Many students head off to college still needing preparation for entry-level college courses, particularly at the community college level. Massive open online courses (MOOCs) are often seen as a way to offer a flexible and affordable way to improve those skills without paying for remedial classes.
However, MOOCs are also self-directed and self-paced, which can be a problem. Research has shown that community college students in particular struggle with online learning environments, according to Matt Lawson, principal architect at NetApp, who suggested that the solution lies in the support the institution provides its students.
“Of particular significance with MOOCs on community college campuses is identification and support of students at academic risk,” Lawson wrote in a column for eCampus News. “Big data and analytics are a formidable tool that can help identify these at-risk students and thereby enable much-needed proactive intervention to help those students succeed in college.”
While serving as director of enterprise services for community colleges in Virginia, Lawson found that student engagement could be recorded through the number of times they clicked into the online courseware. Using that information allowed the system to determine which students were engaged with the material and which were struggling.
“This sort of targeted intervention can prove critical at the community college level, and could prove to be a boost to student retention and attrition—two top goals of any institution of higher education,” he wrote.