Enter the Algorithms: Could Mobile Games Be Part of College Admissions?

algorithmsGood high school grades don’t always predict college success. A Boston Globe analysis of more than 100 high school valedictorians from the classes of 2005 to 2007 found that 25 percent of them didn’t get a bachelor’s degree within six years. So colleges must try to dig a little deeper to figure out whether an applicant has what it takes to stay on track to earn a diploma.

In addition to assessing students’ grades and essays, college admissions officers have long looked at SAT and ACT scores to help them identify the best applicants. But disruption caused by the coronavirus has led many colleges and universities to make admission exams such as the ACT and SAT optional for applicants.

Even the College Board, maker of the SAT, advised colleges to be flexible about requiring the test in the upcoming admissions cycle because of challenges students face getting to in-person tests and glitches in the board’s efforts to administer exams remotely.

Enter the Algorithms

To fill the void, colleges may consider using algorithms gleaned from other sources designed to gauge students’ potential or hidden skills. For example, they can adapt mobile games, web tracking and machine learning systems to capture and process student data, then convert qualitative inputs into quantitative outcomes.

There’s been growing interest among colleges in this kind of “holistic admissions,” in part due to the movement—well underway even before the pandemic—to make test scores optional, according to Tom Green, an associate executive director at the American Association of Collegiate Registrars and Admissions Officers.

“When used in combination with GPA, [holistic admissions] can greatly increase the predictive quality of success,” he says. “I think people are really looking for more equitable ways of being able to identify good students, especially for groups of students who haven’t tested well.”

Companies selling admissions algorithms say that they are a fairer, more scientific way to predict student success. Behind the scenes, algorithms measure players’ “microbehaviors” and gather information such as whether they repeat mistakes or take experimental paths, to try to identify how players process information and whether they have high potential for learning.

Mobile Games, Web Tracking, Machine Learning Systems

KnackApp games are designed to feel as fun and addictive as Candy Crush and Angry Birds. But just ten minutes of gameplay reveals a “powerful indication of your human operating system,” says Guy Halfteck, founder and CEO of KnackApp. The games are designed “to measure and identify and discover those intangibles that tell us about the hidden talent, hidden abilities, hidden potential for success.”

For admissions, colleges can use the platform to create gamified assessments customized to the traits they’re most interested in measuring and include links to those games in their applications, or even tie them to QR codes that they post in public places. Colleges outside of the U.S. already use KnackApp in student advising, Halfteck says, as does the Illinois Student Assistance Commission.

Meanwhile, colleges hoping to measure whether a particular student will actually enroll if accepted, may turn to tools that track their web browsing practices. At Dickinson College, admissions officers track how much time students who have already made contact with the school spend on certain pages of the institution’s website in order to assess their “demonstrated interest,” says Catherine McDonald Davenport, vice president for enrollment and dean of admissions there.

Many colleges employ the comprehensive services of enrollment management firms, whose machine learning tools try to detect patterns in historical student data, then use those patterns to identify prospective new students who might help colleges meet goals like improving graduation rates, diversifying the campus, or moving up in ranking lists.

“What the machine can do that human beings can’t do is look at thousands of inputs,” says Matt Guenin, CCO at ElectrifAi, a machine learning analytics company. “Sometimes an admissions process can be extremely subjective. We are bringing far more objectivity to the process. We’re essentially trying to use all the information at their disposal to make a better decision.

Full Story: EdSurge (7/10/2020)

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