Using AI for college admission ratings

[Anonymous]

Anonymous wrote:

Anonymous wrote:Have been using gpt to estimate admission ratings, found it very helpful. Basically plug in the stats and ECs, and ask gpt to evaluate each of the following:
Academic
Extracurricular
Athletic
Personal

Academic rating is based on rigor in the school context, gpa in the school context, test score, recommendation (if teachers told you what they are going to write).

EC rating is based on leadership, depth, impact, initiative, etc.

Athletic is the most definitive. DC got a score of 3. 1 is for D1 recruit, 2 is for D3 recruit. 3 is for varsity / club level.

It's fun.

To do this well or completely, you need to input the scoring rubric FOR each college along with the CDS (showing what the school values). Some of the scoring rubric for certain schools is in the link below. Its different for each school - as you can see even in the link some schools view ECs more importantly than other schools.

https://www.dcurbanmom.com/jforum/posts/list/1224166.page

I did something similar, using that old, linked thread for my '25 graduate. It was pretty accurate, to be honest - kid is headed to a T10.

Used the paid version of Claude and turned off data sharing. You have to do each school separately and upload as much info as you can get your hands on for each college, one by one (save each as a new "Project" in Claude).
For each college, include all admissions info you can get your hands on. I included transcripts of interviews with AO from the school, material from the school's website, and any Reddit posts where someone reviewed their application in the past few years and viewed their file—also included info from our high school on # admitted each year.
Then, uploaded a draft pdf of the Common App for that school (so Claude had access to all info about the applicant - incl major, essays, ECs).
Next, ask for a very detailed review by the categories or scoring rubric for that particular college. Continue to "push" the AI bot to think harder and more critically, including identify the weakness in the application.
Lastly, give it Reddit r/collegeresults data too for that school in the last 2 years to see if it can add that data to its decision-making.

[Anonymous]

Someone viewed his Penn admissions file. Here is what is on his admissions file:

M/A: (scale of 1-4, 4 is highest) Match and Alignment -- Student's developed interest in Penn, fit with Penn programs, and talent within academic priorities

E: (scale of 1-6, 6 is highest) Excellence of Mind -- Student's pursuit of academic interests and achievements within school/community context

I: (scale of 1-6, 6 is highest) Impact in your space -- Student as a catalyst for impact/involvement with school/community context

AI: Academic index, a calculated value combining GPA and ACT/SAT

https://www.reddit.com/r/ApplyingToCollege/comments/ydb2pb/i_viewed_my_upenn_admissions_file_and/

[Anonymous]

Amazing tips. Headed to Claude now.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:Have been using gpt to estimate admission ratings, found it very helpful. Basically plug in the stats and ECs, and ask gpt to evaluate each of the following:
Academic
Extracurricular
Athletic
Personal

Academic rating is based on rigor in the school context, gpa in the school context, test score, recommendation (if teachers told you what they are going to write).

EC rating is based on leadership, depth, impact, initiative, etc.

Athletic is the most definitive. DC got a score of 3. 1 is for D1 recruit, 2 is for D3 recruit. 3 is for varsity / club level.

It's fun.

To do this well or completely, you need to input the scoring rubric FOR each college along with the CDS (showing what the school values). Some of the scoring rubric for certain schools is in the link below. Its different for each school - as you can see even in the link some schools view ECs more importantly than other schools.

https://www.dcurbanmom.com/jforum/posts/list/1224166.page

I did something similar, using that old, linked thread for my '25 graduate. It was pretty accurate, to be honest - kid is headed to a T10.

Used the paid version of Claude and turned off data sharing. You have to do each school separately and upload as much info as you can get your hands on for each college, one by one (save each as a new "Project" in Claude).
For each college, include all admissions info you can get your hands on. I included transcripts of interviews with AO from the school, material from the school's website, and any Reddit posts where someone reviewed their application in the past few years and viewed their file—also included info from our high school on # admitted each year.
Then, uploaded a draft pdf of the Common App for that school (so Claude had access to all info about the applicant - incl major, essays, ECs).
Next, ask for a very detailed review by the categories or scoring rubric for that particular college. Continue to "push" the AI bot to think harder and more critically, including identify the weakness in the application.
Lastly, give it Reddit r/collegeresults data too for that school in the last 2 years to see if it can add that data to its decision-making.

For DC, we were using school data not using outside data because the school gpa is deflated. Calibration is done using only our school's past data, whatever that is available.
You can instruct gpt to ignore outside data but it's not necessary.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:Have been using gpt to estimate admission ratings, found it very helpful. Basically plug in the stats and ECs, and ask gpt to evaluate each of the following:
Academic
Extracurricular
Athletic
Personal

Academic rating is based on rigor in the school context, gpa in the school context, test score, recommendation (if teachers told you what they are going to write).

EC rating is based on leadership, depth, impact, initiative, etc.

Athletic is the most definitive. DC got a score of 3. 1 is for D1 recruit, 2 is for D3 recruit. 3 is for varsity / club level.

It's fun.

To do this well or completely, you need to input the scoring rubric FOR each college along with the CDS (showing what the school values). Some of the scoring rubric for certain schools is in the link below. Its different for each school - as you can see even in the link some schools view ECs more importantly than other schools.

https://www.dcurbanmom.com/jforum/posts/list/1224166.page

I did something similar, using that old, linked thread for my '25 graduate. It was pretty accurate, to be honest - kid is headed to a T10.

Used the paid version of Claude and turned off data sharing. You have to do each school separately and upload as much info as you can get your hands on for each college, one by one (save each as a new "Project" in Claude).
For each college, include all admissions info you can get your hands on. I included transcripts of interviews with AO from the school, material from the school's website, and any Reddit posts where someone reviewed their application in the past few years and viewed their file—also included info from our high school on # admitted each year.
Then, uploaded a draft pdf of the Common App for that school (so Claude had access to all info about the applicant - incl major, essays, ECs).
Next, ask for a very detailed review by the categories or scoring rubric for that particular college. Continue to "push" the AI bot to think harder and more critically, including identify the weakness in the application.
Lastly, give it Reddit r/collegeresults data too for that school in the last 2 years to see if it can add that data to its decision-making.

For DC, we were using school data not using outside data because the school gpa is deflated. Calibration is done using only our school's past data, whatever that is available.
You can instruct gpt to ignore outside data but it's not necessary.

Does your school data include ECs? Awards? Other soft metrics?
I think that's much more important that GPA and scores, after you meet the threshold.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:Have been using gpt to estimate admission ratings, found it very helpful. Basically plug in the stats and ECs, and ask gpt to evaluate each of the following:
Academic
Extracurricular
Athletic
Personal

Academic rating is based on rigor in the school context, gpa in the school context, test score, recommendation (if teachers told you what they are going to write).

EC rating is based on leadership, depth, impact, initiative, etc.

Athletic is the most definitive. DC got a score of 3. 1 is for D1 recruit, 2 is for D3 recruit. 3 is for varsity / club level.

It's fun.

To do this well or completely, you need to input the scoring rubric FOR each college along with the CDS (showing what the school values). Some of the scoring rubric for certain schools is in the link below. Its different for each school - as you can see even in the link some schools view ECs more importantly than other schools.

https://www.dcurbanmom.com/jforum/posts/list/1224166.page

I did something similar, using that old, linked thread for my '25 graduate. It was pretty accurate, to be honest - kid is headed to a T10.

Used the paid version of Claude and turned off data sharing. You have to do each school separately and upload as much info as you can get your hands on for each college, one by one (save each as a new "Project" in Claude).
For each college, include all admissions info you can get your hands on. I included transcripts of interviews with AO from the school, material from the school's website, and any Reddit posts where someone reviewed their application in the past few years and viewed their file—also included info from our high school on # admitted each year.
Then, uploaded a draft pdf of the Common App for that school (so Claude had access to all info about the applicant - incl major, essays, ECs).
Next, ask for a very detailed review by the categories or scoring rubric for that particular college. Continue to "push" the AI bot to think harder and more critically, including identify the weakness in the application.
Lastly, give it Reddit r/collegeresults data too for that school in the last 2 years to see if it can add that data to its decision-making.

For DC, we were using school data not using outside data because the school gpa is deflated. Calibration is done using only our school's past data, whatever that is available.
You can instruct gpt to ignore outside data but it's not necessary.

Does your school data include ECs? Awards? Other soft metrics?
I think that's much more important that GPA and scores, after you meet the threshold.

DC can only gather whatever available. We know some kids’ ECs. School matriculation instagram has some information. Most kids at our school are doing mid ECs, a tier below Reddit kids’ ECs.

DC wants gpt to conduct independent evaluation based on DC’s input. We think it already learnt from internet, instructing gpt to look at some outside data in particular may be biased.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:Have been using gpt to estimate admission ratings, found it very helpful. Basically plug in the stats and ECs, and ask gpt to evaluate each of the following:
Academic
Extracurricular
Athletic
Personal

Academic rating is based on rigor in the school context, gpa in the school context, test score, recommendation (if teachers told you what they are going to write).

EC rating is based on leadership, depth, impact, initiative, etc.

Athletic is the most definitive. DC got a score of 3. 1 is for D1 recruit, 2 is for D3 recruit. 3 is for varsity / club level.

It's fun.

To do this well or completely, you need to input the scoring rubric FOR each college along with the CDS (showing what the school values). Some of the scoring rubric for certain schools is in the link below. Its different for each school - as you can see even in the link some schools view ECs more importantly than other schools.

https://www.dcurbanmom.com/jforum/posts/list/1224166.page

I did something similar, using that old, linked thread for my '25 graduate. It was pretty accurate, to be honest - kid is headed to a T10.

Used the paid version of Claude and turned off data sharing. You have to do each school separately and upload as much info as you can get your hands on for each college, one by one (save each as a new "Project" in Claude).
For each college, include all admissions info you can get your hands on. I included transcripts of interviews with AO from the school, material from the school's website, and any Reddit posts where someone reviewed their application in the past few years and viewed their file—also included info from our high school on # admitted each year.
Then, uploaded a draft pdf of the Common App for that school (so Claude had access to all info about the applicant - incl major, essays, ECs).
Next, ask for a very detailed review by the categories or scoring rubric for that particular college. Continue to "push" the AI bot to think harder and more critically, including identify the weakness in the application.
Lastly, give it Reddit r/collegeresults data too for that school in the last 2 years to see if it can add that data to its decision-making.

How do you upload reddit r/college results data? By link or screenshots? Do you also upload scoir scatterplot/admit information by university? How? Screenshot or link? Trying to do this correctly and any help would be appreciated!