Internet Learning Volume 6, Number 2, Fall 2017/Winter 2018 | Page 16

Better Together: How Blending Course Modalities Impacts Student Persistence
Looking at the set of data features
across populations is a simplistic
but useful first step in understanding
the differences between them.
Within the rank-ordered list of
data features for each population at
each institution, we can also search for
any significant differences in feature
values. In Table 3, four specific data
features are compared across three different
course-taking populations. For
two 4-year, two 2-year, and one proprietary
institution, we first compare
students who are blending their course
modality first with students who take
all courses on-ground, we then compare
students who are blending to
students who take all online courses.
The set of data features examined are
Average Credits Attempted (Cumulative),
Average Number of Days Enrolled
Before Start (Current Term), Age, and
GPA (Cumulative). They represent academic,
behavioral, and demographic
characteristics. For each population
comparison, Blended is set as the baseline
group, and either Online or Onground
is established as the comparator
group. Feature values are shown for
each group. The last column displays
the Normalized Difference value which
is difference between the two population
means, divided by the pooled
standard deviation.
What can be seen from the table
is first, that students who blend
their curricula have consistently higher
credit hour loads than either fully onground
or fully online students. This is
seen across all the institutions examined,
and holds even for the proprietary
institutions where the majority of
courses are offered online. The Average
Number of Days Enrolled Before Start
data feature is a measure of when the
student enrolled for the term, where
larger values represent perhaps a more
purposeful approach to their academic
career. With one exception, the blended
students are enrolling earlier than the
other student populations. Age and Cumulative
GPA have less consistency in
terms of predictiveness among the student
course-taking populations, with
some groups having a normalized difference
above that of the Blended group,
and some below.
Discussion
Before summarizing the findings
above, we need to review
the approach taken in the study.
We are examining the differences between
populations of students within
individual institutions by course-taking
modality. By looking at the delta of
persistence risk among the populations
on an institution-by-institution basis,
rather than in aggregate, we can reduce
concerns about apples to oranges comparisons.
While there are certainly differences
in the populations that typically
take different course modalities, for
example, fully online students tend to
be older than fully on-ground students,
this approach accounts for differences
in students that are attending a public
4-year institution when compared to a
proprietary institution.
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