Student Predictive Analytics Services docs
It is a clone of this request.
| Submitted | Sept. 3, 2023 |
| Est. Completion | Sept. 22, 2023 |
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Communications
From: Todd Feathers
To Whom It May Concern:
Pursuant to the Georgia Open Records Act, I hereby request records related to student predictive analytics services used by the university.
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 university.
c) To generate predictions about prospective students' financial aid needs and/or likely response to different financial aid packages.
d) To generate predictions about prospective students' likelihood of passing a class, re-enrolling for another term (retention), and/or graduation.
My request applies to all student predictive analytics services used by the university during the 2022-23 academic year, including those developed in-house by the university or purchased by the university from a vendor.
I request:
1) All contracts and statements of work between the university and outside parties for student predictive analytics services that the university 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 university used during the 2022-23 academic year (In other words, records defining each data point fed into each machine learning model and its respective impact on the model's output).
3) Records documenting the accuracy (AUC, true/false positive, lift, etc.) of each student predictive analytics service the university used during the 2022-23 academic year.
4) Validation studies, disparate impact studies, or other records comparing how each student predictive analytics service used by the university during the 2022-23 academic year performs for different 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 3 business days, as the statute requires.
Sincerely,
Todd Feathers
From: Muckrock Staff
To Whom It May Concern:
I wanted to follow up on the following Georgia Open Records Act request, copied below, and originally submitted on Sept. 3, 2023. Please let me know when I can expect to receive a response.
Thanks for your help, and let me know if further clarification is needed.
From: University of Georgia
Mr. Feathers—
This is in response to your request for documents under the Georgia Open Records Act, filed after hours Sunday, September 3, 2023. For the purposes of the three-day response, we deem your request to be received Tuesday, September 5, 2023, because the university was closed Monday, September 4, 2023, in observance of the Labor Day holiday. This response is in accordance with the three-day period of response pursuant to O.C.G.A. § 50-18-71(b)(2).
You have requested “records related to student predictive analytics services used by the university.” Specifically, you say your “request applies to all student predictive analytics services used by the university during the 2022-23 academic year, including those developed in-house by the university or purchased by the university from a vendor.”
“I request:
1) All contracts and statements of work between the university and outside parties for student predictive analytics services that the university 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 university used during the 2022-23 academic year (In other words, records defining each data point fed into each machine learning model and its respective impact on the model's output).
3) Records documenting the accuracy (AUC, true/false positive, lift, etc.) of each student predictive analytics service the university used during the 2022-23 academic year.
4) Validation studies, disparate impact studies, or other records comparing how each student predictive analytics service used by the university during the 2022-23 academic year performs for different student groups (e.g. Black students vs. White students, male students vs. female students).”
With respect to your request, we have reached out to units/departments across campus where responsive records may exist so that we can prepare search, retrieval, review, and production time/cost estimates. We anticipate having an update for you by September 22, 2023, if not sooner.
At this point, some information may be exempt from release in accordance with O.C.G.A. § 50-18-72(a)(1), (20)(A), (21) and (37). As we process your request further, there may additional exemptions. We will notify you of any additional exemptions no later than three business days after the records have been retrieved in accordance with O.C.G.A. § 50-18-71(d).
Regards,
Bob Taylor
Division of Marketing & Communications
Open Records Manager
Hodgson Oil Building, Suite 200 N | 286 Oconee St. | Athens, GA 30602
706-542-8090 | btaylor@uga.edu<mailto:btaylor@uga.edu> | www.uga.edu<http://www.uga.edu/>
[University of Georgia]
[Facebook]<https://www.facebook.com/uga.edu> [Twitter] <https://twitter.com/universityofga> [Instagram] <https://www.instagram.com/universityofga/> [Linkedin] <https://www.linkedin.com/edu/school?id=18190> [Youtube] <https://www.youtube.com/uga> [Snapchat] <https://www.snapchat.com/add/university-ga>
From: University of Georgia
Mr. Feathers—
This is a follow-up and final response to your Open Records Act request for “records related to student predictive analytics services used by the university.” Specifically, you say your “request applies to all student predictive analytics services used by the university during the 2022-23 academic year, including those developed in-house by the university or purchased by the university from a vendor.”
With respect to your request, there are no responsive documents.
Regards,
Bob Taylor
Division of Marketing & Communications
Open Records Manager
Hodgson Oil Building, Suite 200 N | 286 Oconee St. | Athens, GA 30602
706-542-8090 | btaylor@uga.edu<mailto:btaylor@uga.edu> | www.uga.edu<http://www.uga.edu/>
[University of Georgia]
[Facebook]<https://www.facebook.com/uga.edu> [Twitter] <https://twitter.com/universityofga> [Instagram] <https://www.instagram.com/universityofga/> [Linkedin] <https://www.linkedin.com/edu/school?id=18190> [Youtube] <https://www.youtube.com/uga> [Snapchat] <https://www.snapchat.com/add/university-ga>
From: Todd Feathers
Hello Bob,
Thank you very much for your help with this request. To clarify, are you saying that there are no responsive records because UGA doesn't use any student predictive analytics services?
I would be very surprised if the university didn't use any of these tools. For example, UGA's LMS is powered by Desire2Learn's Brightspace and includes the Student Success System predictive model, according to these instructions for UGA instructors: http://rxidto.uga.edu/InstructorBasics.pdf.
Best,
Todd
From: Muckrock Staff
To Whom It May Concern:
I'm following up on the following Georgia Open Records Act request, copied below, and originally submitted on Sept. 3, 2023. You had previously indicated that it would be completed on Sept. 22, 2023. I wanted to check on the status of my request, and to see if there was a new estimated completion date.
Thanks for your help, and let me know if further clarification is needed.
From: University of Georgia
Mr. Feathers—
This is in response to your Sept. 21 email asking us for clarification. You write, “are you saying that there are no responsive records because UGA doesn't use any student predictive analytics services?”
As we stated on Sept. 21, we are saying there are no documents responsive to your request for “records related to student predictive analytics services used by the university.” We checked with our Office of the Vice President for Instruction.
Bob Taylor
Division of Marketing & Communications
Open Records Manager
Hodgson Oil Building, Suite 200 N | 286 Oconee St. | Athens, GA 30602
706-542-8090 | btaylor@uga.edu<mailto:btaylor@uga.edu<mailto:btaylor@uga.edu%3cmailto:btaylor@uga.edu>> | www.uga.edu<http://www.uga.edu/<http://www.uga.edu%3chttp:/www.uga.edu/>>
[University of Georgia]
[Facebook]<https://www.facebook.com/uga.edu> [Twitter] <https://twitter.com/universityofga> [Instagram] <https://www.instagram.com/universityofga/> [Linkedin] <https://www.linkedin.com/edu/school?id=18190> [Youtube] <https://www.youtube.com/uga> [Snapchat] <https://www.snapchat.com/add/university-ga>
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~WRD0000