i-Ready® Diagnostic
Reading

Descriptive Information

Please provide a description of your tool:

Offering a continuum of scale scores from kindergarten through high school, i Ready Diagnostic is a web-based adaptive screening assessment for reading. Evidence-based, proven valid and reliable, and aligned to state and Common Core standards, i-Ready meets the expected rigor in each of the covered domains—Phonological Awareness, Phonics, High-Frequency Words, Vocabulary, Comprehension of Informational Text, and Comprehension of Literature—providing actionable data and reports for each domain. Screening is administered up to three times per academic year, with 12-18 weeks of instruction between assessments. Each screening takes approximately 30-60 minutes—which may be broken into multiple sittings—and may be conducted with all students or with specific groups of students who have been identified as at risk of academic failure. i-Ready’s sophisticated adaptive algorithm automatically selects from thousands of technology-enhanced and multiple-choice items to get to the core of each student's strengths and challenges, regardless of the grade level at which he or she is performing. The system automatically analyzes, scores, and reports student responses and results. Available as soon as a student completes the assessment, i Ready’s intuitive reports provide comprehensive information (including developmental analyses) about student performance, group students who struggle with the same concepts, make instructional recommendations to target skill deficiencies, and monitor progress and growth as students follow their individualized instructional paths. Reports include suggested next steps for instruction and PDF Tools for Instruction lesson plans for the teacher to use during individual, small-group, or whole-class instruction. In addition, should educators also purchase the optional i Ready Instruction, the system automatically prescribes online lessons that address each student’s identified academic needs.

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):

multimedia items, drag and drop, and highlight items; a number of items use audio for phonics, phonological awareness, high-frequency words, and grade K vocabulary and comprehension passages

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:

Five domains are assessed within i Ready Growth Monitoring for reading; each domain has corresponding sub-domains. The topics addressed in the Phonological Awareness domain are: rhyme recognition; phoneme identity and isolation; phoneme blending and segmentation; phoneme addition and substitution; and phoneme deletion. The topics addressed in the Phonics and Word Recognition domain are: letter recognition; consonant sounds; short and long vowels; decoding one- and two-syllable words; inflectional endings; prefixes and suffixes; digraphs and diphthongs; vowel patterns; decoding longer words; and high-frequency words. The topics addressed in the Vocabulary domain are: academic and domain-specific vocabulary; word relationships; word-learning strategies; use of reference materials; prefixes; suffixes; and word roots. The topics addressed in the Comprehension of Informational Text domain are: author’s purpose; categorize and classify; cause and effect; drawing conclusions/making inferences; fact and opinion; main idea and details; message; summarize; text structure; vocabulary in context; compare and contrast across different mediums; analysis of close reading of the text; and citing textual evidence. The topics addressed in the Comprehension of Literature domain are: author’s purpose; cause and effect; drawing conclusions/making inferences; figurative language; story structure; summarize; theme/mood; understanding character; vocabulary in context; compare and contrast across different mediums; analysis of close reading of the text; and citing textual evidence.

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

Internalizing
Externalizing
Internalizing and Externalizing

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

Acquisition and Cost Information

Where to obtain:

Email Address

info@cainc.com

Address

153 Rangeway Road, N. Billerica MA 01862

Phone Number

800-225-0248

Website

www.curriculumassociates.com

Initial cost for implementing program:

Cost

$6.00

Unit of cost

student

Replacement cost per unit for subsequent use:

Cost

$6.00

Unit of cost

student

Duration of license

year

Additional cost information:

Describe basic pricing plan and structure of the tool. Provide information on what is included in the published tool, as well as what is not included but required for implementation.

$6.00/student/year for i-Ready Diagnostic for reading. Annual license fee includes online student access to assessment, plus staff access to management and reporting suite, downloadable lesson plans, and user resources including i-Ready Central support website; account set-up and secure hosting; all program maintenance/ updates/ enhancements during the active license term; unlimited user access to U.S.-based service and support via toll-free phone and email during business hours. Professional development is required and available at an additional cost ($2,000/session up to six hours)

Provide information about special accommodations for students with disabilities.

i Ready Diagnostic is a fully web-based, vendor-hosted, Software-as-a-Service application. The per-student or site-based license fee includes account set-up and management; unlimited access to i-Ready’s assessment, management, and reporting functionality; plus unlimited access to U.S.-based customer service/technical support and all program maintenance, updates, and enhancements for as long as the license remains active. The license fee also includes hosting, data storage, and data security. Via the i-Ready teacher and administrator dashboards and i-Ready Central support website, educators may access comprehensive user guides and downloadable lesson plans, as well as implementation tips, best practices, video tutorials, and more to supplement onsite, fee-based professional development. These resources are self-paced and available 24/7. Curriculum Associates engaged an independent consultant to thoroughly evaluate i Ready Diagnostic’s accessibility and provide some recommendations regarding how best to support the broadest possible range of student learners. Overall, the report found that i-Ready “materials included significant functionality that indirectly supports… students with disabilities.” The report also indicated ways to support these groups of students more directly, which we are in the process of prioritizing for future development. We are committed to meaningful ongoing enhancement and expansion of the program’s accessibility. Diverse student groups experience success with the program largely due to its adaptive nature and program design. All items in i-Ready Diagnostic are designed to be accessible for most students. In a majority of cases, students who require accommodations (e.g., large print, extra time) will not require additional help during administration. The thoughtful planning Curriculum Associates invested in the general assessment design ensures that a large percentage of students requiring accommodations will have the necessary adjustments without compromising the interpretation or purpose of the test. To address the elements of Universal Design as they apply to large-scale assessment (http://www.cehd.umn.edu/nceo/onlinepubs/Synthesis44.html), in developing i-Ready Diagnostic Curriculum Associates considered several issues related to accommodations. Most may be grouped into the following general categories that i Ready addresses: • Timing—Students may need extra time to complete the task. The Diagnostic assessment may be stopped and started as needed to allow students needing extra time to finish. The Diagnostic is untimed and can be administered in multiple test sessions. In fact, to ensure accurate results, a time limit is not recommended for any student, though administration must be completed within a period of no longer than 22 days. • Flexible Scheduling—Students may need multiple days to complete the assessment. i-Ready recommends that all students be given multiple days, as necessary, to complete the test (as noted above, administration must be completed within a period of no longer than 22 days). • Accommodated Presentation of Material—All i-Ready Diagnostic items are presented in a large, easily legible format specifically chosen for its readability. i Ready currently offers the ability to change the screen size; with the coming HTML5 items slated for a future release, users will be able to adjust the font size. There is only one item on the screen at a time. As appropriate to the skill(s) being assessed, some grade levels K–2 reading items also offer optional audio support. • Setting—Students may need to complete the task in a quiet room to minimize distraction. This can easily be done, as i-Ready Diagnostic is available on any computer with internet access that meets the technical requirements. Furthermore, all students are encouraged to use quality headphones in order to hear the audio portion of the items. Headphones also help to cancel out peripheral noise, which can be distracting to students. • Response Accommodation—Students should be able to control a mouse. They only need to be able to move a cursor with the mouse and be able to point, click, and drag. We are moving toward iPad® compatibility (see updates at www.i-Ready.com/support), with a beta expected in 2017-2018. This would mean touchscreen, which is potentially easier for those with motor impairments. Some schools report that they have successfully used i-Ready Diagnostic with a screen reader or other assistive technologies, but we cannot certify those applications at this time.

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

45

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:

Are norms available?

Yes

Are benchmarks available?

Yes

If yes, how many benchmarks per year?

Up to three. There is no fixed form in i-Ready designed specifically as a benchmark. Curriculum Associates recommends giving the assessment three times a year. These tests are equivalent to benchmark tests. i-Ready provides different views for the intervention screener for scale scores students should achieve to be considered as Tier 1, Tier 2, or in danger of Tier 3.

If yes, for which months are benchmarks available?

September, January/February, and April/May

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

If yes, how many students can be rated concurrently?

Training & Scoring

Training

Is training for the administrator required?

Yes

Describe the time required for administrator training, if applicable:

4-8 hours of training

Please describe the minimum qualifications an administrator must possess.

professional, paraprofessional

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:

Onsite professional development also required and available for an additional cost

Can users obtain ongoing professional and technical support?

Yes

If Yes, please describe how users can obtain support:

Dedicated account manager plus unlimited access to in-house technical support during business hours

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:

on-grade achievement level placements

Does your tool include decision rules?

If yes, please describe.

Can you provide evidence in support of multiple decision rules?

No

If yes, please describe.

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

i-Ready Diagnostic scale scores are linear transformations of logit values. Logits, also known as “log odd units,” are measurement units for logarithmic probability models such as the Rasch model. Logit is used to determine both student ability and item difficulty. Within the Rasch model, if the ability matches the item difficulty, then the person has a .50 chance of answering the item correctly. For i-Ready Diagnostic, student ability and item logit values generally range from around -6 to 6. When the i-Ready vertical scale was updated in August 2016, the equipercentile equating method was applied to the updated logit scale. The appropriate scaling constant and slope were applied to the logit value to convert to scale score values between 100 and 800 (Kolen and Brennan, 2014). This scaling is accomplished by converting the estimated logit values with the following equations: Scale Value = 499.38 + 37.81 × Logit Value Once this conversion is made, floor and ceiling values are imposed to keep the scores within the 100–800 scale range. This is achieved by simply recoding all values below 100 up to 100 and all values above 800 down to 800. The scale score range, mean, and standard deviation on the updated scale are either exactly the same as (range), or very similar (mean and standard deviation) to those from the scale prior to the August 2016 scale update, which generally allows year-over-year comparisons of i-Ready scale scores.

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.

i-Ready Diagnostic has Response to Intervention (RTI) screening reports that categorize students into three colors: green is on track, yellow identifies Tier 2 students, and red identifies students in danger of being Tier 3. There are three screening reports: beginning-of-year, standard, and end-of-year. Depending on the achievement level placement of the student, he or she is designated into one of the three levels based on chronological grade level. For beginning-of-year, red is more than two levels below, yellow is two levels below, and green is one level below and any placement above that. For the standard report, red is two or more levels below, yellow is one level below, and green is early-on level or any placement above that. For the end-of-year report, red is one or more levels below, yellow is early-on level, and green is mid-on level or any placement above that. It is recommended that students categorized as red receive the most intensive intervention, those categorized as yellow receive intervention services, and those categorized as green continue in their instructional path. In addition, i-Ready provides national norms (as percentiles) for beginning-of-year, mid-year, and end-of-year testing. Test users who are more familiar with the percentile-based screening approach could also use the national norms for RTI classification. Curriculum Associates is committed to fair and unbiased product development. i-Ready is developmentally, linguistically, and culturally appropriate for a wide range of students at each of grade. For instance, the names, characters, and scenarios used within the programs—as well as the “study buddies” who act as onscreen guides for students—are ethnically and culturally diverse. We developed all items in i-Ready to be accessible for most students regardless of their need for accommodation. In most cases, students who require accommodations (e.g., large print or extra time) will not require additional help to complete an i-Ready assessment. The design of the assessment emphasizes making necessary adjustments to the items, so that a large percentage of students requiring accommodations will be able to take the test in a standard manner and the interpretation or the purpose of the test is not compromised. According to the Standards (AERA, APA, NCME, 2014), “Universal Design processes strive to minimize access challenges by taking into account test characteristics that may impede access to the construct for certain test takers.” i-Ready Diagnostic was developed with the universal principles of design for assessment in mind and followed the seven elements of Universal Design for large-scale assessments recommended by NCEO (2002): 1. Inclusive assessment population 2. Precisely defined constructs 3. Accessible, non-biased items 4. Amenable to accommodations 5. Simple, clear, and intuitive instructions and procedures 6. Maximum readability and comprehensibility 7. Maximum legibility Differential Item Function (DIF) was investigated using WINSTEPS® by comparing the item difficulty measure for two demographics categories in a pairwise comparison. The following demographic categories were compared: Female vs. Male; African American and Hispanic vs. Caucasian; South, West, and Northeast vs. Midwest; English learner vs. non–English learner; Special Ed vs. General Ed; Economically disadvantaged vs. Not economically disadvantaged. In each pairwise comparison, estimates of item difficulty for each category in the comparison were calculated. The difference between the two groups was then evaluated using both the Welch’s t-statistics and Mantel-Haenszel method. Items with significant and large differences in difficulty between the comparison groups were flagged for content inspection. In reading, of the 3,117 items evaluated, only three percent showed significant DIF, with one percent showing large DIF. Items with large and significant DIF are retired or replaced. Items with significant, but small, DIF are subjected to extensive content review by a committee, who then determine whether each item should remain in the operational pool, be removed, or be revised and re-piloted.

Classification Accuracy & Cross-Validation Summary

Grade	Kindergarten	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

SBAC

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 percentile scores defined by 2016 SBAC assessments are used to classify students at grade 3-8. Students who were below 30th percentile on the SBAC test were classified as at-risk and students who were at or above 30th percentile were classified as no-risk.

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 i-Ready cut scores were determined at the 20th percentile for each grade level using the i-Ready National Norms. Using these cut scores, students were identified as at-risk if they were below the 20th percentile on the fall i-Ready Diagnostic test or no-risk if they scored at or above the cut. Classification indices between at-risk/no-risk on i-Ready and at-risk/no-risk on the SBAC assessment are calculated per the formulas in the classification worksheet.

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.

---

DIBELS NEXT

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 scores of DIBELS assessment are used to classify students at grade K-2. Students who were below the level of “Likely to Receive Intensive Support” were classified as at-risk and students who were at or above that cut score were classified as no-risk.

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 i-Ready cut scores were determined at the 20th percentile for each grade level using the i-Ready National Norms. Using these cut scores, students were identified as at-risk if they were below the 20th percentile on the fall i-Ready Diagnostic test or no-risk if they scored at or above the cut.

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?

Yes

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.

K-2: Selected scale scores of DIBELS assessments are used to classify students at grade K-2. Specifically, for grades 1 and 2, students who were below the level of “Likely to Receive Intensive Support” were classified as at-risk and students who were at or above that cut score were classified as no-risk. For Kindergarten, consistent with Curriculum Associates’ guidance on screening, a higher DIBELS score is used to guard against incorrectly identifying students in need of intervention as being sufficiently proficient

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).

The i-Ready cut scores were determined at the 20th percentile for each grade level using the on i-Ready National Norms. Using these cut scores, students were identified as at-risk if they were below the 20th percentile in the fall i-Ready Diagnostic test or no-risk if they scored at or above the cut. Classification indices between the at-risk/no-risk on i-Ready and at-risk/no-risk on the NYS assessment are calculated per the formulas in the classification worksheet. AUC values are calculated using the Risk/No-Risk categories on the criterion (outcome) measure as the dependent variable and the i-Ready score as the independent variable.

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.

---

New York State Testing Program (NYSTP)

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.

3-8: The estimated 30th percentile scores based on the publicly released percentile score ranges are used to classify students. Students who were below the grade-level cut scores on the NYS test were classified as at-risk and students who were at or above the cut scores were classified as no-risk.

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 i-Ready cut scores were determined at the 20th percentile for each grade level using the on i-Ready National Norms. Using these cut scores, students were identified as at-risk if they were below the 20th percentile in the fall i-Ready Diagnostic test or no-risk if they scored at or above the cut. Classification indices between the at-risk/no-risk on i-Ready and at-risk/no-risk on the NYS assessment are calculated per the formulas in the classification worksheet. AUC values are calculated using the Risk/No-Risk categories on the criterion (outcome) measure as the dependent variable and the i-Ready score as the independent variable.

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.

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Classification Accuracy - Fall

Evidence	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Criterion measure	DIBELS NEXT	DIBELS NEXT	DIBELS NEXT	SBAC	SBAC	SBAC	SBAC	SBAC	SBAC
Cut Points - Percentile rank on criterion measure
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	328.00	370.00	421.00	463	486	509	528	542	555
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)	0.75	0.87	0.93	0.93	0.94	0.94	0.94	0.94	0.94
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.72	0.85	0.92	0.93	0.93	0.94	0.94	0.93	0.93
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.78	0.89	0.94	0.94	0.93	0.95	0.95	0.94	0.95

Statistics	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Date	2016-2017	2016-2017	2016-2017	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016
Sample Size
Geographic Representation
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	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Criterion measure	DIBELS NEXT	DIBELS NEXT	DIBELS NEXT	SBAC	SBAC	SBAC	SBAC	SBAC	SBAC
Cut Points - Percentile rank on criterion measure
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	347	397	444	480	500	520	539	550	562
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)			0.93	0.93	0.94	0.93	0.94	0.93	0.93
AUC Estimate’s 95% Confidence Interval: Lower Bound			0.92	0.93	0.94	0.93	0.93	0.92	0.93
AUC Estimate’s 95% Confidence Interval: Upper Bound			0.95	0.94	0.95	0.94	0.93	0.93	0.94

Statistics	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Date	Spring, 2017	Spring, 2017	Spring 2017	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016
Sample Size
Geographic Representation
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	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Criterion measure	DIBELS NEXT	DIBELS NEXT	DIBELS NEXT	SBAC	SBAC	SBAC	SBAC	SBAC	SBAC
Cut Points - Percentile rank on criterion measure
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	367	416	464	491	505	526	543	553	567
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)	0.80		0.92	0.94	0.95	0.94	0.94	0.93	0.93
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.77		0.90	0.94	0.94	0.93	0.94	0.92	0.92
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.83		0.93	0.95	0.95	0.93	0.95	0.93	0.94

Statistics	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Date	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016	Spring 2016
Sample Size
Geographic Representation
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

Cross-Validation - Fall

Evidence	Kindergarten	Grade 1	Grade 2
Criterion measure	DIBELS NEXT	DIBELS NEXT	DIBELS NEXT
Cut Points - Percentile rank on criterion measure	20	20	20
Cut Points - Performance score on criterion measure	328.00	370.00	421.00
Cut Points - Corresponding performance score (numeric) on screener measure
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)	0.73	0.88	0.94
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.71	0.87	0.94
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.74	0.89	0.95

Statistics	Kindergarten	Grade 1	Grade 2
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1	Grade 2
Date	2016-2017	2016-2017	2016-2017
Sample Size
Geographic Representation
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

Cross-Validation - Winter

Evidence	Kindergarten	Grade 1	Grade 2
Criterion measure	DIBELS NEXT	DIBELS NEXT	DIBELS NEXT
Cut Points - Percentile rank on criterion measure
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	347	397	444
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)			0.95
AUC Estimate’s 95% Confidence Interval: Lower Bound			0.94
AUC Estimate’s 95% Confidence Interval: Upper Bound			0.95

Statistics	Kindergarten	Grade 1	Grade 2
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1	Grade 2
Date	Spring 2017	Spring 2017	Spring 2017
Sample Size
Geographic Representation
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

Cross-Validation - Spring

Evidence	Kindergarten	Grade 1	Grade 2
Criterion measure	DIBELS NEXT	DIBELS NEXT	DIBELS NEXT
Cut Points - Percentile rank on criterion measure
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	367	416	464
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC)	0.73		0.94
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.71		0.94
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.74		0.95

Statistics	Kindergarten	Grade 1	Grade 2
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1	Grade 2
Date	Spring 2017	Spring 2017	Spring 2017
Sample Size
Geographic Representation
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	Kindergarten	Grade 1	Grade 2	Grade 3	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8
Rating		d	d	d	d	d	d	d	d

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

The i-Ready Diagnostic provides two types of reliability estimates: • IRT-based reliability measures such as the marginal reliability estimate and standard error of measurement. • Test-retest reliability coefficients. Marginal Reliability: Given that the i-Ready Diagnostic is a computer-adaptive assessment that does not have a fixed form, some traditional reliability estimates such as Cronbach’s alpha are not an appropriate index for quantifying consistency or inconsistency in student performance. The IRT analogue to classical reliability is called marginal reliability, and operates on the variance of the theta scores and the average of the expected error variance. The marginal reliability uses the classical definition of reliability as proportion of variance in the total observed score due to true score under an IRT model (the i-Ready Diagnostic uses a Rasch model to be specific). Standard Error of Measurement (SEM): In an IRT model, SEMs are affected by factors such as how well the data fit the underlying model, student response consistency, student location on the ability continuum, match of items to student ability, and test length. Given the adaptive nature of i-Ready and the wide difficulty range in the item bank, standard errors are expected to be low and very close to the theoretical minimum for the test of the given length. The theoretical minimum would be reached if each interim estimate of student ability is assessed by an item with difficulty matching perfectly to the student’s ability estimated from previous items. Theoretical minimums are restricted by the number of items served in the assessment—the more items that are served up, the lower the SEM could potentially be. For ELA, the minimum SEM for overall scores is 8.9. The Center also possesses graphical representations of the conditional standard errors of measurement (CSEM) that provide additional evidence of the precision with which i-Ready measures student ability across the operational score scale. In the context of model-based reliability analyses for computer adaptive tests, such as i Ready, CSEM plots permit test users to judge the relative precision of the estimate. These figures, which help contextualize the table of reliability analysis results, are available from the Center upon request. Test-retest Reliability: The i-Ready Diagnostic is often used as an interim assessment, and students can take the assessment multiple times a year. Therefore, the test-retest reliability estimate is appropriate to provide stability estimates for the same students who took two Diagnostic tests.

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

Data for obtaining the marginal reliability and SEM was from the August and September administrations of the i-Ready Diagnostic from 2016 (reported in the 2016 i-Ready Diagnostic technical report). All students tested within the time-frame were included. Sample size by grade are presented in the table below. Evidence of test-retest stability was assessed based on a sub-sample of students who, during the 2016–2017 school year, took i-Ready Diagnostic twice within the recommended 12–18-week testing window. The average testing interval is 106 days (15 weeks). Sample sizes by grade are presented in the table below .

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

This marginal reliability uses the classical definition of reliability as proportion of variance in the total observed score due to true score. The true score variance is computed as the observed score variance minus the error variance (see equation below). ρ_θ=(σ_(θ-)^2 σ ̅_E^2)/(σ_θ^2 ) where ρθ is the marginal reliability estimate, σ2θ is the observed error variance of the ability estimate, σ ̅_E^2is the observed average conditional error variance. Similar to a classical reliability coefficient, the marginal reliability estimate increases as the standard error decreases; it approaches 1 when the standard error approaches 0. The observed score variance, the error variance, and SEM (the square root of the error variance) are obtained through WINSTEPS calibrations. One separate calibration was conducted for each grade. For test-retest reliability, Pearson correlation coefficients were obtained between scores for the two Diagnostic tests. Correlations between the two Diagnostic tests were calculated. In lower grades where growth and variability are expected to be higher, test-retest correlations are expected to be relatively lower.

*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)?

Yes

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	Kindergarten	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 internal structure of the i-Ready Diagnostic assessments is supported by the construct maps and the ordering of the skills addressed at different stages on the map. We recognize that coverage of skills and difficulty of items will overlap a fair amount across grades, as much material is reviewed from year to year. However, what should be apparent from the estimated item difficulties is that, generally, items measuring skills targeting lower levels of the map should be easier, and items measuring skills targeting higher levels of the map should be more difficult.

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

Active items in the current item pool for the 2016–2017 school year are included in the analysis for interval validity. The number of items per grade is listed in the table below

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

Distributions of indicator difficulties by grade level provide further evidence of internal structure. The difficulty of an indicator corresponds to a 67% probability of passing on the Indicator Characteristic Curve aggregated across all items aligned to the indicator. The table below shows the average and standard deviation of indicator difficulties.

*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:

*Lexile grade-banded results are featured, rather than grade-specific results. The i-Ready Diagnostic reading scale scores are created on a vertical scale which makes the scale scores comparable across grades. Thus, for efficiency purposes, the linking sample for the Lexile study includes only students from every other grade (i.e., grades 1, 3, 5, and 7), but results are generalized across grades in various grade bands (e.g., K-2). Additional information on the Lexile study, which was conducted in concert with MetaMetrics, is available upon request. The table below shows evidence of internal validity represented by indicator difficulty. The mean and standard deviation, as well as the number of items are presented by grade. Results show that items targeting progressively higher grade levels are progressively more difficult, as indicated by the aggregate difficulty of the indicator. Differences in item difficulties between the upper grades are less dramatic than such differences between the lower grades, which reflects the reality of student performance in the classroom. Validity Grade ID(Mean) ID (SD) Number of Items Internal K 383.48 29.65 439 Internal 1 440.77 37.41 430 Internal 2 502.63 40.37 316 Internal 3 524.97 33.99 302 Internal 4 562.71 21.72 225 Internal 5 583.54 19.13 224 Internal 6 601.60 17.77 244 Internal 7 616.77 19.70 253 Internal 8 627.24 14.34 253

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 internal structure of the i-Ready Diagnostic assessments is supported by the construct maps and the ordering of the skills addressed at different stages on the map. Skills representing the lower levels on the construct map are those generally associated with items targeted at lower grade levels, and skills representing the higher levels on the map are ones generally associated with items targeted at higher grade levels.

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

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:

Provide citations for additional published studies.

Bias Analysis

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

Have you conducted additional analyses related to the extent to which your tool is or is not biased against subgroups (e.g., race/ethnicity, gender, socioeconomic status, students with disabilities, English language learners)? Examples might include Differential Item Functioning (DIF) or invariance testing in multiple-group confirmatory factor models.

Yes

If yes,

a. Describe the method used to determine the presence or absence of bias:

Differential Item Function (DIF) was investigated using WINSTEPS® by comparing the item difficulty measure for two demographic categories in a pairwise comparison through a combined calibration analysis. The essence of this methodology is to investigate the interaction of the person-groups with each item, while fixing all other item and person measures to those from the combined calibration. The method used to detect DIF is based on the Mantel-Haenszel procedure (MH), and the work of Linacre & Wright (1989) and Linacre (2012). Typically, the group representing test takers in a specific demographic group is referred to as the focal group. The group made up of test takers from outside this group is referred to as the reference group. For example, for gender, Female is the focal group, and Male is the reference group.

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

The latest large-scale DIF analysis included a random sample (10%) of students from the 2015–2016 i-Ready operational data. Given the large size of the 2015–2016 i-Ready student population, it is practical to carry out the calibration analysis with a random sample. The following demographic categories were compared: Female vs. Male; African American and Hispanic vs. Caucasian; English Learner vs. non–English Learner; Special Ed vs. General Ed; Economically Disadvantaged vs. Not Economically Disadvantaged. In each pairwise comparison, estimates of item difficulty for each category in the comparison were calculated.

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.

Active items in the current item pool for the 2016–2017 school year are included in the DIF analysis. The total numbers of items are 3649 for ELA. WINSTEPS (Version 3.92) was used to conduct the calibration for DIF analysis by grade. To help interpret the results, the Educational Testing Service (ETS) criteria using the delta method was used to categorize DIF (Zwick, Thayer, & Lewis, 1999).