Student Predictive Analytics Services docs

Todd Feathers filed this request with the Allentown School District of Allentown, PA.

It is a clone of this request.

Status
Rejected

Communications

From: Todd Feathers

To Whom It May Concern:

Pursuant to the Pennsylvania Right to Know Act, I hereby request records related to student predictive analytics services used by the district.

For the purpose of this request, the term "student predictive analytics services" means software or computer code that employs machine learning models to generate predictions about individual students or groups of students for one or more of the following purposes:

a) To generate predictions about students' likelihood of dropping out or graduating (these tools are sometimes called early warning systems).
b) To generate predictions about students' likely performance in individual classes, honors or AP programs, and/or on standardized tests (including state assessments, the ACT, SAT, etc.)
c) To generate predictions about students' attentiveness and/or emotional wellbeing.
d) To generate predictions about students' behavior and/or safety (e.g. whether a student is at risk of harming themself or others)
e) To generate predictions that are used to determine whether students are placed in special schools, programs, and/or classes.

My request applies to student predictive analytics services used by the district during the 2022-23 academic year, including those developed in-house by the district, purchased from a vendor, or provided by another agency (e.g. the state department of education or a university).

I request:

1) All contracts and statements of work between the district and outside parties for student predictive analytics services that the district used during the 2022-23 academic year.

2) Records defining the input variables and their weights/relative power for each student predictive analytics service the district used during the 2022-23 academic year (In other words, records defining the data points fed into each predictive model and their respective impacts on the model's output).

3) Records documenting the accuracy (AUC, true/false positive, specificity, lift, etc.) of each student predictive analytics service the district used during the 2022-23 academic year.

4) Any validation studies, disparate impact studies, or other records documenting differences in how the student predictive analytics services the district used during the 2022-23 academic year performed across student groups (e.g. Black students vs. Hispanic students, male students vs. female students).

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 about the operations of a government agency. If you choose to impose fees, I ask that you provide an explanation of the fees, including the hourly wage of the lowest-paid employee capable of fulfilling the request.

If you choose to reject this request or redact portions of responsive documents, I ask that you cite the statutory exemptions and associated case law underlying your decision to withhold each portion from public review.

The requested documents will be made available to the general public, and this request is not being made for commercial purposes.

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 5 business days, as the statute requires.

Sincerely,

Todd Feathers

From: Allentown School District

Attached is the acknowledgment letter for your Right to know.
You will receive an email when we get the information together.

From: Allentown School District


From: openrecords <openrecords@allentownsd.org>
Sent: Monday, September 18, 2023 9:41 AM
To: requests@muckrock.com; openrecords <openrecords@allentownsd.org>
Subject: RE: Pennsylvania Right to Know Act Request: Student Predictive Analytics Services docs

Attached is the acknowledgment letter for your Right to know.
You will receive an email when we get the information together.

From: requests@muckrock.com<mailto:requests@muckrock.com> <requests@muckrock.com<mailto:requests@muckrock.com>>
Sent: Wednesday, September 6, 2023 3:39 PM
To: openrecords <openrecords@allentownsd.org<mailto:openrecords@allentownsd.org>>
Subject: Pennsylvania Right to Know Act Request: Student Predictive Analytics Services docs

Allentown School District
RTK Office
31 South Penn Street
Allentown, PA 18102

September 6, 2023

To Whom It May Concern:

Pursuant to the Pennsylvania Right to Know Act, I hereby request records related to student predictive analytics services used by the district.

For the purpose of this request, the term "student predictive analytics services" means software or computer code that employs machine learning models to generate predictions about individual students or groups of students for one or more of the following purposes:

a) To generate predictions about students' likelihood of dropping out or graduating (these tools are sometimes called early warning systems).
b) To generate predictions about students' likely performance in individual classes, honors or AP programs, and/or on standardized tests (including state assessments, the ACT, SAT, etc.)
c) To generate predictions about students' attentiveness and/or emotional wellbeing.
d) To generate predictions about students' behavior and/or safety (e.g. whether a student is at risk of harming themself or others)
e) To generate predictions that are used to determine whether students are placed in special schools, programs, and/or classes.

My request applies to student predictive analytics services used by the district during the 2022-23 academic year, including those developed in-house by the district, purchased from a vendor, or provided by another agency (e.g. the state department of education or a university).

I request:

1) All contracts and statements of work between the district and outside parties for student predictive analytics services that the district used during the 2022-23 academic year.

2) Records defining the input variables and their weights/relative power for each student predictive analytics service the district used during the 2022-23 academic year (In other words, records defining the data points fed into each predictive model and their respective impacts on the model's output).

3) Records documenting the accuracy (AUC, true/false positive, specificity, lift, etc.) of each student predictive analytics service the district used during the 2022-23 academic year.

4) Any validation studies, disparate impact studies, or other records documenting differences in how the student predictive analytics services the district used during the 2022-23 academic year performed across student groups (e.g. Black students vs. Hispanic students, male students vs. female students).

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 about the operations of a government agency. If you choose to impose fees, I ask that you provide an explanation of the fees, including the hourly wage of the lowest-paid employee capable of fulfilling the request.

If you choose to reject this request or redact portions of responsive documents, I ask that you cite the statutory exemptions and associated case law underlying your decision to withhold each portion from public review.

The requested documents will be made available to the general public, and this request is not being made for commercial purposes.

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 5 business days, as the statute requires.

Sincerely,

Todd Feathers

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