension screening forms to be used locally for establishing benchmarks and 17 forms in Reading Comprehension to be used to monitor progress.

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:

The easyCBM Reading Comprehension measures are optimized for online administration but can also be taken using paper and pencil forms with teachers entering students' responses into the system after the test has been completed. The measures are designed for group administration (with the number of students limited only by the number of available computers/tablets and adults to supervise the testing environment.

ACADEMIC ONLY: What are the discontinue rules?

No discontinue rules provided
Basals
Ceilings
Other

If other, please specify:

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. In year one, there are three training webinars; one is provided at no charge and two cost $225 each.

Please describe the minimum qualifications an administrator must possess.

Administrators are expected to have basic student management skills and be familiar with using websites.

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:

Help desk via email and phone

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:

Please describe the scoring structure. Provide relevant details such as the scoring format, the number of items overall, the number of items per subscale, what the cluster/composite score comprises, and how raw scores are calculated.

Each subtest has its own score; these individual scores are not converted to a total composite score. The subtest total score is simply the total of all items correct. Raw scores are simply the total correct.

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

No

ACADEMIC ONLY: Do you provide benchmarks for the slopes?

No

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.

The authors have approached progress monitoring from two perspectives with respect to (a) goal level sampling from nationally framed standards and (b) scaling. Test format focuses on principles of universal design with either individually administered tasks (for early reading skills and fluency) or computer-based testing for group-administered tests in vocabulary, comprehension, and all mathematics tests. Scoring practices emphasize objectivity with diagnostic information for teachers and immediate feedback for students. In reading, the authors used the report from the National Reading Panel (NRP) to develop a full complement of tasks across the grade levels. easyCBM reading measures include phonemic awareness (letter names, letter sounds, and phoneme segmentation), phonics (word reading fluency), fluency (passage fluency), vocabulary (word meaning synonyms), and comprehension (multiple-choice narrative stories that have associated questions addressing literal, inferential, and evaluative understanding). From a scaling perspective, the authors used Item Response Theory (IRT) to design alternate forms for most measures (passage reading fluency is the only exception) so they are comparable. A common-person, common-item equating design was used to scale all items. Within specific skill areas (e.g., letter names, letter sounds, words in a list for word reading fluency, vocabulary, and comprehension), approximately 250 students responded to multiple item sets, and each test form contained items common across forms. The equated item scale scores and model fit statistics were used to (a) identify items of similar difficulty, (b) estimate student equated scores, and (c) remove/revise items of poor psychometric quality. The authors then placed the items into final alternate forms for progress monitoring so that each form included items with similar levels of difficulty. The authors generally placed easier items and interspersed common items near the beginning of the form, as many measures are timed, and students would then be assured of a sensitive measure for estimating their ability. N.B. IRT analyses were used to equate the forms but not to make the scales; rather, all outcomes are based on raw scores. A Technical Report detailing this process is available from the Center upon request. Reading tasks are grade level referenced. For all computer-based tests, the student administration is compatible with popular browsers (PC: Chrome, Internet Explorer, and Firefox, Mac: Safari, Chrome, and Firefox). Furthermore, the computer presentation was optimized for a clear presentation of the item, with large-option buttons to facilitate option selection, and ‘next’ buttons to assure easy navigation in moving forward or backward across questions. See the Technical Manual: easyCBM detailing this process (attached).

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?

No

If yes, specify the growth standards:

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

Yes

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

Spring norms based on representative national sample. See easyCBM Norms, 2014 Edition (attached).

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

2013-2014

Size

2000 per grade

Gender (Percent)

Male

50%

Female

50%

Unknown

SES indicators (Percent)

Eligible for free or reduced-price lunch

Other SES Indicators

Race/Ethnicity (Percent)

White, Non-Hispanic

50%

Black, Non-Hispanic

Hispanic

American Indian/Alaska Native

Asian/Pacific Islander

Other

50%

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.

Note: The authors also developed a set of norms using a stratified random sample of students by gender and ethnicity-race (white female, white male, non-white female, non-white male). Race and ethnicity were aggregated, as the count of students with complete data for both categories was insufficient for disaggregation. In this process, Hispanic students were counted as “non-white” even when lacking a race designation other than “white.”

Reliability

Grade	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Rating	d	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.

Internal consistency was investigated using Cronbach's Alpha, perhaps the most common measure of internal consistency. The authors supplemented these indices with split-half reliability estimates using all possible split-half comparisons. The mean of the split-half estimates are reported in the table below.

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

A large sample collected across the country was used for investigation. Measures from each of the fall, winter, and spring test windows were evaluated in Grades 3-8. The proportion of male students across grades varied from 50.8% to 52.4%. Across grades, approximately 3–4% of students identified as American Indian or Alaskan Native; 3–4% identified as Asian; 11–12% identified as Black or African American; 0–1% identified as Native Hawaiian or Other Pacific Islander; 5–10% identified as two or more races; 59–62% identified as White; and 10–16% were unknown or refused to report.

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

Item-level data were extracted from the easyCBM database. Correct responses were coded 1 while incorrect responses were coded 0. The psych package in R was used to calculate both indicators of internal consistency.

*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:

Yes

Provide citations for additional published studies.

Irvin, P. S., Alonzo, J., Lai, C. F., Park, B. J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 7 (technical report 1206). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Irvin, P. S., Alonzo, J., Park, B. J., Lai, C. F., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 6 (technical report 1205). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Lai, C. F., Irvin, P. S., Alonzo, J., Park, B. J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 2 (technical report 1201). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Lai, C. F., Irvin, P. S., Park, B. J., Alonzo, J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 3 (technical report 1202). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Park, B. J., Irvin, P. S., Alonzo, J., Lai, C. F., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 4 (technical report 1203). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Park, B. J., Irvin, P. S., Lai, C. F., Alonzo, J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 5 (technical report 1204). Eugene, OR: Behavioral Research and Teaching, University of Oregon.

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:

Yes

Provide citations for additional published studies.

Irvin, P. S., Alonzo, J., Lai, C. F., Park, B. J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 7 (technical report 1206). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Irvin, P. S., Alonzo, J., Park, B. J., Lai, C. F., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 6 (technical report 1205). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Lai, C. F., Irvin, P. S., Alonzo, J., Park, B. J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 2 (technical report 1201). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Lai, C. F., Irvin, P. S., Park, B. J., Alonzo, J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 3 (technical report 1202). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Park, B. J., Irvin, P. S., Alonzo, J., Lai, C. F., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 4 (technical report 1203). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Park, B. J., Irvin, P. S., Lai, C. F., Alonzo, J., & Tindal, G. (2012). Analyzing the reliability of the easyCBM reading comprehension measures: Grade 5 (technical report 1204). Eugene, OR: Behavioral Research and Teaching, University of Oregon.

Validity

Grade	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
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 reading portion of the Washington state summative test was used for all criterion-related validity evidence. Washington is part of the Smarter Balanced Assessment Consortium, and the corresponding state test was used.

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

The sample size for each grade is listed in the tables in item #4 below. Across grades, approximately 40–48% of students were male (7–21% missing data); 8–10% of students received special education services; 23–31% received free or reduced price lunch; and 6–10% received English language services.

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

Scores from each measure were correlated with their corresponding Smarter Balanced assessment scores. See pages 34–35 in the article, “The Relation Between easyCBM and Smarter Balanced Reading and Mathematics Assessments,” (available from the Center upon request) for plots of the relation.

*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:

Yes

Provide citations for additional published studies.

Tindal, G., Nese, J. F., & Alonzo, J. (2009). Criterion-related evidence using easyCBM® reading measures and student demographics to predict state test performance in grades 3-8 (technical report 0910). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Jamgochian, E. M., Park, B. J., Nese, J. F. T., Lai, C. F., Sáez, L., Anderson, D., et al. (2010). Technical adequacy of the easyCBM grade 2 reading measures (technical report 1004). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Sáez, L., Park, B. J., Nese, J. F. T., Jamgochian, E. M., Lai, C. F., Anderson, D., et al. (2010).Technical adequacy of the easyCBM reading measures (Grades 3-7), 2009-2010 version (technical report 1005). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Park, B. J., Alonzo, J., & Tindal, G. (2011). The development and technical adequacy of seventh-grade reading comprehension measures in a progress monitoring assessment system (Technical Report No. 1102). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Lai, C. F., Alonzo, J., & Tindal, G. (2013). easyCBM reading criterion related validity evidence: Grades 2-5 (technical report 1310). Eugene, OR: Behavioral Research and Teaching, University of Oregon.

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

Across the grades, the concurrent and predictive validity evidence is strong, ranging from 0.54 to 0.68. These values correspond to the easyCBM measures accounting for approximately 29-46% of the total variance in the statewide assessment.

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:

Yes

Provide citations for additional published studies.

Jamgochian, E.M., Park, B.J., Nese, J.F.T, Lai, C.F., Anderson, D. Alonzo, J. & TINFAL, G. (2010). Technical adequacy of the easyCBM grade 2 reading measures, 2009-2010 version. (Technical Report #1004). Eugene, OR: Behavioral Research and Teaching. Sáez, L., Park, B.J., Nese, J.F.T, Jamgochian, E.M., Lai, C.F., Anderson. D. Alonzo, J., & Tindal, G. (2010) Techincal Adequacy of the easyCBM reading measures (Grades 3-8), 2009-2010 Version. (Technical Report #1005). Eugene, OR: Behavioral Research and Teaching.

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:

To investigate Differential Item Functioning (DIF) of the easyCBM reading measures, the Mantel-Haenszel test using a purification process was conducted (Holland & Thayer, 1988; Kamata & Vaughn, 2004) with the R software using the difR package (Magis et al., 2013). When using the Mantel-Haenszel test to investigate DIF, contingency tables are constructed, and the resulting odds for the focal group answering the item correctly are compared to the odds for the reference group. The contingency table summarizes correct and incorrect responses to each item by respondents’ total raw score by subgroup (Kamata & Vaughn, 2004). If there is no difference in performance for the two groups, the odds ratio of the focal group performance to reference group performance will equal one. An odds ratio greater than one means the focal group is performing better than the reference group, with the opposite being true for odds ratios less than one. The difR package contains a built in algorithm to conduct purification automatically. We used criteria outlined by the Educational Testing Service (ETS) for DIF Classification (Holland & Thayer, 1988) to determine whether or not items exhibited DIF, as the difR package reports delta values by default, defined as: ∆_MH=2.35*ln⁡(a_mh) where ln⁡(a_mh )= β_MH.The Holland and Thayer criteria for ∆_MH is as follows: |∆_MH |<1.0="A\" items,1 ≤ " |"∆" _"MH" |"<1.5=\"" B" items,and |∆_MH | ≥2.5="C" items The Holland and Thayer criteria were used for all Mantel-Haenszel analyses. It was determined a priori that any items that were flagged as “B” level items would be reviewed by the item development team for potential biases and possible removal. All items flagged as “C” level items would be removed from the operational pool. All operational items from 2016-17 were included in the analyses.

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

The easyCBM MCRC DIF analyses compared Male/Female, White/Non-White, and Non-Hispanic-Latino/Hispanic-Latino subgroups. Male, White, and Non-Hispanic-Latino were the reference groups, respectively. Sample sizes ranged from 23,000–35,000 students. Full sample statistics are published in the technical report, which is available from the Center upon request.

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, easyCBM reading items are functioning in a manner that appears not to exhibit bias based on the demographic characteristics reviewed. Across all MCRC grade levels, no items were assigned to the “C” level, denoting large effect size differences between subgroups. In the Male/Female comparisons, 98% of items were assigned to the “A” level DIF category (352/360). In the White/Non-White comparisons, 99% of items were assigned to the “A” level DIF category (358/360). In the Non-Hispanic-Latino/ Hispanic-Latino comparisons, 100% of items were assigned to the “A” level DIF category (360/360). The “A” level categorizations are labeled as negligible DIF by the ETS delta criteria.

Sensitivity: Reliability of Slope

Grade	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Rating	d	d	d	d	d	d

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.

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 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:

Yes

Provide citations for additional published studies.

Jamgochian, E.M., Park, B.J., Nese, J.F.T., Lai, C.F., Sáez, L., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM grade 2 reading measures, 2009-2010 version. (Technical Report #1004). Eugene, OR: Behavioral Research and Teaching. Sáez, L , Park, B.J., Nese, J.F.T, Jamgochian, E.M., Lai, C.F., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM reading measures (Grades 3-8), 2009-2010 Version. (Technical Report #1005). Eugene, OR: Behavioral Research and Teaching

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)?

Yes

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:

Yes

Provide citations for additional published studies.

Jamgochian, E.M., Park, B.J., Nese, J.F.T., Lai, C.F., Sáez, L., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM grade 2 reading measures, 2009-2010 version. (Technical Report #1004). Eugene, OR: Behavioral Research and Teaching. Sáez, L , Park, B.J., Nese, J.F.T, Jamgochian, E.M., Lai, C.F., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM reading measures (Grades 3-8), 2009-2010 Version. (Technical Report #1005). Eugene, OR: Behavioral Research and Teaching.

Sensitivity: Validity of Slope

Grade	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Rating	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 reading portion of the Washington summative state test was used for all criterion-related validity evidence. Washington is part of the Smarter Balanced Assessment Consortium, and the corresponding state test was used.

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 size for each grade is described in the table in item #4 below. Across grades, approximately 40–48% of students were male (7–21% missing data); 8–10% of students received special education services; 23–31% received free or reduced price lunch; and 6–10% received English language services.

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

Assessments were collected during the fall, winter, and spring of the academic school year.

Describe the analysis procedures for each reported type of validity.

Data were split into quartiles of normative achievement based on students’ fall benchmark. A two-level growth model was then fit to the data for each quartile within each grade, with measurement occasions nested in students. The random effect estimates for the students’ slope were then extracted and correlated with their corresponding Smarter Balanced Assessment scores. We conducted analyses separately by quartile to ensure students’ growth was referenced to students with similar initial achievement.

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:

Yes

Provide citations for additional published studies.

Jamgochian, E.M., Park, B.J., Nese, J.F.T., Lai, C.F., Sáez, L., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM grade 2 reading measures, 2009-2010 version. (Technical Report #1004). Eugene, OR: Behavioral Research and Teaching. Sáez, L , Park, B.J., Nese, J.F.T, Jamgochian, E.M., Lai, C.F., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM reading measures (Grades 3-8), 2009-2010 Version. (Technical Report #1005). Eugene, OR: Behavioral Research and Teaching.

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

Typically, measures of growth correlate far less strongly with criterion measures than do measures of status. When comparing growth estimates within quartiles, and thus to students with similar initial achievement, the correlations were moderate, providing good evidence for the validity of the slope for informing instructional decisions.

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)?

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:

Yes

Provide citations for additional published studies.

Jamgochian, E.M., Park, B.J., Nese, J.F.T., Lai, C.F., Sáez, L., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM grade 2 reading measures, 2009-2010 version. (Technical Report #1004). Eugene, OR: Behavioral Research and Teaching. Sáez, L , Park, B.J., Nese, J.F.T, Jamgochian, E.M., Lai, C.F., Anderson, D., Alonzo, J., & Tindal, G. (2010) Technical adequacy of the easyCBM reading measures (Grades 3-8), 2009-2010 Version. (Technical Report #1005). Eugene, OR: Behavioral Research and Teaching.

Alternate Forms

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

Legend

Convincing evidence

Partially convincing evidence

Unconvincing evidence

Data unavailable

^dDisaggregated data available

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

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

Initially, items were piloted using a common person / common item design to create an item bank with known item parameters (measure, mean square outfit, standard error, etc.). Using this data, the authors then distributed items across the multiple forms (3 screening forms to be administered in the fall, winter, and spring and 17 progress monitoring) to have approximately equal item measure estimates and comparable ranges. The comparability of each of the alternate forms was tested with grade-level students, using repeated measures ANOVA to test for form differences. Results of these studies are reported in the technical reports documenting the development of the measures: Alonzo, J., Liu, K., & Tindal, G. (2008). Examining the technical adequacy of second-grade reading comprehension measures in a progress monitoring assessment system (Technical Report No. 0808). Eugene, OR: Behavioral Research and Teaching, University of Oregon. TechRpt_0808 Alonzo, J., Liu, K., & Tindal, G. (2007). Examining the technical adequacy of reading comprehension measures in a progress monitoring assessment system (Technical Report No. 41). Eugene, OR: Behavioral Research and Teaching, University of Oregon. TechRpt_41 Alonzo, J., & Tindal, G. (2008). Examining the technical adequacy of fifth-grade reading comprehension measures in a progress monitoring assessment system (Technical Report No. 0807). Eugene, OR: Behavioral Research and Teaching, University of Oregon.TechRpt_0807 Alonzo, J., & Tindal, G. (2009). Alternate form and test-retest reliability of easyCBM® reading measures (Technical Report No. 0906). Eugene, OR: Behavioral Research and Teaching, University of Oregon.

If IRT based, provide evidence of item or ability invariance

The technical reports cited throughout this submission document provide evidence of item invariance, along with a variety of other information.

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 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
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 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
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.