Teens rate their college chances online

Add "chance me" to the list of must-know online interactions for teens.

The Los Angeles Times points to a new wrinkle in the college admissions process – students are posting their GPAs, test scores, extracurricular activities, and other personal information online for their peers to rate.

Sites like Mychances.net, Yahoo Answers, and City-data.com, have respondents "calculating" students' likelihood of admission to top schools. The "What Are My Chances?" forum on CollegeConfidential.com is the most popular place for "chance me" interactions, according to the Times article.

Students' postings are written in a ritualized vernacular: "Chance me, I'll chance you back." Clubs, sports, volunteer work, and leadership positions are "ECs" -- extracurricular activities. A "match" is a good bet, a "safety" is a fallback, a "reach" is a stretch -- but a "hook" could get you in.

The playground-caliber nature of some exchanges – and the weight some posters are putting behind the responses they receive – have admissions officials rolling their eyes.

"The thing that worries me is that they are more frequently turning to each other and less frequently turning to someone who can actually answer the question," said Bruce Poch, dean of admissions at Pomona College. "Some of them are getting false encouragement, some are getting a little ego massage, [but] they aren't necessarily getting an answer."

College hopefuls can add that bogus admissions advice to the list of things to watch out for as the college search and application process has moved online. Facebook presents its own pitfalls. Late last year Butler University communications coordinator Brad Ward uncovered workers from a company called College Prowler posing as incoming freshmen and creating "Class of 2013" groups on the social networking site.

Meanwhile, The New York Times ran a story this week on how colleges are adjusting admissions procedures to cope with the recession's new realities. The take-home message? The old statistical models of how many to accept and when don't work.