Jul 14 2020

How to Increase College Success for Underserved Students

Explore how online learning can become a new frontier for student success — especially for disadvantaged students.

At a time when severe budget cuts in higher education could push some institutions to emphasize legacy admissions, it can be easy to overlook the needs of low-income students. But we have a moral imperative to prioritize our most vulnerable student populations.

During times of economic crisis, college success is even more important for disadvantaged students. The vast majority of jobs created after economic downturns typically require applicants to have a college degree — or at least some college education. Ninety-five percent of the jobs created during the Great Recession recovery were given to candidates with a college education.

That is why it is deeply concerning that fewer low-income students are planning to return to college for the 2020-2021 academic year. According to federal data, about 250,000 fewer students from the lowest income backgrounds renewed their Free Application for Federal Student Aid. Compared with this time last year, overall FAFSA renewals have dropped by nearly 5 percent.

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Recent Pell Grant applications show a similar troubling pattern. About 24 percent fewer Pell Grant–eligible applicants from the lowest income group are planning to return to college, and 20 percent fewer students whose families earn between $25,000 and $50,000 have reapplied for Pell Grants.

While the primary reason for this decline is likely due to personal financial uncertainties, there are some steps that universities and colleges can take to help bridge the gap. The unprecedented shift to digital education is creating an opportunity for higher education to rethink how technology and data analytics can support the success of underserved students.

Using AI and Data to Help Underserved Students

Online learning can potentially give colleges and universities more student data than schools have ever had before. With great power comes great responsibility.

Studies show students of lower socioeconomic status tend to have had lower quality early education experiences. Without as strong of an educational foundation as their affluent classmates, it can be difficult for them to meet the demands of higher education without additional support.

But when one professor is lecturing hundreds of students a week, it is not humanly possible for an educator to support the distinct learning needs of each disadvantaged student. This is where AI and data analytics can help facilitate more student-centered learning.

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I believe we will see a rise in emerging support systems that not only engage students, but also evaluate their strengths and weaknesses.

Case in point: If everyone is reading electronic textbooks, it is potentially possible for professors to track if students are actually doing the readings. How much time do students spend on reading assignments? Do they skip chapters? Do they highlight and engage with the text?

Having this kind of data can enable schools to examine the root causes behind poor academic performance, which in turn allows faculty to form more student-centered instructional strategies. Why are some students not reading? Are their reading levels not where they should be? Can the school offer more specialized support to help these students get up to speed?

Or are these students single parents who do not have time to read because they are working multiple jobs? In that case, these students might benefit from a different set of assignments tailored to their learning and personal needs.

Since educators cannot obtain this type of data from physical textbooks, online learning has the potential to open a new frontier for student success. If universities and colleges want to develop better, data-informed strategies to support underserved students, companies will create the technology to make this possible.

This article is part of EdTech: Focus on Higher Education’s UniversITy blog series.

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