vibeffect’s individual variables include things like whether someone has held a job, whether he or she likes working independently or on a team, and if the person is apt to ask for help (or not). On the college side, vibeffect factors in a school’s use of innovative teaching techniques, transportation options, and social opportunities. “Through that, we’re able to create correlations between an individual and the campus features that will help them thrive,” says Elena Maria Cox, co-founder and CEO.

For current college students, Cox says vibeffect can help the 30 to 40 percent of individuals who transfer to other institutions and – even more ambitiously – help reduce the 50 percent college dropout rate. “For the freshman who is unhappy and considering a transfer, we have individualized, self-assessments to help make those decisions,” says Cox, who calls the typical institution’s student retention efforts very “one-dimensional” in nature.

“A university and its professors are basically standing behind a one-way mirror, looking at the student’s behavior from yesterday and judging the future based on that information,” she explains. “Using data and predictive analytics, the same schools and instructors can determine which campus resources and features will put students on the path to thriving and graduating.”

So how does a student determine his or her personal traits, and how does the algorithm match those with the right college ecosystem?

Using a background steeped in research, vibeffect set a baseline to find out how many college students in the U.S. are currently “thriving” at a high level. Thriving was broken out into four separate levels: low, medium-low, medium-high, and high. According to the company, those thriving at a high level experience the maximum benefits from a specific college ecosystem, and demonstrate this through heightened academic and social integration and a deeper sense of happiness.

Using a team of experts from different fields, a national survey was developed that gathered 263 variables about how college students at four-year campuses are experiencing their college on several dimensions aligned to the definition of thriving. According to the company, this was the first research effort to define, on a national scale, what qualitative aspects of an entire college ecosystem can be identified and quantified.

The inaugural data set, established in 2013, provided the first consumer-based Index on how many students are thriving at a high level in four-year colleges. The data is updated annually, and the current data set includes more than 1.2 Million points on a representative set of students in over 1000 campuses across the country. The Index aims to be a snapshot of what is happening at a moment in time with real students in real colleges nationwide.

The initial Index found that only 1-in-5 college students are thriving at a high level and may be the root cause of the nation’s current 50 percent dropout rate, says the company.

With the Index in place, an algorithm was created using predictive sciences. The algorithm has the ability to leverage the 1.2 million data points to run predictive simulations regarding challenges in today’s higher education system.

For instance, the algorithm found that college students that are first generation Americans from low-income families have a higher probability of thriving than their wealthy peers. It also found that individuals that start in a two-year community college and transfer to a four-year university are more likely to thrive at a high level. In other words, thriving is not based on financial background, race or other homogeneous measures; but rather an individual’s confidence that what they are getting from the college experience will improve their lives and future. That desire, along with the pairing of an individual’s traits to a specific college ecosystem, creates the perfect environment for “high thriving.”

In order to help prospective students understand what their traits are and what to look for in a college ecosystem, a survey instrument was created that contains 66 individual traits and 100 campus features. The survey instrument, coupled with the algorithm, creates a predictive Model. Once a student interacts with the survey instrument, the Model provides a set of resources to predict the ideal campus environment for that individual.

The algorithm used in the Model is tested and re-tested using artificial intelligence methods and run through thousands of simulations until it produces “an acceptable probability accuracy,” noted the company. Depending on how many individual variables are captured, the algorithm has up to a 90 percent accuracy rating.

The Model does not say which college to attend by name, since the ecosystem of a college or university often changes based on the students in attendance and the faculty that are currently on staff. Campus clubs, among other things, may also come and go, changing the ecosystem in a unique way.

(Next page: Selling point for colleges; Beyond SATs)

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