Demonstrated Interest (DI) vs Likelihood to Enroll (LTE)

[Anonymous]

Anonymous wrote:Someone needs to reverse-engineer the algorithms and post the findings to help with transparency and level the playing field.

Agree, but I'm still watching the video, and they mention "hundreds of variables" that can be considered.

They also play with the variables - what if we change a variable (e.g. send spam) - what happens to the likelihood score.

[Anonymous]

Anonymous wrote:Someone posted a you tube link of essentially a zoom meeting pitching their services - probably was removed above. Anyway, it's quite interesting - individual likelihood of attending score. Still listening, but wondering whether, and how, this score would fit into an admission decision.

I posted the link and it is still in the thread. I don't work for the company (I'm a professor) and my university doesn't use their software. My apologies if I violated the board norms/rules. I thought it would be helpful compared to explaining anonymously on this board how it works.

[Anonymous]

Anonymous wrote:

Anonymous wrote:Someone needs to reverse-engineer the algorithms and post the findings to help with transparency and level the playing field.

Agree, but I'm still watching the video, and they mention "hundreds of variables" that can be considered.

They also play with the variables - what if we change a variable (e.g. send spam) - what happens to the likelihood score.

It's difficult to find research articles that are not behind a paywall. I did find an article on Occidental's use of enrollment management algorithms that you may find interesting: https://www.mdpi.com/2306-5729/4/2/65/htm

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:Someone needs to reverse-engineer the algorithms and post the findings to help with transparency and level the playing field.

Agree, but I'm still watching the video, and they mention "hundreds of variables" that can be considered.

They also play with the variables - what if we change a variable (e.g. send spam) - what happens to the likelihood score.

It's difficult to find research articles that are not behind a paywall. I did find an article on Occidental's use of enrollment management algorithms that you may find interesting: https://www.mdpi.com/2306-5729/4/2/65/htm

Thank you!

[Anonymous]

Anonymous wrote:

Anonymous wrote:Someone posted a you tube link of essentially a zoom meeting pitching their services - probably was removed above. Anyway, it's quite interesting - individual likelihood of attending score. Still listening, but wondering whether, and how, this score would fit into an admission decision.

I posted the link and it is still in the thread. I don't work for the company (I'm a professor) and my university doesn't use their software. My apologies if I violated the board norms/rules. I thought it would be helpful compared to explaining anonymously on this board how it works.

I thought it was interesting- thanks.

[Anonymous]

One of the studies cited found Class Size to be one of the top factors for LTE. Anyone knows how that cuts/ what the association is?

[Anonymous]

I watched the video and read the Occidental article, and it is pretty disheartening. My DC does not fit any of these prediction models, as in the items college believe will influence a student actually were not important parts of the decision making process.

[Anonymous]

Anonymous wrote:I watched the video and read the Occidental article, and it is pretty disheartening. My DC does not fit any of these prediction models, as in the items college believe will influence a student actually were not important parts of the decision making process.

Could you share some examples? Thanks. I’m trying to understand all this.

[Anonymous]

Anonymous wrote:

Anonymous wrote:I watched the video and read the Occidental article, and it is pretty disheartening. My DC does not fit any of these prediction models, as in the items college believe will influence a student actually were not important parts of the decision making process.

Could you share some examples? Thanks. I’m trying to understand all this.

And did you understand the class size factor?