Agency predictive model documentation (Texas Education Agency)

Todd Feathers filed this request with the Texas Education Agency of Texas.
Tracking #

50444

Multi Request Agency predictive model documentation
Status
Completed

Communications

From: Todd Feathers

To Whom It May Concern:

Pursuant to the Texas Public Information Act, I hereby request the following records:

1) Executive summaries, algorithmic impact reports, predictive model reports, and/or model validation studies dating from Jan. 1, 2017 until the present for all predictive analytics tools and automated decision systems (ADS) used by the agency. This includes predictive models and ADSs built in-house as well as those built by vendors for the agency or those used by agency employees through third-party software.

2) All contracts and statements of work regarding the purchase and/or creation of tools identified in response to part one of this request.

2) A data dictionary/library for each predictive model and ADS identified in response to part one of this request. Please note: Data dictionaries list the names of data fields (i.e. column headers in a spreadsheet), they do not contain the actual data analyzed by models.

If you have any questions regarding this request, please don't hesitate to contact me for further clarification.

I ask that all fees be waived as I am a journalist and intend to use the requested records to publish articles in the public interest. In the event you choose to impose fees, I request a detailed breakdown of the fees, including the hourly wage of each employee involved and an explanation justifying the employee hours required to fulfill the request.

Should you choose to reject this request or redact portions of responsive documents, I ask that you provide a detailed breakdown of the statutory exemptions and associated case law underlying your decision to withhold each/any portions from public review.

In the event that there are fees, I would be grateful if you would inform me of the total charges in advance of fulfilling my request. I would prefer the request filled electronically, by e-mail attachment if available or CD-ROM if not.

Thank you in advance for your anticipated cooperation in this matter. I look forward to receiving your response to this request within 10 business days, as the statute requires.

Sincerely,

Todd Feathers

From: Texas Education Agency

Public Information Request

Receipt Acknowledgement

October 26, 2021

Todd Feathers

MuckRock News

Dept MR 120443

411A Highland Ave

Sommerville, MA 02144

TEA PIR #50444

Dear Mr. Todd Feathers:

Thank you for contacting the Texas Education Agency. I want to acknowledge receipt of your request. Your request number is PIR # 50444.

Our Public Information Request Coordinators are processing your request in coordination with the area(s) that may have the responsive information/data. A response to your request should be provided on or before 10 business days: November 8, 2021. Should you not receive a response within this timeline, please do not hesitate to contact our office and ask to speak to one of our Coordinators.

If you have any questions or wish to discuss this matter further, please contact me at (512) 463-3464 or by email at PIR@tea.texas.gov<file:///C:/Users/fzuma/AppData/Local/Temp/PIR@tea.texas.gov>.

Sincerely,

[Logo Description automatically generated]
Sherry Mansell
Public Information Coordinator
Office of General Counsel
[cid:image002.png@01D7C9CA.FAB59560]
512-463-3464
[cid:image003.png@01D7C9CA.FAB59560]
pir@tea.texas.gov<mailto:pir@tea.texas.gov>
[Icon Description automatically generated]
www.tea.texas.gov<http://www.tea.texas.gov>

Sherry Mansell

Public Information Coordinator

Enclosure: Original Request

From: Texas Education Agency

Public Information Request

Release of Information Delayed

November 8, 2021

Todd Feathers

MuckRock News

Dept MR 120443

411A Highland Ave

Sommerville, MA 02144

TEA PIR #50444

Dear Mr. Todd Feathers:

On October 25, 2021, you requested public information from the Texas Education Agency (TEA). Currently, we are in the process of compiling the documents responsive to your request.

TEA anticipates that the information will be released to you on or before: November 19, 2021.

If you have any questions or wish to discuss this matter further, please contact me at (512) 463-3464 or by email at PIR@tea.texas.gov.

Sincerely,

[Logo Description automatically generated]
Sherry Mansell
Public Information Coordinator
Office of General Counsel
[cid:image002.png@01D7D47D.6CD68E80]
512-463-3464
[cid:image003.png@01D7D47D.6CD68E80]
pir@tea.texas.gov<mailto:pir@tea.texas.gov>
[Icon Description automatically generated]
www.tea.texas.gov<http://www.tea.texas.gov>

Sherry Mansell

Public Information Coordinator

Enclosure: Original Request

From: Texas Education Agency

Public Information Request

Release Documents at No Charge

November 18, 2021

Todd Feathers

MuckRock News

Dept MR 120443

411A Highland Ave

Sommerville, MA 02144

TEA PIR #50444

Dear Mr. Todd Feathers:

On October 25, 2021, the Texas Education Agency (TEA) received your request for public information. To the extent it exists, the requested information is provided to you with this letter and includes a copy of the original request.

TEA College Career and Military Preparation provided the report for CCMR Predictive Validity Study. The agency uses SAS and SAS JMP for predictive analytics as well as Anaconda license for Python and R kernals.

Data dictionaries can be found here:

https://tealprod.tea.state.tx.us/TWEDS/93/0/0/0/Introduction/List/705<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftealprod.tea.state.tx.us%2FTWEDS%2F93%2F0%2F0%2F0%2FIntroduction%2FList%2F705&data=04%7C01%7CFrank.Ward%40tea.texas.gov%7C768b90f6dca54b326b9f08d9aaa98f94%7C65d6b3c3723648189613248dbd713a6f%7C0%7C0%7C637728468597185353%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=6ChTYroQoHrpXI2BV%2F1vnEGeM5sjc3%2F20weyX6cseQw%3D&reserved=0>

https://rptsvr1.tea.texas.gov/perfreport/tapr/2019/xplore/taprref.html<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Frptsvr1.tea.texas.gov%2Fperfreport%2Ftapr%2F2019%2Fxplore%2Ftaprref.html&data=04%7C01%7CFrank.Ward%40tea.texas.gov%7C768b90f6dca54b326b9f08d9aaa98f94%7C65d6b3c3723648189613248dbd713a6f%7C0%7C0%7C637728468597185353%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=W2eEv0srQJE6mkyeWvfsVpOgwVrhxc5EeC6oC0HGmlY%3D&reserved=0>

TEA Assessment provided the information below and refers to the attached PDF contract with Cambium.

1) Executive summaries, algorithmic impact reports, predictive model reports, and/or model validation studies dating from Jan. 1, 2017 until the present for all predictive analytics tools and automated decision systems (ADS) used by the agency. This includes predictive models and ADSs built in-house as well as those built by vendors for the agency or those used by agency employees through third-party software.

One of the purposes of the Interim assessments of the Texas Assessment Program is to predict student performance on the State of Texas Assessments of Academic Readiness (STAAR) through the use of prediction models.

The Interim Assessments Technical Report<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftea.texas.gov%2Fsites%2Fdefault%2Ffiles%2FTexas%25202018-19%2520Interim%2520Assessment%2520Technical%2520Report.pdf&data=04%7C01%7CFrank.Ward%40tea.texas.gov%7C768b90f6dca54b326b9f08d9aaa98f94%7C65d6b3c3723648189613248dbd713a6f%7C0%7C0%7C637728468597195304%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=8utqHPuGngRpkborOo80s7BO%2BKVmstAkC4oOsa51cJ4%3D&reserved=0> (starting on page 14) outlines the steps taken to build the prediction models to predict the probability of reaching each performance level on the corresponding STAAR assessment.

2) All contracts and statements of work regarding the purchase and/or creation of tools identified in response to part one of this request.

The Cambium contract covers Interim Assessments. Information responsive to this section should come from the Contracts team.

3) A data dictionary/library for each predictive model and ADS identified in response to part one of this request. Please note: Data dictionaries list the names of data fields (i.e. column headers in a spreadsheet), they do not contain the actual data analyzed by models. If you have any questions regarding this request, please don't hesitate to contact me for further clarification.

Interim Assessment Data File Layout<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftea.texas.gov%2Fsites%2Fdefault%2Ffiles%2Ftx-boy-interim-file-layout-district-version.pdf&data=04%7C01%7CFrank.Ward%40tea.texas.gov%7C768b90f6dca54b326b9f08d9aaa98f94%7C65d6b3c3723648189613248dbd713a6f%7C0%7C0%7C637728468597205262%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=z2tDgVLKMRM90xTp9z%2B8jwW%2BHpeD3B1wF8k%2BtRXdOTk%3D&reserved=0>

Additionally, there are no charges for fulfilling this request and PIR # 50444 is considered closed.

If you have any questions or wish to discuss this matter further, please contact me at (512) 463-3464 or by email at PIR@tea.texas.gov<mailto:PIR@tea.texas.gov>.

Sincerely,

[Logo Description automatically generated]

Sherry Mansell

Public Information Coordinator

Office of General Counsel

[cid:image002.png@01D7DC65.95DCEB90]

512-463-3464

[cid:image003.png@01D7DC65.95DCEB90]

pir@tea.texas.gov<mailto:pir@tea.texas.gov>

[Icon Description automatically generated]

www.tea.texas.gov<https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.tea.texas.gov%2F&data=04%7C01%7CFrank.Ward%40tea.texas.gov%7C768b90f6dca54b326b9f08d9aaa98f94%7C65d6b3c3723648189613248dbd713a6f%7C0%7C0%7C637728468597205262%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=xbusDxT%2B6r9DpQI%2Fo9NALIVXnMF2zuiDpOp2jBVpwzE%3D&reserved=0>

Sherry Mansell

Public Information Coordinator

Enclosures:

Original Request

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