Student Predictive Analytics Services docs
It is a clone of this request.
| Submitted | Sept. 5, 2023 |
| Est. Completion | None |
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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 college.
For the purpose of this request, the term "student predictive analytics services" means software or computer code that employ 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 which prospective student names/contact information to buy from vendors such as the College Board, ACT, Cappex, etc. for advertising and recruiting.
b) To generate predictions about prospective students' likelihood to apply to, be admitted to, and/or enroll at the college.
c) To generate predictions about prospective students' financial aid needs and/or likely response to different financial aid packages.
d) To generate predictions about enrolled students' likelihood of passing a class, re-enrolling for another term (retention), and/or graduation (these tools are sometimes called early warning systems).
My request applies to student predictive analytics services used by the college during the 2022-23 academic year, including those developed in-house by the college or purchased from a vendor.
I request:
1) All contracts and statements of work between the college and outside parties for student predictive analytics services that the college 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 college 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 college 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 college used during the 2022-23 academic year performed across student groups (e.g. Black students vs. White 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: Muckrock Staff
Hello,
Please find the request form attached. Thank you for your help with this request.
Sincerely,
MuckRock
From: Montgomery County Community College
September 6, 2023
Todd Feathers
requests@muckrock.com<mailto:requests@muckrock.com>
MuckRock News, DEPT MR151614, 263 Huntington Ave
Boston, MA 02115
Re: Right to Know Request 2023090601
Dear Todd:
We have received your request for information pursuant to the Pennsylvania Right-To-Know law.
On September 6, 2023, you requested, “ Pursuant to the Pennsylvania Right to Know Act, I hereby request records related to student predictive analytics services
used by the college.
For the purpose of this request, the term "student predictive analytics services" means software or computer code that employ 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 which prospective student names/contact information to buy from vendors such as the
College Board, ACT, Cappex , etc. for advertising and recruiting.
b) To generate predictions about prospective students' likelihood to apply to, be admitted to, and/or enroll at the college.
c) To generate predictions about prospective students' financial aid needs and/or likely response to different financial aid
packages.
d) To generate predictions about enrolled students' likelihood of passing a class, re-enrolling for another term (retention), and/or graduation (these tools are sometimes called early warning systems).
My request applies to student predictive analytics services used by the college during the 2022-23 academic year,
including those developed in-house by the college or purchased from a vendor.
I request:
1) All contracts and statements of work between the college and outside parties for student predictive analytics services
that the college 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
college 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 college 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 college used during the 2022-23 academic year performed across student groups
( e.g. Black students vs. White students, male students vs. female students). ”
The request for records is denied. Th e college did not use “student predictive analytics services” during the 2022-2023 academic year ; the records requested do not exist.
Your request is denied for the following reasons, as permitted by Section 708 of the Right-to-Know Law:
* The college does not currently use “student predictive analytics services . Due to this, Montgomery County Community College has denied your request because the records which you requested do not exist. This is supported by Section 705 of the Right-to-Know Law (“RTKL”), states that “an agency shall not be required to create a record which does not currently exist.”
Because the Re quest has been denied, you are advised of your right to appeal this decision to the Office of Open Records (OOR). Any such appeal must be in writing and submitted to the OOR within fifteen (15) business days of the date of this letter. It also must include the legal basis for your belief that you were improperly denied records and address each basis for denial proffered by the College. The appeal should be directed to: Office of Open Records, 333 Market Street, 16 th Floor, Harrisburg, PA 17101-2234; by fax at 717-425-5343; by email to openrecords@pa.gov <mailto:openrecords@pa.gov> ; or www.openrecords.pa.gov <http://www.openrecords.pa.gov/> .
Please be advised that this correspondence will serve to close this record with our office as permitted by law .
Respectfully,
Celeste Schwartz
Right-to-Know Officer
Montgomery County Community College
Advanced Technology Center, 3rd Floor
Information Technology Department
340 DeKalb Pike
Blue Bell, PA 19422
(215) 641-6492
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