Istation’s Indicators of Progress (ISIP)
Early Math

Summary

ISIP Early Math is a web based computer adaptive formative assessment intended for students in PreKindergarten through Grade 1. The assessment is intended to provide teachers and administrators with student test results to answer two questions: (a) whether students are at risk of failure, and (b) the degree of intensity of instructional support students need to be successful. ISIP Early Math can be administered individually or in group settings. The assessment is administered in English. The assessment is untimed; however, most students complete the assessment within 30 minutes. There is no additional scoring time required for the assessment. Teachers can be trained on ISIP Math through either a webinar or an in-person training session. Training takes between 1 and 4 hours. All training materials are online and are created by Istation. Reports are available for both individual and groups of students indicating single administration results and comparisons of results over time. All reports include student scaled scores and tier levels based on student percentiles.

Where to Obtain:
Istation
info@istation.com
8150 North Central Expressway, Suite 2000, Dallas, TX, 75206
(866) 883-READ
www.istation.com
Initial Cost:
$5.95 per student
Replacement Cost:
$5.95 per student per 1 year
Included in Cost:
ISIP Early Math is purchased as a yearly subscription. ISIP Early Math assessment packages includes online assessment, data hosting, reporting, teacher resources, online training center, user and manuals. In-person training conducted by a professional development specialist cost is $2800 per specialist per day. Computers and/or tablets are needed to implement this assessment, as well as internet access. ISIP Early can be used on many different technology platforms including desktops, laptops, and tablets.
Appropriate accommodations are provided during ISIP assessments for students who are receiving support services, including those who have an Individual Education or 504 Plan, or who qualify as English Language learners. These accommodations support students’ access to the content of the assessment by reducing or eliminating the effects of the disability or limitation but do not change the content of the assessment. ISIP assessments provide people with disabilities access that is comparable to access for non-impaired people — with the exception of a totally blind or totally deaf disabled person. Administrators with manager accounts can assign accommodations to students in the Istation report and Management Portal. See attached for more specific accommodations and assistive technology.
Training Requirements:
1-4 hrs of training
Qualified Administrators:
paraprofessional at minimum
Access to Technical Support:
By email and phone (M-F 7am-6:30pm) CST)
Assessment Format:
  • Performance measure
  • Direct: Computerized
  • One-to-one
Scoring Time:
  • Scoring is automatic
Scores Generated:
  • Raw score
  • Percentile score
  • IRT-based score
  • Composite scores
  • Other: MetaMetrics Quantile Score
Administration Time:
  • 25 minutes per student
Scoring Method:
  • Automatically (computer-scored)
Technology Requirements:
  • Computer or tablet
  • Internet connection
Accommodations:
Appropriate accommodations are provided during ISIP assessments for students who are receiving support services, including those who have an Individual Education or 504 Plan, or who qualify as English Language learners. These accommodations support students’ access to the content of the assessment by reducing or eliminating the effects of the disability or limitation but do not change the content of the assessment. ISIP assessments provide people with disabilities access that is comparable to access for non-impaired people — with the exception of a totally blind or totally deaf disabled person. Administrators with manager accounts can assign accommodations to students in the Istation report and Management Portal. See attached for more specific accommodations and assistive technology.

Descriptive Information

Please provide a description of your tool:
ISIP Early Math is a web based computer adaptive formative assessment intended for students in PreKindergarten through Grade 1. The assessment is intended to provide teachers and administrators with student test results to answer two questions: (a) whether students are at risk of failure, and (b) the degree of intensity of instructional support students need to be successful. ISIP Early Math can be administered individually or in group settings. The assessment is administered in English. The assessment is untimed; however, most students complete the assessment within 30 minutes. There is no additional scoring time required for the assessment. Teachers can be trained on ISIP Math through either a webinar or an in-person training session. Training takes between 1 and 4 hours. All training materials are online and are created by Istation. Reports are available for both individual and groups of students indicating single administration results and comparisons of results over time. All reports include student scaled scores and tier levels based on student percentiles.
The tool is intended for use with the following grade(s).
selected Preschool / Pre - kindergarten
selected Kindergarten
selected First grade
not selected Second grade
not selected Third grade
not selected Fourth grade
not selected Fifth grade
not selected Sixth grade
not selected Seventh grade
not selected Eighth grade
not selected Ninth grade
not selected Tenth grade
not selected Eleventh grade
not selected Twelfth grade

The tool is intended for use with the following age(s).
not selected 0-4 years old
selected 5 years old
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:
not 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
selected Multiple Choice
selected Constructed Response

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

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

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

Mathematic Application
not selected Accuracy
not selected Speed
selected Multiple Choice
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
info@istation.com
Address
8150 North Central Expressway, Suite 2000, Dallas, TX, 75206
Phone Number
(866) 883-READ
Website
www.istation.com
Initial cost for implementing program:
Cost
$5.95
Unit of cost
student
Replacement cost per unit for subsequent use:
Cost
$5.95
Unit of cost
student
Duration of license
1 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.
ISIP Early Math is purchased as a yearly subscription. ISIP Early Math assessment packages includes online assessment, data hosting, reporting, teacher resources, online training center, user and manuals. In-person training conducted by a professional development specialist cost is $2800 per specialist per day. Computers and/or tablets are needed to implement this assessment, as well as internet access. ISIP Early can be used on many different technology platforms including desktops, laptops, and tablets.
Provide information about special accommodations for students with disabilities.
Appropriate accommodations are provided during ISIP assessments for students who are receiving support services, including those who have an Individual Education or 504 Plan, or who qualify as English Language learners. These accommodations support students’ access to the content of the assessment by reducing or eliminating the effects of the disability or limitation but do not change the content of the assessment. ISIP assessments provide people with disabilities access that is comparable to access for non-impaired people — with the exception of a totally blind or totally deaf disabled person. Administrators with manager accounts can assign accommodations to students in the Istation report and Management Portal. See attached for more specific accommodations and assistive technology.

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
selected Performance measure
not selected Questionnaire
selected Direct: Computerized
selected One-to-one
not selected 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)
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
25
per (student/group/other unit)
student

Additional scoring time:
Time in minutes
0
per (student/group/other unit)
student

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?
3
If yes, for which months are benchmarks available?
Entire year; January through December
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:
1-4 hrs of training
Please describe the minimum qualifications an administrator must possess.
paraprofessional at minimum
not 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:
Training manuals, users guides, and an online training center are included in the cost of the tool. In-person training conducted by a professional development specialist cost is $2800 per specialist per day.
Can users obtain ongoing professional and technical support?
Yes
If Yes, please describe how users can obtain support:
By email and phone (M-F 7am-6:30pm) CST)

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?
selected Raw score
not selected Standard score
selected Percentile score
not selected Grade equivalents
selected IRT-based score
not selected Age equivalents
not selected Stanines
not selected Normal curve equivalents
not selected Developmental benchmarks
not selected Developmental cut points
not selected Equated
not selected Probability
not selected Lexile score
not selected Error analysis
selected Composite scores
not selected Subscale/subtest scores
selected Other
If other, please specify:
MetaMetrics Quantile 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.
Ability scores are estimated using Bayesian EAP with an informative prior under a 2 PL unidimensional IRT model. Reported scale scores are generated through a linear transformation of the raw IRT-based ability scores. An overall ability is estimated after all of the appropriate sub-contents (number sense, operations, geometry, algebra and algebraic thinking, measurement, data analysis, probability and statistics, personal financial literacy, and mathematical reasoning) are measured based on the responses from all items.
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.

Technical Standards

Classification Accuracy & Cross-Validation Summary

Grade Kindergarten
Grade 1
Classification Accuracy for Criterion 1 Fall Partially convincing evidence Unconvincing evidence
Classification Accuracy for Criterion 1 Winter Partially convincing evidence Partially convincing evidence
Classification Accuracy for Criterion 1 Spring Partially convincing evidence Unconvincing evidence
Classification Accuracy for Criterion 2 Fall Data unavailable Data unavailable
Classification Accuracy for Criterion 2 Winter Data unavailable Data unavailable
Classification Accuracy for Criterion 2 Spring Data unavailable Data unavailable
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available

Classification Accuracy - Criterion 1 Fall

Evidence Kindergarten Grade 1
Criterion measure Test of Early Mathematics Ability (TEMA) Test of Early Mathematics Ability (TEMA)
Cut Points - Percentile rank on criterion measure 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 1793 1762
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) 0.71 0.74
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.50 0.66
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.74 0.81
Statistics Kindergarten Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1
Date September – October 2015 September – October 2015
Sample Size
Geographic Representation West South Central (TX) West South Central (TX)
Male 86 115
Female 83 101
Other
Gender Unknown 2 1
White, Non-Hispanic 77 117
Black, Non-Hispanic 17 17
Hispanic 67 67
American Indian/Alaska Native
Other
Race / Ethnicity Unknown 10 16
Low SES 82 107
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Criterion 1 Winter

Evidence Kindergarten Grade 1
Criterion measure Test of Early Mathematics Ability (TEMA) Test of Early Mathematics Ability (TEMA)
Cut Points - Percentile rank on criterion measure 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 1883 1871
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) 0.76 0.77
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.58 0.69
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.81 0.84
Statistics Kindergarten Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1
Date January – February 2016 January – February 2016
Sample Size
Geographic Representation West South Central (TX) West South Central (TX)
Male 87 128
Female 78 101
Other
Gender Unknown 5 1
White, Non-Hispanic 77 120
Black, Non-Hispanic 16 17
Hispanic 66 77
American Indian/Alaska Native
Other
Race / Ethnicity Unknown 11 16
Low SES 82 119
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Criterion 1 Spring

Evidence Kindergarten Grade 1
Criterion measure Test of Early Mathematics Ability (TEMA) Test of Early Mathematics Ability (TEMA)
Cut Points - Percentile rank on criterion measure 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 1984 1965
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 0.74
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.68 0.66
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.91 0.82
Statistics Kindergarten Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1
Date May – June 2016 May – June 2016
Sample Size
Geographic Representation West South Central (TX) West South Central (TX)
Male 83 122
Female 76 98
Other
Gender Unknown 4 1
White, Non-Hispanic 77 114
Black, Non-Hispanic 16 16
Hispanic 61 75
American Indian/Alaska Native
Other
Race / Ethnicity Unknown 9 16
Low SES 78 110
IEP or diagnosed disability
English Language Learner

Cross-Validation - Criterion 1 Fall

Evidence Kindergarten Grade 1
Criterion measure Test of Early Mathematics Ability (TEMA) Test of Early Mathematics Ability (TEMA)
Cut Points - Percentile rank on criterion measure 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 1793 1762
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) 0.71 0.74
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.50 0.66
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.74 0.81
Statistics Kindergarten Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1
Date September – October 2015 September – October 2015
Sample Size
Geographic Representation West South Central (TX) West South Central (TX)
Male 86 115
Female 83 101
Other
Gender Unknown 2 1
White, Non-Hispanic 77 117
Black, Non-Hispanic 17 17
Hispanic 67 67
American Indian/Alaska Native
Other
Race / Ethnicity Unknown 10 16
Low SES 82 107
IEP or diagnosed disability
English Language Learner

Cross-Validation - Criterion 1 Winter

Evidence Kindergarten Grade 1
Criterion measure Test of Early Mathematics Ability (TEMA) Test of Early Mathematics Ability (TEMA)
Cut Points - Percentile rank on criterion measure 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 1883 1871
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) 0.76 0.77
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.58 0.69
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.81 0.84
Statistics Kindergarten Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1
Date January – February 2016 January – February 2016
Sample Size
Geographic Representation West South Central (TX) West South Central (TX)
Male 87 128
Female 78 101
Other
Gender Unknown 5 1
White, Non-Hispanic 77 120
Black, Non-Hispanic 16 17
Hispanic 66 77
American Indian/Alaska Native
Other
Race / Ethnicity Unknown 11 16
Low SES 82 119
IEP or diagnosed disability
English Language Learner

Cross-Validation - Criterion 1 Spring

Evidence Kindergarten Grade 1
Criterion measure Test of Early Mathematics Ability (TEMA) Test of Early Mathematics Ability (TEMA)
Cut Points - Percentile rank on criterion measure 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 1984 1965
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 0.74
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.68 0.66
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.91 0.82
Statistics Kindergarten Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1
Date May – June 2016 May – June 2016
Sample Size
Geographic Representation West South Central (TX) West South Central (TX)
Male 83 122
Female 76 98
Other
Gender Unknown 4 1
White, Non-Hispanic 77 114
Black, Non-Hispanic 16 16
Hispanic 61 75
American Indian/Alaska Native
Other
Race / Ethnicity Unknown 9 16
Low SES 78 110
IEP or diagnosed disability
English Language Learner

Reliability

Grade Kindergarten
Grade 1
Rating Convincing evidence d Convincing evidence d
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.
Cronbach’s (1951) coefficient alpha is typically used as an indicator of reliability across test items within a testing instance. However, Cronboch’s Alpha is not appropriate for any IRT based measure because alpha assumes that all students in the testing instance respond to a common set of items. Due to its very nature, students taking a CAT-based assessment, such as ISIP Math, will receive a custom set of items based on their initial estimates of ability and response patterns. Thus, students do not respond to a common set of items. The IRT analogue to classical internal consistency is marginal reliability (Bock & Mislevy, 1982) and thus applied to ISIP Math.
*Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
Samples were obtained from three school districts in Texas during the 2015-2016 school year. There were 171 kindergartners for beginning of the year assessment (BOY/Fall), 170 kindergartners for middle of the year assessment (MOY/Winter), 163 kindergartners for end of the year assessment (EOY/Spring), 217 first graders for beginning of the year assessment (BOY), 230 first graders for middle of the year assessment (MOY), and 221 first graders for end of the year assessment (EOY).
*Describe the analysis procedures for each reported type of reliability.
IRT based reliability is derived from Classical Test Theory to Item Response Theory as follow. (see attached doc) IRT based reliability in equation (1) is computed at each administration.

*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:
Additional disaggregated data is available from the Center upon request.
Manual cites other published reliability studies:
No
Provide citations for additional published studies.

Validity

Grade Kindergarten
Grade 1
Rating Unconvincing evidence d Convincing evidence d
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.
Predictive validity examines the relation between performance on the screener and a criterion of similar content that is administered at some time in the future. On the other hand, Concurrent validity examines the relation between performance on the screener and a criterion of similar content that is administered at the same point in time. Renaissance Learning’s STAR Math is a computerized adaptive test intended for students in Grades 1 through 8. STAR Math is designed to provide teachers and administrators with data that can be used for multiple purposes such as screening, placement, planning instruction, benchmarking, and outcomes measurement. It also provides educators with estimates of students’ instructional math levels relative to national norms. Because STAR Math assesses a similar construct and has a similar use, STAR Math was used to provide concurrent validity for ISIP Math. The Test of Early Mathematics Ability –Third Edition (TEMA-3) was selected to provide concurrent validity for ISIP Math because it assesses a similar construct. TEMA-3 is intended to identify children who are significantly behind or ahead of their peers in the development of mathematical thinking (Ginsburg & Baroody, 2003). The TEMA-3 is intended to be administered at the beginning of the school year as an early indicator of students’ abilities, but can also be administered later in the school year to assess student progress. Mathematical concepts and skills assessed in the TEMA-3 include relative magnitude, counting, calculation, convention, number facts, base 10 concepts, non-verbal production, non-verbal addition and subtraction, part whole concepts, equal partitioning, symbolic additive commutativity, number comparisons, and mental addition and subtraction.
*Describe the sample(s), including size and characteristics, for each validity analysis conducted.
Samples are derived from urban school districts in the northeast area of the state of Texas approximately 200 students per each assessment point (Fall/Winter/Spring).
*Describe the analysis procedures for each reported type of validity.
Data for this study was obtained from three school districts in Texas during the 2015-2016 school year. There were 178 kindergartners and 239 first graders. The validity was calculated by determining the correlation between the scaled scores of the ISIP Math and the scaled scores of the TEMA-3, and the STAR Math individually, by grade level.

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

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of validity analysis not compatible with above table format:
Manual cites other published reliability studies:
No
Provide citations for additional published studies.
Describe the degree to which the provided data support the validity of the tool.
The results suggest moderate to strong relationships between ISIP Math and STAR Math and TEMA-3. Our findings also show very convincing evidence across all 3 data points (Fall: beginning of the year (BOY), Winter: middle of the year (MOY), and Spring: end of the year (EOY) both K and Grade 1.
Do you have validity data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?
Yes

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

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:
Additional disaggregated data is available from the Center upon request.
Manual cites other published reliability studies:
No
Provide citations for additional published studies.

Bias Analysis

Grade Kindergarten
Grade 1
Rating 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 Functioning (DIF) analysis was conducted by grade level (K - 1) using logistic regression DIF detection analysis by difR package in R software.
b. Describe the subgroups for which bias analyses were conducted:
Four DIF factors were investigated: socioeconomic status, gender, race/ethnicity, and special education students.
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 Zumbo & Thomas (ZT) DIF criterion, results showed 97% displayed as A item (negligible or non-significant DIF effect), 2% displayed as B item (slightly to moderate DIF effect), and only 1% displayed as C item (moderate to large DIF effect) across these four DIF factors.

Disclaimer

Most tools and programs evaluated by the NCII are branded products which have been submitted by the companies, organizations, or individuals that disseminate these products. These entities supply the textual information shown above, but not the ratings accompanying the text. NCII administrators and members of our Technical Review Committees have reviewed the content on this page, but NCII cannot guarantee that this information is free from error or reflective of recent changes to the product. Tools and programs have the opportunity to be updated annually or upon request.