Online learning has given millions of students convenient entry points into higher education – and been a powerful tool to increase student enrollment for both traditional and online institutions.

According to national data, 25 percent of all higher education students took at least one online course in fall 2013 (Allen & Seaman, 2015), and that number is surely growing. Approximately half of those students choose to pursue full degrees online, while other students intentionally blend online courses into their on-ground academic programs.

Did you ever wonder if 100 percent old-school, campus-based, face-to-face learning might be better for all students? Or that maybe online learning should only be available to certain kinds of students? Maybe online learning is actually slowing students down on their journey to completion… and maybe it penalizes at-risk students most of all.

Today, we can answer all of these questions: “No.”

As an article in this week’s special Learning Analytics issue of the OLC’s Online Learning peer-reviewed journal titled “Retention, Progression, and the Taking of Online Courses” helped reveal the following:

  • Participation in online coursework is not necessarily harmful to student retention.
  • For students at traditional four-year universities, there was no difference in retention among the different delivery modes (on-the ground, blended, or fully-online).
  • At institutions that operate primarily online, students with some online courses (but not all) had slightly better odds of being retained than students who chose coursework either all on-ground or all online.

The research behind these exciting findings was conducted by Scott James, PAR Framework Data Scientist; Professor Dr. Karen Swan, University of Illinois Springfield, and Sandy Daston, PAR Framework Director of Student Success. The full article, “Retention, Progression and the Taking of Online Courses” Online Learning Journal, Vol 20, (2), June 2016. pp 75-96, can be found here.

In recent years, researchers studying student success have come to understand that student populations of online programs are different from those described by IPEDs data, which tracks full-time freshman enrollment and completion.

In their work, James, Swan and Daston compared findings from earlier published studies with fresh analysis of 656,258 student records collected through the Predictive Analytics Reporting (PAR) Framework to see if it was possible to obtain a more nuanced picture of online student success.

Notably, the PAR sample included students from five primarily on-ground community colleges, five primarily on-ground four-year universities, and four primarily online institutions. PAR’s work defining a set of common cross-institutional data definitions allowed the authors to consider potentially differential effects of delivery mode related to Pell grant status, gender, and/or age.

If educational stakeholders hope to extend access to underserved populations, increase completion, focus on improving access to jobs, and improve the quality of educational decision-making at each point in the system, then online learning must be a part of the conversation.

Online learning provides a viable, even an attractive pathway for part-time students, working adults, first-generation, military and other traditionally underserved populations.

It’s time to provide these online learners with targeted interventions and services to maximize their chances of completion, just in the same way that campus-based students are provided with student success services.

PAR is proud to be able to contribute to new perspectives on pathways toward degrees and certifications, catalyzed by opportunities to support the success of these new and post-traditional student populations. The recent article in Online Learning demonstrates that the higher education community can realize the potential for big-data research focused on student success outcomes for all students.

For more information on this important work, join OLC's webinar on Wednesday, July 13, 2016 from 1:00 - 2:00 p.m. ET. Register here.

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