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Reflections on Enrollment Numbers and Success Rates
at the openHPI MOOC Platform
Christoph Meinel, Christian Willems, Jan Renz and Thomas Staubitz
Comparing the numbers of enrolled students (during
course term and in total) with the active participants actually
questions the high participant numbers that providers
of massive open online courses publish. The values indicate,
that roughly between 55% and 70% of all enrolled
students in a course never submit any contribution to
the platform. These users either register for the course
before the start date and back off when the course starts
or just take a sneak peek into the first week’s content and
then decide to not take the course at all. The reasons for
this behavior must be investigated in future user studies.
This observation raises the question, should completion
rates for (massive open) online courses be calculated
against the total number of participants eligible for certification
– Participation (term) in table II, should the rate
be the quotient of the certificates issued and the actually
active participants. The motivation for MOOC providers
to state high enrollment numbers is an obvious sales argument.
Nevertheless: when it comes to refunding (e.g.
through paid certificates), the enrollment numbers become
obsolete.
Table 3 shows a comparison of the two outlined options
for completion rates as it concerns the so far concluded
courses on openHPI. The column Completion (term) takes
the rate as quotient of the number of certificates and the
eligible participants, while Completion (active) only takes
the active participants into consideration.
Table 3: Completion Rates
Course
Certificates
Completion
(term)
Completion
(active)
In-Memory Data Management 2,137 16.28% 52,53%
Internetworking mit TCP/IP 1,635 16.53% 55.88%
Semantic Web Technologies 784 13.15% 32.13%
Datenmanagment mit SQL 1,641 23.55% 53.94%
Web-Technologien 1,727 23.50% 54.46%
Total / Average 7,924 18.30% 51.11%
Even though the traditionally calculated completion rates
of openHPI courses between 13% and 24% compare
quite well against an average completion rate for MOOCs
of less than 10% (according to Jordan, 2013), the expressiveness
of theses numbers must be considered relatively
low as a metric for the quality of the course concept and
content. This is because the set of participants serving as
basis for the calculation of these rates also incorporates
the group of users who never really got in touch with the
learning material – the above mentioned “sneak-peekers”
and those who enroll and never come back. Udacity is taking
a leap forward here following another approach: students
can preview nearly any course content (including
practical programming exercises, e.g. in the course “Introduction
to Computer Science”6) without having to join the
course – openHPI, Coursera and others follow different
rules, i.e. users can only see general course information
and introductory material before actually enrolling in a
course.
5
Actually, these participants enrolled prior to
the release of the final exam; since openHPI
certificates are issued when a participant
reaches at least 50% of the overall score and
the final exam is worth exactly this 50%, they
could still qualify for certification.
Another point for further discussion and investigation is
the “arbitrary” definition of active users used in the paper
at hand. Definitions of activity must not be based on submission
of graded, mandatory assignments or contributions
to discussions since there can also be active users
who neither intend to go for certification nor post in the
forum, but are of a passive user type (i.e. belong to levels
0 or 1 in Fischer’s (2011) “ecologies of participation,” also
see Grünewald, 2013). Future work must analyze usage
patterns of different participant groups more precisely
and try to identify attributes and thresholds to distinguish
active users, lurkers, and users that do not actually take
part in the course.
Participants’ Engagement during
Courses
We also observed the participants’ engagements throughout
the seven course weeks – taking the number of submitted
homework assignments as measured value. Fig. 2
presents the submission numbers for all mandatory assignments
(weekly homework and final examination) for
Research Track |104