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.