{"id":8051,"date":"2023-01-23T20:20:51","date_gmt":"2023-01-24T01:20:51","guid":{"rendered":"https:\/\/www.sanmita.com\/?p=8051"},"modified":"2023-10-19T09:00:31","modified_gmt":"2023-10-19T13:00:31","slug":"higher-ed-admissions-the-applicants-who-got-away-and-how-to-find-them-again","status":"publish","type":"post","link":"https:\/\/www.sanmita.com\/higher-ed-admissions-the-applicants-who-got-away-and-how-to-find-them-again\/","title":{"rendered":"Lost in the Admissions Shuffle: Tracking Down Missing Higher Ed Applicants"},"content":{"rendered":"

Sometimes we just can’t finish what we started, and this is especially true for college applicants. But what if admission officers had technology in place to capture and reach out to potential candidates who may have had an interest but did not submit an application? They do. Using tracking software on their school website, or cookies, colleges are collecting more data about prospective students than ever before \u2014 part of an effort, administrators say, to make better predictions about which students are the most likely to apply, accept an offer and enroll.<\/p>\n

In fact, before many schools even look at an application, they comb through prospective students\u2019 personal data, such as web-browsing habits and financial history. (Washington Post, October 2019.) <\/em>Case in point: When one student visited the site last year, the software automatically recognized who she was based on a piece of code (cookie) which it had placed on her computer during a prior visit. The software sent an alert to the school\u2019s assistant director of admissions containing the student\u2019s name, contact information and details about her life and activities on the site, according to internal university records reviewed by The Washington Post. The email said she was a graduating high school senior in Little Chute, Wis., of Mexican descent who had applied to UW-Stout.<\/p>\n

The admissions officer also received a link to a private profile of the student, listing all 27 pages she had viewed on the school\u2019s website and how long she spent on each one. A map on this page showed her geographical location, and an \u201caffinity index\u201d estimated her level of interest in attending the school. Her score of 91 out of 100 predicted she was highly likely to accept an admission offer from UW-Stout, the records showed.<\/p>\n

At the time of the Washington Post article, records showed that at least 44 public and private universities in the United States work with outside consulting companies to collect and analyze data on prospective students, by tracking their web activity or formulating predictive scores to measure each student\u2019s likelihood of enrolling.<\/p>\n

“Data Mining” and “Demonstrated Interest”<\/h3>\n

Data mining and analytics is not a new concept in the college admissions process. Many schools have been using analytics to identify and target prospective students that, on paper, seem to be a good fit for the school. Collecting data on interested students takes the analytics process a step closer to Big Brother territory by capturing data without the student\u2019s knowledge.<\/p>\n

The “demonstrated interest” is now calculated by collecting data from electronic interactions between a university and a prospective student. The data that colleges collect from digital interactions includes:<\/p>\n