openHPI: Evolution of a MOOC Platform from LMS to SOA
Michael Totschnig, Christian Willems and Christoph Meinel
Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
Keywords:
Massive Open Online Course, Learning Management System, Service Oriented Architecture.
Abstract:
This article presents a new platform for Massive Open Online Courses (MOOC), developed at the Hasso Plat-
tner Institute in Germany. After describing the evolution of the MOOC concept and the format, we explain how
we defined the requirements for the platform, how we evaluated different open source learning management
systems as candidate solutions, and how the actual platform was built. The results of two first courses deliv-
ered through the platform are presented and an outlook is given towards a planned redesign of the platform
based on a Service Oriented Software (SOA) approach.
1 MOOC FORMAT AND
HISTORY
The concept of Massive Open Online Courses
(MOOC) has been coined in 2008 in the context
of a course experiment conducted by Canadian ed-
ucational researchers Stephen Downes and George
Siemens, who opened a for credit course titled Con-
ncectivism and Connective Knowledge at the Univer-
sity of Manitoba, Canada to open registration. The
gist of the experiment consisted in encouraging learn-
ers to take the course content not as the end, but
as the beginning of an autonomous and active jour-
ney defined by the connections the learner creates be-
tween resources and with co-learners (McAuley et al.,
2010).
The same concept has recently been invested with
a considerably different meaning when applied to
University courses that are migrated from the setting
of a closed physical classroom with a limited audi-
ence to an open online environment with a massive
audience. MOOCs in this second sense have origi-
nated at Stanford and MIT and some of them attracted
more than 100,000 participants.
Most discussions about MOOCs distinguish be-
tween these two concepts and formats, often referring
to them as cMOOC and xMOOC (Siemens, 2012).
At the heart of this distinction lies the tension be-
tween two opposing forces that are acting on higher
education: On the one hand, higher education in-
creasingly leaves the confines of national boundaries,
and relates to supranational frameworks (e.g. the Eu-
ropoean Bologna process) and global markets. On
the other hand, pedagogical theories that conceive the
learning process as active and social instead of pas-
sive and individual no longer are the privilege of al-
ternative and marginal institutions or educators, but
are now the backbone of commonly accepted learning
designs like collaborative or problem-based learning.
MOOCs, both the c and x variants, can be clearly sit-
uated in both movements:
By offering a MOOC today, universities try to po-
sition themselves as global leaders of innovation,
and as educational institutions capable of deliver-
ing high-quality education on a global scale. And
in the same time invest in their attractiveness for
the most talented prospective candidates.
While a MOOC can be organized according to
an established model of instruction, where teach-
ers transmit a well-defined body of knowledge to
unknowing learners that prove their progress by
repeating back that same knowledge, it also of-
fers the opportunity of integrating collaboration
and exploration into the learning design. And
even if xMOOCs have been criticized for a lack
of pedagogical innovation, it can be hypothesized
that their massive success is due both to the effer-
vescent nature of their discussion forums and to
the learning tools available in many MOOC plat-
forms that allow creative exploration of the do-
main through virtual laboratories.
593
Totschnig M., Willems C. and Meinel C..
openHPI: Evolution of a MOOC Platform from LMS to SOA.
DOI: 10.5220/0004416905930598
In Proceedings of the 5th International Conference on Computer Supported Education (CSEDU-2013), pages 593-598
ISBN: 978-989-8565-53-2
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
2 openHPI’s COURSE FORMAT
AND REQUIREMENTS
openHPI is a platform for xMOOCs, hosted at the
Hasso Plattner Institute in Potsdam (HPI), Germany.
openHPI is the result of tele-TASK, a research and de-
velopment project conducted since 2004, which has
brought into existence an advanced lecture recording
system (Schillings and Meinel, 2002), and an online
portal
1
for the distribution of lecture videos. While
the tele-TASK portal has been augmented with so-
phisticated semantic web search capabilities (Sack
et al., 2009) and social web functionalities, it mainly
stayed focused on delivering lecture content to HPI’s
students allowing them to replay or to replace the
class lecture. In the advent of the MOOC format, we
see the opportunity to open up the pedagogical qual-
ity and domain expertise formerly reserved to our stu-
dents to a broader audience.
While the inspiration for our project stemmed
from the success of the Stanford courses about artifi-
cial intelligence
2
and databases
3
and the MIT course
on Circuits & Electronics
4
, we set our ambition to de-
fine a course format following a unique educational
scenario: The subject domain is split up into six
weekly units. For each week, video lectures, reading
materials, and quizzes are produced and presented in
a learning sequence. Discussion forums are set up for
each week, and actively moderated by the teaching
team. Learning progress is assessed through self-tests
that can be taken an indefinite number of times, and
homework, where points are granted and collected for
the final score, required for obtaining the certificate.
For the technical implementation of the platform,
it was clear that we did not want to rely on an ex-
ternal SAAS hosting solution, but create a platform
we could freely adapt and evolve. Teaching at HPI
focuses on IT-Systems Engineering, and the ambi-
tious project of creating a platform for thousands of
learners constitutes a very interesting challenge for
our own teaching and research. Critical success fac-
tors for the fulfilment of this ambition were identified
with respect to the delivery of content, the learning
process, and community building.
2.1 Learning Content
The teaching team should be empowered to concen-
trate on the quality of the content by being provided
1
http://www.tele-task.de/
2
https://www.ai-class.com/
3
http://www.db-class.org/
4
https://6002x.mitx.mit.edu/
intuitive and powerful tools for content editing and
structuring.
The presentation of the learning content should
suggest a meaningful path to novice learners while
giving advanced learners the freedom to jump to top-
ics most relevant to them.
xMOOCs draw on the distinctive engagement
qualities of video lectures, chunked into small-sized
segments. The platform must allow to embed video
content, and to enrich it with textual explanation.
openHPI uses videos from the tele-TASK portal,
where lecture video recordings already exist in form
of chunk podcasts and additional metadata extracted
from the videos.
Learning content needs to be presented in its hy-
pertextual structure, in order to allow learners to grasp
more than a linear sequence of content, i.e. the rich
connections that exist between knowledge inside and
across learning domains.
2.2 Learning Process
The learning environment must support the learning
process by allowing learners to test new competences
and by confronting them with graphical representa-
tions of their progress. Assessment tools need to be
user-friendly and interactive in a way to engage and
motivate learners. The synthetic representation of
learning progress must be easily accessible from any
part of the platform.
Learners should be able to annotate content with
personal notes only available to them and with shared
notes and comments that trigger reactions from the
teaching team and discussions in the learning com-
munity.
Learners should also be allowed to connect the
learning experience with their own tools and devices,
e.g offline consumption of lecture videos, or integra-
tion of course schedules with personal productivity
environments.
2.3 Learning Community
The distinguishing feature of the MOOC format is its
social event character: In the past, universities have
made course materials available on institutional web-
sites, and eventually provided feedback forms or dis-
cussion possibilities, for example MIT’s openCourse-
Ware project (Lerman et al., 2008). MOOCs take
place during a given time period, and hence concen-
trate the otherwise dispersed participation into a co-
herent site of collective learning. Discussion forums
should allow the teaching team to trigger participa-
tions and learners to question the content.
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Many learners are less comfortable when taking
part anonymously in large groups and prefer the in-
timacy of small groups, eventually defined by simi-
lar characteristics like age, location, or interests. The
platform should allow learners to find like-minded
learners, and to define protected spaces for groups to
organize a collaborative learning experience.
The platform must not lock the user into its own
confines, but allow users to connect their learning ex-
perience to their social networks.
2.4 Quality Attributes
These functional requirements are mainly compatible
with what many learning management systems, pro-
prietary or open source, provide. But while weight-
ing quality attributes (Bass et al., 2005), like stability,
scalability, usability, look & feel, extensibility, main-
tainability, security and performance, important ques-
tions arose:
On the one hand with respect to performance:
Learning management systems have been conceived
for the context of schools or universities where class
sizes range from tens to at the most hundreds of stu-
dents. Delivering a MOOC to thousands of possibly
concurrent users needs a robust technical infrastruc-
ture, and a scalable architecture.
On the other hand, we envisioned a platform
that would be easily extensible in order to imple-
ment teaching methods like game-based learning,
peer teaching and evaluation, and to connect to vir-
tual laboratories.
Last but not least, we set as our goal, to attract
learners through an attractive online experience that
does not fall behind their experience with modern
Web 2.0 platforms.
3 openHPI’s TECHNICAL
INFRASTRUCTURE
With the start of the openHPI project, the first task
was to build up an infrastructure that scales for a po-
tentially massive amount of users and is highly avail-
able, and to implement a suitable courseware for the
desired course format.
3.1 Courseware Implementation
The first general decision to be taken was between
designing and implementing an own solution based
on a common web framework and the adaption and
customization of an existing (open source) software
project. When collecting the requirements for a
courseware platform it became obvious that the devel-
opment of a courseware platform from scratch would
take at least 6 months of work for a full time devel-
oper team which is a huge (financial) effort for a first
course with experimental character. For this reason,
we decided to build openHPI on top of an existing
tool, that would allow to us to gain experience with
the construction, administration and delivery of mas-
sive open online courses, and that both technically
and legally allowed and facilitated experimentation
with and modification of the system.
While evaluating the landscape of existing plat-
forms for the delivery of online courses it became ap-
parent that several types of systems had each unique
advantages to offer:
Content management systems with respect to the
flexibility of the management and delivery of
learning content;
Collaborative platforms with respect to the com-
munication features;
Learning management systems with respect to the
support for quizzes and course design.
Finally the decision was made in favor of an open
source learning management system, where a num-
ber of potential candidates were evaluated. Among
these candidates, the projects Sakai CLE, Sakai OAE,
Canvas LMS, and Lernanta (actually a LMS frame-
work) were investigated and matched to the openHPI
requirements. The evaluation results are summarized
in Table 1.
Canvas was chosen because of its modern user
interface and the availability of crucial functional
components necessary for implementing openHPI’s
course design, mainly the sophisticated quiz engine
for managing practice exercises, assignments and ex-
ams, the discussion forum and the user-friendly in-
terface for creating and presenting the course module
structure.
Nevertheless, it was desired that the platform did
not look or behave like an actual LMS, since LMS
offer users much more freedom than openHPI needs
for the provision of its courses. A developer team of
4 full time working students put 5 weeks of work into
the adaption and customization of the Canvas LMS,
which resulted in a massive change of the Web user
interface as seen by student users. The main changes
were:
complete rebrush of UI and platform navigation;
additional content type for learning units: flexible
video player;
content navigation adopted to openHPI’s 6 week
course schedule;
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Table 1: Comparison of Open Source Learning Management Systems.
Canvas LMS Sakai CLE Sakai OAE Lernanta
Course Landing
Page
Customizable,
Rich Text Editor
Static landing page
from course infor-
mation
Content Reposi-
tory allows flexible
content
Tasks and Activity
Wall, not customiz-
able
Content Sequence Tool for course de-
sign (modules and
content blocks)
Simple syllabus
tool
Hierarchic organi-
zation of content
pages
Tasks can be re-
ordered
Learning Unit
Presentation
Generic blocks in-
side a module
As wiki pages See landing page A taks is defined
by only one content
block
Quiz Environ-
ment
Very flexible, so-
phisticated UI
Complex function-
ality, but sluggish
and overloaded UI
Only available
through integration
with Sakaii CLE
-
Discussion Forum Threaded discus-
sions, no voting
No voting No voting Participants can
post messages to
activity wall and
comments to tasks
Learning
Progress
Users can track vis-
ited units
Tracking of sub-
mitted tests
- -
Announcements Rich Text Editor Via external RSS
feed
- -
Maturity Closed-source ver-
sion used produc-
tively by schools
and universities
Used by major US
universities
Experimental In active develop-
ment, used produc-
tively P2PU
5
Scalability Ruby on Rails,
needs resources
Needs resources,
but works for more
than 100k users
No experience No experience
Useability, Look
& Feel
Modern UI Feels sluggish, old-
fashioned
Modern UI Clean and stylable
UI
Extendability API, vendor plug-
ins possible
API Relies on extensi-
ble framework
-
additional navigation bar for browsing the course
sequence;
integration of a helpdesk;
enhancement of the discussion forum (context-
specific discussions, tagging, search functional-
ity).
The adoption process kept on going during the
first two courses, where the development team gath-
ered user feedback and wishes from the community to
leverage the running system.
3.2 Hardware Platform
The difficulty in building the infrastructure mainly
was about estimating the resources needed and de-
pended on a) the application-dependent demand for
resources and b) the number of expected partici-
pants. Due to a strict schedule for the first course on
openHPI a temporary website for registration was set
up rapidly and went online about 4 weeks prior to the
launch of the actual courseware platform and 5 weeks
before the start of the first course.
The demand for openHPI’s offering turned out to
be quite overwhelming: one week after the launch
of the temporary registration website, the database
counted more than 10.000 unique visits and about
3.000 registrations. At the point of the turnover to the
actual course platform, there were more than 10.000
registered users, of which 9.000 students enrolled for
the first course, 30.000 unique visits and 110.000 page
impressions.
Although these numbers were a baseline for the
final user count and could help when estimating
the resources, openHPI was put on a flexible and
scalable infrastructure using a private cloud frame-
work (namely OpenNebula) for the operation of the
adopted Canvas LMS (see Figure 1).
The private cloud infrastructure allows flexible
scalability and the provision of more computing re-
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Figure 1: Overview of openHPI hardware architecture.
sources by simply adding additional physical hosts
to the cloud respectively shutting down servers for
reduced power consumption when the server load is
low
6
.
In the initial resource pool, two VM hosts were
provided, each with 64 cores and 64 GB RAM as well
as fast RAID 5 storage systems. Additional physical
servers provide the shared database and central ser-
vices like website monitoring. Incoming requests are
distributed by a loadbalancer appliance that also han-
dles the SSL sessions.
The video streaming was outsourced to the stream
hosting service Vimeo, which also scales with rising
demand and offers a reasonable cost model.
4 INSIGHTS FROM THE FIRST
COURSES
openHPI’s first two courses have met with substantial
interest from the respective target audience: 13,126
learners registered for the first course, from which
4,068 actively participated and 2,137 received the
graded certificate of successful completion. The sec-
ond course had 9891 registered learners, with 2726
active participants, and 1635 successful completions
with graded certificate. The students took about
100.000 (resp. 80.000 for the second course) self-test
attempts and submitted about 18.000 (14.000) solu-
tions of homework assignments. During the 6 weeks
of course runtime, the community generated about
1.600 forum postings in the first course and more than
3.000 postings in the second course.
For the second course, we observed, that Sun-
day and Monday were the peak days concerning page
6
For a general evaluation of cloud based services in ed-
ucation, see (Ivanov, 2011).
access: up to 6.000 unique visitors generated up
to 60.000 page impressions. This peak behaviour
was actually expectable, since Monday was the day
when the weekly homework submissions were due
and the course content for the next week was pub-
lished. Concerning the dimension of the available
hardware platform, it never came to shortage of re-
sources that would have led to increased response
time for users even though the implemented software
platform turned out to be greedy for computing re-
sources.
The basic insight after first experiences with the
implemented platform for openHPI is that traditional
learning management systems are actually not suit-
able for the operation of massive open online courses.
This insight was gained from two observations. The
first one is a different demand concerning scalability:
traditional universities usually offer a large number of
courses with a relatively low number of participants
in each course (hundreds of students). In opposite to
this, openHPI offers only very few courses at a time,
with thousands of students in a course. This led to
massive performance problems with the Canvas LMS
since many standard system operations were imple-
mented without focus on performance but on main-
tainability and simply did not scale with participant
numbers larger than about 1.000 students. Addition-
ally, several UI elements (i.e. where lists of users
were involved) became unusable.
The second aspect is, that LMS focus on man-
agement of courses, students, tests, learning material,
etc. while the focus of a platform for massive open
online courses should be on social activity respec-
tively the activity of the students in general. Learn-
ing Management Systems are designed for courses
run and tutored by teachers or teaching teams, while
the openHPI courses should empower the students to
peer teach each other. The restricted suitability of the
LMS-based implementation of the openHPI platform
manifested e.g. in the non-availability of certain fea-
tures for students, that have been available for teach-
ers. I.e. a teacher could link every content item be-
longing to the course within related discussion post-
ings, while students would have to manually copy &
paste the respective links or describe the item in ques-
tion in their own words. In general, LMS lack the
support for mixed roles between course providers and
course participants.
5 openHPI’s NEXT GENERATION
Based on the evaluation of above shortcomings, cur-
rently a new generation for the openHPI platform is
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597
planned. It will be based on a service-oriented archi-
tecture with the following design principles in mind:
The new system should integrate with state-of-
the-art backend services, if they are available as
open source solutions and can be trusted to be
both scalable and reliable. For example we evalu-
ate the incorporation of digital asset management
systems like Fedora.
Service-oriented system design similar to
component-based approaches strives at modu-
larity and re-usability. Well-defined interfaces
allow to separate the construction of the system
into development tasks that can be executed by
independent teams in parallel.
Making services consumable from different client
environments allows straightforward implementa-
tion of alternative client software, i.e. for mobile
devices (mobile websites and native apps for iOS,
Android and Windows 8).
By decoupling the consumption of services in spe-
cific contexts from the provision of these services,
both can evolve independently with respect to the
affordances of their respective environment, for
example the integration of new UI libraries, or the
adoption of new communication protocols.
A service-oriented architecture provides a sound
basis for the integration of the learning platform
into existing and future content production work-
flows. For example, we plan to integrate openHPI
with the tele-TASK portal, were tools for collab-
orative work with e-lectures, such as live script-
ing and temporal (social) annotations have already
been implemented.
Allow exposure of services to third-party tools
that provide value-added services to learners and
teachers (e.g. personal learning environments,
social networks or competence management (e-
portfolio) systems.
In the global competitive MOOC landscape, plat-
forms need to provide unique learning tools in or-
der to distinguish themselves from the competi-
tion. Hence it is important that the system can
connect with external learning facilities, such as
virtualized computing labs or simulation environ-
ments for hands-on training.
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