Star
Reading

Summary

Star Reading is a computer-adaptive, interim assessment of reading comprehension and overall reading achievement for students in grades 1 through 12. The tool provides information on student performance in 46 reading skill areas in 11 domains.

Where to Obtain:
Renaissance Learning
answers@renaissance.com
Renaissance Learning, PO Box 8036, Wisconsin Rapids, WI 54495
(800) 338-4204
http://www.renaissance.com
Initial Cost:
Contact vendor for pricing details.
Replacement Cost:
Contact vendor for pricing details.
Included in Cost:
There is a one-time setup fee along with a per student subscription fee. Total cost will depend on the number of schools and students. Please contact: answers@renaissance.com or (800) 338-4204 for specific details on pricing for your district. Star Reading is cloud-based and purchase includes the tool, software/technical manual, installation guide, testing instructions, and remote installation and setup.
Star Reading is a computer-adaptive assessment, and the difficulty of items presented is adjusted automatically to reflect the skill level of the student. Students may use the keyboard or the mouse, accommodating students with limited motor skills. Star Reading offers several accommodations for students with disabilities through the accessibility options built into a computer's operating system. For students with limited vision, the introductory screens of Star Reading respond to the "high contrast" accessibility feature within Windows and the "switch to black and white" accessibility feature in Mac OS. The assessment screens within Star Reading already provide visual contrast through a yellow background and black writing. Furthermore, Star Reading is compatible with Mac’s "zoom in" accessibility feature, which allows users to magnify nearly all Star Reading screens
Training Requirements:
Less than 1 hour of training
Qualified Administrators:
No minimum qualifications specified.
Access to Technical Support:
Renaissance Technical Support Staff
Assessment Format:
  • Direct: Computerized
  • Other: Group administered
Scoring Time:
  • Scoring is automatic
Scores Generated:
  • Percentile score
  • Grade equivalents
  • IRT-based score
  • Normal curve equivalents
  • Equated
  • Lexile score
  • Other: Instructional Reading Level, scale score
Administration Time:
  • 18 minutes per student/group
Scoring Method:
  • Automatically (computer-scored)
Technology Requirements:
  • Computer or tablet
  • Internet connection
Accommodations:
Star Reading is a computer-adaptive assessment, and the difficulty of items presented is adjusted automatically to reflect the skill level of the student. Students may use the keyboard or the mouse, accommodating students with limited motor skills. Star Reading offers several accommodations for students with disabilities through the accessibility options built into a computer's operating system. For students with limited vision, the introductory screens of Star Reading respond to the "high contrast" accessibility feature within Windows and the "switch to black and white" accessibility feature in Mac OS. The assessment screens within Star Reading already provide visual contrast through a yellow background and black writing. Furthermore, Star Reading is compatible with Mac’s "zoom in" accessibility feature, which allows users to magnify nearly all Star Reading screens

Descriptive Information

Please provide a description of your tool:
Star Reading is a computer-adaptive, interim assessment of reading comprehension and overall reading achievement for students in grades 1 through 12. The tool provides information on student performance in 46 reading skill areas in 11 domains.
The tool is intended for use with the following grade(s).
not selected Preschool / Pre - kindergarten
not selected Kindergarten
selected First grade
selected Second grade
selected Third grade
selected Fourth grade
selected Fifth grade
selected Sixth grade
selected Seventh grade
selected Eighth grade
selected Ninth grade
selected Tenth grade
selected Eleventh grade
selected Twelfth grade

The tool is intended for use with the following age(s).
not selected 0-4 years old
not selected 5 years old
not selected 6 years old
not selected 7 years old
not selected 8 years old
not selected 9 years old
not selected 10 years old
not selected 11 years old
not selected 12 years old
not selected 13 years old
not selected 14 years old
not selected 15 years old
not selected 16 years old
not selected 17 years old
not selected 18 years old

The tool is intended for use with the following student populations.
not selected Students in general education
not selected Students with disabilities
not selected English language learners

ACADEMIC ONLY: What skills does the tool screen?

Reading
Phonological processing:
not selected RAN
not selected Memory
not selected Awareness
not selected Letter sound correspondence
not selected Phonics
not selected Structural analysis

Word ID
not selected Accuracy
not selected Speed

Nonword
not selected Accuracy
not selected Speed

Spelling
not selected Accuracy
not selected Speed

Passage
not selected Accuracy
not selected Speed

Reading comprehension:
selected Multiple choice questions
not selected Cloze
not selected Constructed Response
not selected Retell
not selected Maze
not selected Sentence verification
not selected Other (please describe):


Listening comprehension:
not selected Multiple choice questions
not selected Cloze
not selected Constructed Response
not selected Retell
not selected Maze
not selected Sentence verification
not selected Vocabulary
not selected Expressive
not selected Receptive

Mathematics
Global Indicator of Math Competence
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Early Numeracy
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematics Concepts
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematics Computation
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematic Application
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Fractions/Decimals
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Algebra
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Geometry
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

not selected Other (please describe):

Please describe specific domain, skills or subtests:
BEHAVIOR ONLY: Which category of behaviors does your tool target?


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

Acquisition and Cost Information

Where to obtain:
Email Address
answers@renaissance.com
Address
Renaissance Learning, PO Box 8036, Wisconsin Rapids, WI 54495
Phone Number
(800) 338-4204
Website
http://www.renaissance.com
Initial cost for implementing program:
Cost
Unit of cost
Replacement cost per unit for subsequent use:
Cost
Unit of cost
Duration of license
Additional cost information:
Describe basic pricing plan and structure of the tool. Provide information on what is included in the published tool, as well as what is not included but required for implementation.
There is a one-time setup fee along with a per student subscription fee. Total cost will depend on the number of schools and students. Please contact: answers@renaissance.com or (800) 338-4204 for specific details on pricing for your district. Star Reading is cloud-based and purchase includes the tool, software/technical manual, installation guide, testing instructions, and remote installation and setup.
Provide information about special accommodations for students with disabilities.
Star Reading is a computer-adaptive assessment, and the difficulty of items presented is adjusted automatically to reflect the skill level of the student. Students may use the keyboard or the mouse, accommodating students with limited motor skills. Star Reading offers several accommodations for students with disabilities through the accessibility options built into a computer's operating system. For students with limited vision, the introductory screens of Star Reading respond to the "high contrast" accessibility feature within Windows and the "switch to black and white" accessibility feature in Mac OS. The assessment screens within Star Reading already provide visual contrast through a yellow background and black writing. Furthermore, Star Reading is compatible with Mac’s "zoom in" accessibility feature, which allows users to magnify nearly all Star Reading screens

Administration

BEHAVIOR ONLY: What type of administrator is your tool designed for?
not selected General education teacher
not selected Special education teacher
not selected Parent
not selected Child
not selected External observer
not selected Other
If other, please specify:

What is the administration setting?
not selected Direct observation
not selected Rating scale
not selected Checklist
not selected Performance measure
not selected Questionnaire
selected Direct: Computerized
not selected One-to-one
selected Other
If other, please specify:
Group administered

Does the tool require technology?
Yes

If yes, what technology is required to implement your tool? (Select all that apply)
selected Computer or tablet
selected Internet connection
not selected 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?
selected Individual
selected Small group   If small group, n=
selected Large group   If large group, n=
not selected Computer-administered
not selected Other
If other, please specify:

What is the administration time?
Time in minutes
18
per (student/group/other unit)
student/group

Additional scoring time:
Time in minutes
per (student/group/other unit)

ACADEMIC ONLY: What are the discontinue rules?
selected No discontinue rules provided
not selected Basals
not selected Ceilings
not selected Other
If other, please specify:


Are norms available?
Yes
Are benchmarks available?
Yes
If yes, how many benchmarks per year?
Unlimited
If yes, for which months are benchmarks available?
All
BEHAVIOR ONLY: Can students be rated concurrently by one administrator?
If yes, how many students can be rated concurrently?

Training & Scoring

Training

Is training for the administrator required?
Yes
Describe the time required for administrator training, if applicable:
Less than 1 hour of training
Please describe the minimum qualifications an administrator must possess.
selected 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

How are scores calculated?
not selected Manually (by hand)
selected Automatically (computer-scored)
not selected 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?
not selected Age norms
selected Grade norms
not selected Classwide norms
not selected Schoolwide norms
not selected Stanines
not selected Normal curve equivalents

What types of performance level scores are available?
not selected Raw score
not selected Standard score
selected Percentile score
selected Grade equivalents
selected IRT-based score
not selected Age equivalents
not selected Stanines
selected Normal curve equivalents
not selected Developmental benchmarks
not selected Developmental cut points
selected Equated
not selected Probability
selected Lexile score
not selected Error analysis
not selected Composite scores
not selected Subscale/subtest scores
selected Other
If other, please specify:
Instructional Reading Level, scale score

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.
All scores are calculated automatically by the software. The software calculates a maximum likelihood Rasch ability estimate based on the calibrated difficulty of the items that were administered to the student, and the pattern of the student’s right and wrong responses to those items. Star Reading uses a proprietary, Rasch-based, 1-parameter logistic response model to calculate scores. The scaled score is a non-linear, monotonic transformation of the Rasch ability estimate resulting from the adaptive test. From the scaled scores and the student’s current grade placement are derived grade equivalent, percentile, and normal curve equivalent scores. No clusters, composite, or raw scores are reported.
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.
Star Reading’s multiple-choice item format assesses vocabulary, fluency, and comprehension skills in five broad Common Core State Standard domains: Word Knowledge and Skills; Comprehension Strategies and Constructing Meaning; Analyzing Literary Text; Understanding Author’s Craft; and Analyzing Argument and Evaluating. Star Reading’s items assess 475 grade-specific skills; multiple items are available to measure each skill. The assessment’s computer-adaptive structure matches students to items of appropriate difficulty, which in turn may help to reduce student frustration during testing. This skill measurement provides a crucial component in progress monitoring. As students learn new skills in the state standards or growth within a response to intervention plan, Star Reading can assess the level of achievement as often as weekly. As a screener, Star Reading can provide accurate and reliable scores to place a student on a continuum of skills aligned to the state standards, which creates the foundation for a personalized learning environment. The frequency of which a student is assessed, therefore, can be either as often as weekly or at key milestones throughout the year without overexposure to the test items. For this reason, the Star Reading assessment has a large item bank, containing thousands of unique items. Each item has been designed to measure a skill at a specific grade level. All items have been calibrated, so that the difficulty of each item is expressed on a Rasch difficulty scale that spans the range of reading proficiency from grade 1 through grade 12.

Technical Standards

Classification Accuracy & Cross-Validation Summary

Grade Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Grade 9
Grade 10
Grade 11
Classification Accuracy Fall Data unavailable Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence
Classification Accuracy Winter Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Partially convincing evidence
Classification Accuracy Spring Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Data unavailable
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available

PARCC Reading

Classification Accuracy

Select time of year
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
The PARCC assessment is an external outcome measure administered at least 90 days after each student’s Star assessment.
Do the classification accuracy analyses examine concurrent and/or predictive classification?

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 Star cut-point for students at risk was determined to be at the 25th percentile of Star scores. This point aligns with students in need of intervention, as indicated in Star default benchmarks. Students scoring below the 25th percentile were placed into the at-risk category and students scoring above the 25th percentile were placed into the no-risk category. Consistent with the TRC guidelines, we selected the 20th PR on the outcome measure as the point aligned with students in need of intensive intervention.
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.
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
The PARCC ELA assessment is an external outcome measure administered at least 90 days after each student’s Star assessment.
Do the cross-validation analyses examine concurrent and/or predictive classification?

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 Star cut-point for students at risk was determined to be at the 25th percentile of Star scores. This point aligns with students in need of intervention, as indicated in Star default benchmarks. Students scoring below the 25th percentile were placed into the at-risk category and students scoring above the 25th percentile were placed into the no-risk category. Consistent with the TRC guidelines, we selected the 20th PR on the outcome measure as the point aligned with students in need of intensive intervention.
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.

Smarter Balanced ELA

Classification Accuracy

Select time of year
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
The Smarter Balanced ELA assessment is an external outcome measure administered at least 90 days after each student’s Star assessment.
Do the classification accuracy analyses examine concurrent and/or predictive classification?

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 Star cut-point for students at risk was determined to be at the 25th percentile of Star scores. This point aligns with students in need of intervention, as indicated in Star default benchmarks. Students scoring below the 25th percentile were placed into the at-risk category and students scoring above the 25th percentile were placed into the no-risk category. Consistent with the TRC guidelines, we selected the 20th PR on the outcome measure as the point aligned with students in need of intensive intervention.
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.
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?

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.

SAT EBRW

Classification Accuracy

Select time of year
Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.
The SAT EBRW assessment is an external outcome measure administered at least 90 days after each student’s Star assessment.
Do the classification accuracy analyses examine concurrent and/or predictive classification?

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 Star cut-point for students at risk was determined to be at the 25th percentile of Star scores. This point aligns with students in need of intervention, as indicated in Star default benchmarks. Students scoring below the 25th percentile were placed into the at-risk category and students scoring above the 25th percentile were placed into the no-risk category. Consistent with the TRC guidelines, we selected the 20th PR on the outcome measure as the point aligned with students in need of intensive intervention.
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.
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?

Describe when screening and criterion measures were administered and provide a justification for why the method(s) you chose (concurrent and/or predictive) is/are appropriate for your tool.
Describe how the cross-validation analyses were performed and cut-points determined. Describe how the cut points align with students at-risk. Please indicate which groups were contrasted in your analyses (e.g., low risk students versus high risk students, low risk students versus moderate risk students).
Were the children in the study/studies involved in an intervention in addition to typical classroom instruction between the screening measure and outcome assessment?
If yes, please describe the intervention, what children received the intervention, and how they were chosen.

Classification Accuracy - Fall

Evidence Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
Criterion measure PARCC Reading PARCC Reading Smarter Balanced ELA Smarter Balanced ELA Smarter Balanced ELA Smarter Balanced ELA Smarter Balanced ELA PARCC Reading PARCC Reading PARCC Reading
Cut Points - Percentile rank on criterion measure 20 20 20 20 20 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure <187 <231 <328 <413 <484 <542 <604 <564 <585 <798
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) 0.87 0.90 0.91 0.92 0.91 0.92 0.91 0.84 0.85 0.84
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.85 0.89 0.91 0.91 0.90 0.91 0.90 0.83 0.83 0.80
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.89 0.92 0.92 0.93 0.92 0.93 0.92 0.86 0.87 0.89
Statistics Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
Date Fall 2013 Fall 2014 Fall 2014 Fall 2014 Fall 2014 Fall 2014 Fall 2014 Fall 2014 Fall 2014 Fall 2014
Sample Size
Geographic Representation East North Central (IL)
Middle Atlantic (NJ)
Mountain (CO, NM)
West South Central (AR)
East North Central (OH)
Middle Atlantic (NJ)
Mountain (CO, NM)
New England (RI)
West South Central (AR)
New England (CT)
Pacific (CA, OR, WA)
New England (CT)
Pacific (CA, OR, WA)
New England (CT)
Pacific (CA, OR, WA)
New England (CT)
Pacific (CA, OR, WA)
New England (CT)
Pacific (CA, OR, WA)
East North Central (OH)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
Male                    
Female                    
Other                    
Gender Unknown                    
White, Non-Hispanic                    
Black, Non-Hispanic                    
Hispanic                    
Asian/Pacific Islander                    
American Indian/Alaska Native                    
Other                    
Race / Ethnicity Unknown                    
Low SES                    
IEP or diagnosed disability                    
English Language Learner                    

Classification Accuracy - Winter

Evidence Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
Criterion measure PARCC Reading PARCC Reading PARCC Reading PARCC Reading Smarter Balanced ELA PARCC Reading Smarter Balanced ELA PARCC Reading PARCC Reading PARCC Reading PARCC Reading
Cut Points - Percentile rank on criterion measure 20 20 20 20 20 20 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure <85 <187 <290 <376 <448 <462 <578 <538 <580 <609 <769
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) 0.87 0.89 0.89 0.91 0.92 0.89 0.91 0.90 0.86 0.86 0.88
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.83 0.87 0.88 0.90 0.92 0.88 0.90 0.89 0.85 0.84 0.83
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.92 0.91 0.91 0.92 0.93 0.90 0.92 0.92 0.88 0.88 0.93
Statistics Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
Date Winter 2012-13 Winter 2013-14 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15
Sample Size
Geographic Representation East North Central (IL)
Mountain (CO, NM)
West South Central (AR)
East North Central (IL)
Middle Atlantic (NJ)
Mountain (CO, NM)
West South Central (AR)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO, NM)
New England (RI)
West South Central (AR)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO, NM)
New England (RI)
West South Central (AR)
New England (CT)
Pacific (CA, OR, WA)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO, NM)
New England (RI)
West South Central (AR)
New England (CT)
Pacific (CA, OR, WA)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
Male                      
Female                      
Other                      
Gender Unknown                      
White, Non-Hispanic                      
Black, Non-Hispanic                      
Hispanic                      
Asian/Pacific Islander                      
American Indian/Alaska Native                      
Other                      
Race / Ethnicity Unknown                      
Low SES                      
IEP or diagnosed disability                      
English Language Learner                      

Classification Accuracy - Spring

Evidence Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10
Criterion measure PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading Smarter Balanced ELA PARCC Reading PARCC Reading PARCC Reading
Cut Points - Percentile rank on criterion measure 20 20 20 20 20 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure <129 <238 <336 <419 <449 <485 <611 <587 <590 <830
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) 0.89 0.89 0.91 0.89 0.86 0.88 0.91 0.84 0.87 0.92
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.85 0.87 0.90 0.87 0.85 0.86 0.90 0.83 0.84 0.87
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.93 0.91 0.93 0.90 0.87 0.89 0.92 0.86 0.89 0.98
Statistics Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10
Date Spring 2013 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014
Sample Size
Geographic Representation East North Central (IL)
Middle Atlantic (NJ)
Mountain (CO, NM)
West South Central (AR)
East North Central (IL)
Middle Atlantic (NJ)
Mountain (CO, NM)
West South Central (AR)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO, NM)
New England (RI)
West South Central (AR)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO, NM)
New England (RI)
West South Central (AR)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO, NM)
New England (RI)
West South Central (AR)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
New England (CT)
Pacific (CA, OR, WA)
East North Central (IL, OH)
Middle Atlantic (NJ)
Mountain (CO)
New England (RI)
West South Central (AR)
East North Central (OH)
Mountain (CO)
New England (RI)
West South Central (AR)
Mountain (CO)
New England (RI)
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 Grade 2 Grade 3 Grade 9 Grade 10 Grade 11
Criterion measure PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading
Cut Points - Percentile rank on criterion measure 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure <187 <231 <564 <585 <798
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) 0.91 0.93 0.90 0.91 0.90
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.87 0.90 0.87 0.88 0.86
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.95 0.96 0.94 0.94 0.93
Statistics Grade 2 Grade 3 Grade 9 Grade 10 Grade 11
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Grade 2 Grade 3 Grade 9 Grade 10 Grade 11
Date Fall 2013 Fall 2014 Fall 2014 Fall 2014 Fall 2014
Sample Size
Geographic Representation Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ)
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 Grade 1 Grade 2 Grade 3 Grade 4 Grade 6 Grade 8 Grade 9 Grade 10 Grade 11
Criterion measure PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading
Cut Points - Percentile rank on criterion measure 20 20 20 20 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure <85 <187 <290 <376 <462 <538 <580 <609 <769
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) 0.87 0.92 0.97 0.96 0.93 0.92 0.86 0.99 0.83
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.83 0.87 0.95 0.93 0.90 0.88 0.76 0.96 0.71
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.92 0.96 0.98 0.98 0.96 0.97 0.96 1.00 0.95
Statistics Grade 1 Grade 2 Grade 3 Grade 4 Grade 6 Grade 8 Grade 9 Grade 10 Grade 11
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Grade 1 Grade 2 Grade 3 Grade 4 Grade 6 Grade 8 Grade 9 Grade 10 Grade 11
Date Winter 2012-13 Winter 2013-14 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15 Winter 2014-15
Sample Size
Geographic Representation Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ)
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 Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 8 Grade 9 Grade 10
Criterion measure PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading PARCC Reading
Cut Points - Percentile rank on criterion measure 20 20 20 20 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure <129 <238 <336 <419 <449 <485 <587 <590 <830
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) 0.90 0.93 0.95 0.98 0.88 0.94 0.88 0.92 0.90
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.85 0.90 0.93 0.97 0.82 0.92 0.82 0.84 0.84
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.94 0.96 0.97 0.99 0.94 0.97 0.88 0.89 0.95
Statistics Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 8 Grade 9 Grade 10
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 8 Grade 9 Grade 10
Date Spring 2013 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014 Spring 2014
Sample Size
Geographic Representation Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ) Middle Atlantic (NJ)
Male                  
Female                  
Other                  
Gender Unknown                  
White, Non-Hispanic                  
Black, Non-Hispanic                  
Hispanic                  
Asian/Pacific Islander                  
American Indian/Alaska Native                  
Other                  
Race / Ethnicity Unknown                  
Low SES                  
IEP or diagnosed disability                  
English Language Learner                  

Reliability

Grade Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Grade 9
Grade 10
Grade 11
Rating Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available
*Offer a justification for each type of reliability reported, given the type and purpose of the tool.
The internal consistency reliability coefficient estimates the proportion of variability within a single administration of a test that is due to inconsistency among the items that comprise the test
*Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
For each grade, a large sample (n = 100,000) of students completed Star Reading assessments throughout the 2012–2013 school year
*Describe the analysis procedures for each reported type of reliability.
Reliability was defined as the proportion of test score variance that is attributable to true variation in the trait the test measures. The variance of the test scores was calculated from Scaled Score data. The variance of the errors of measurement was estimated from the conditional standard error of measurement (CSEM) statistics that accompany each of the IRT-based test scores, including the Scaled Scores. The conditional standard error of measurement (CSEM) was calculated along with the IRT ability estimate and Scaled Score. Squaring and summing the CSEM values yielded an estimate of total squared error; dividing by the number of observations yielded an estimate of error variance. Generic reliability was calculated by subtracting the ratio of error variance to Scaled Score variance from 1.

*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:
Yes
Provide citations for additional published studies.
Renaissance Learning (2016). Star Assessments™ for Reading Abridged Technical Manual. Wisconsin Rapids, WI: Author. Available by request to research@renaissance.com.
Do you have reliability data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?
No

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

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of reliability analysis not compatible with above table format:
Manual cites other published reliability studies:
Provide citations for additional published studies.

Validity

Grade Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Grade 9
Grade 10
Grade 11
Rating Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence Convincing evidence
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available
*Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
All criterion measures were external to the screening tool system and represent widely used assessments of general reading ability. • CAT-5. The California Achievement Test, is a nationally normed standardized test that measures achievement in reading. • ITBS. The Iowa Tests For Basic Skills are nationally normed standardized tests that offer educators a diagnostic look at how their students are progressing in reading comprehension. • PARCC. The Partnership for Assessment of Readiness for College and Careers end-of-year assessment covers reading and is intended to be used as an indicator of student needs and progress. • SBA. Smarter Balanced assessments are summative tests designed to measure student achievement and growth in reading to support teaching and learning. • ACT. The American College Testing college readiness assessment is a national standardized test for high school achievement and college admissions. • SAT EBRW. The SAT Evidence-based reading and writing assessment is a standardized test widely used for college admissions in the United States.
*Describe the sample(s), including size and characteristics, for each validity analysis conducted.
Samples included students who had taken both Star Reading and the criterion measure. The sample sizes varied across criterion and grades, ranging from 105 to 10,800 students.
*Describe the analysis procedures for each reported type of validity.
Concurrent and predictive correlations were calculated. A criterion assessment was considered concurrent if it was taken during the same school year as the Star Reading assessment. The correlation was considered predictive if the criterion assessment was taken one or more school years after the Star Reading assessment.

*In the table below, report the results of the validity analyses described above (e.g., concurrent or predictive validity, evidence based on response processes, evidence based on internal structure, evidence based on relations to other variables, and/or evidence based on consequences of testing), and the criterion measures.

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of validity analysis not compatible with above table format:
Manual cites other published reliability studies:
Yes
Provide citations for additional published studies.
Renaissance Learning (2016). Star Assessments™ for Reading Abridged Technical Manual. Wisconsin Rapids, WI: Author. Available by request to research@renaissance.com.
Describe the degree to which the provided data support the validity of the tool.
The provided data indicate that Star Reading results correspond to other various respected measures of general reading ability
Do you have validity data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?
No

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

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of validity analysis not compatible with above table format:
Manual cites other published reliability studies:
No
Provide citations for additional published studies.

Bias Analysis

Grade Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Grade 9
Grade 10
Grade 11
Rating Yes Yes 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:
Logistic regression analyses conditional on ability, group membership, and ability by group interaction were conducted to assess the presence of both uniform and non-uniform DIF simultaneously. Additionally, an effect size measure – Nagelkerke R-squared – was computed to quantify the magnitude of DIF where present.
b. Describe the subgroups for which bias analyses were conducted:
DIF analyses were conducted for gender (males and females) and race/ethnicity (Caucasian, African American, American Indian, Asian, and Hispanic subpopulations). Due to insufficient samples sizes on English Language Learner (ELLs) and students with disabilities (SWD), DIF analyses for these two subgroups were not possible at the time of the analyses.
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.
Using a blended criterion that flagged items for uniform/non-uniform DIF if they had a p-value less than 0.01 and Nagelkerke R2 greater than or equal to 0.035, the results indicated that Star Reading is sufficiently bias-free. A total of 153 items (2% of the Star Reading items) were flagged for DIF. Those flagged items were removed from the item banks for review and recalibration.

Data Collection Practices

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