Receive the latest innovations in online learning directly to your inbox! Subscribe Now

Virtually Inspired Blog

With a focus to inspire innovation in online learning, our blogs feature multiple authors including our founders, Dr. Susan Aldridge and Marci Powell, along with a network of guest bloggers from across the international academic world. This network of colleagues is comprised of education futurists, experts, visionaries, practitioners, and researchers with a passion for the world of online and distance learning. Together this group shares blogs on a variety of topics surrounding the next generation learning environments.

Inverse Blended Learning

How to Deal with MOOCs More Successfully

By guest bloggers: Martin Ebner & Sandra Schön

In this blogpost, two European academic researchers share their findings regarding a didactical concept for MOOCs and its positive effects on dropout rates.


MOOCs – We Love to Work With

We guess that all innovative educators especially in the field of educational technology love to work with MOOCs. We simply get the possibility to teach a broad audience and are working with learners really interested in the stuff. In recent years, the number of those courses have increased while impressive educational institutions report successful experiences.

Besides the success stories and, sometimes enthusiastic, medial echo on MOOCs, the high number of learners who have not finished their participation within a MOOC was always seen as a challenge. The so-called dropout rate is calculated as the proportion of registered learners who finally completed the course and the sum of registered participants of one MOOC. For example, in the famous MOOC of Sebastian Thrun, of more than 160.000 registrations on Artificial Intelligence only 23,000 completed, which means a dropout rate of approximately 93 percent.

Katy Jordan (2013) visualized the MOOC completion rates from 50 investigated MOOCs. She reported that the investigated courses did not have a completion rate of more than 10 percent. On average she pointed out that only 7.5 percent of registered users finish. Similarly, Meyer (2012) found that the dropout rate of MOOCs offered by the famous MOOC platforms of Stanford, MIT or Berkley stays between 80 and 95 percent. There is even more literature, e.g. (Rivard, 2013) (Bruff, 2013) (Khalil & Ebner, 2014) reporting on high dropout rates. Of course, there are also hints on how the dropout rate can be reduced.  For example, by increasing the interaction between learners and teachers or offering more interactive components during the course (Khalil & Ebner, 2013).

But if we take a closer look at the now common MOOC design of a so-called “xMOOC”, it becomes rather obvious why there might be a problem of dropping out.  A typical xMOOC is rather presentation-oriented; the main components are different kind of videos together with a self-assessment possibility and the idea of self-regulated learning. Personal assistance or any other kind of cooperation is not a key component due to financial costs (Lackner et al., 2014).

Inverse Blended Learning

After studying the literature and being faced with doing MOOCs for a broad mass of people, especially those who aren’t not well-founded in digital literacy, a new didactical approach has been invented. Following the idea of blended learning – where face-to-face education is interrupted with online elements – the idea was to bring the pure online courses, the MOOCs, a little bit back to real-life situations. Given that recognized how hard self-regulated learning was for novice learners, we needed a way to give them a possibility for exchange with others.

Figure 1: Inverse Blended Learning

Fig. 1 shows the difference between blended learning and the new approach, named inverse blended learning. Rather than a typical face-to-face education approach which is enhanced with online elements, the didactical approach of inverse blended learning is based directly on a pure online course that is enhanced by face-to-face elements. Those face-to-face elements can be very diverse and should support the social learning process amongst learners.

The most known examples of those social elements are regional learning groups, often founded by learners themselves. Those groups appear because learners want to discuss the content of the course with others, share their experiences or prefer to do the assessments together. Nevertheless, it is quite hard to find nearby participants within the MOOC-platforms because the discussion forums are confusing and there are no assisting tools (Bruff, 2013). Coursera, for example, founded what they call “learning hubs” where MOOC participants can be part of learning groups and will find Internet access as well. One of those places is at the New York Public Library (Kolowich, 2014). Similarly, the “IchMOOC” available for the German speaking area offered MOOCbars, which were located anywhere in Germany where additional synchronous live-streams of the course were watched together (Röthler & Creelman, 2016).


We have been taking the approach of Inverse Blended Learning for 4 years now, we can proudly report that we have reduced the dropout rate dramatically. Even more, we can state that learners who visit the face-to-face offerings on a regularly basis are more likely to complete the course with success. It is great to see, that the arrangement of those face-to-face elements differs arbitrarily; weekly meetings in a very informal setting (cafes, public places) as well as in formal settings (higher educational seminars) and even online (webinars). These settings enable learners to not only discuss content but to see to each other’s problems, needs, questions and to complete tasks.

Learning is a social process.  With the approach of Inverse Blended Learning we are able to help MOOCs to be more successful.

About the authors

Dr. Martin Ebner, TU Graz

Adjunct Prof. Dr. Martin Ebner is currently head of the Department Educational Technology at Graz University of Technology and is responsible for all university wide e-learning activities. He holds an Adjunct Prof. on media informatics (research area: educational technology) and works also at the Institute for Interactive Systems and Data Science as senior researcher. His research focuses strongly on seamless learning, learning analytics, open educational resources, and making and computer science for children. Martin has given a number of lectures in this area as well as workshops and keynotes at international conferences. For publications as well as further research activities, please visit his website:

Dr. Sandra Schön, Innovation Lab at Salzburg Research

Dr. Sandra Schön is a Senior Researcher and Project Manager within the Innovation Lab at Salzburg Research Forschungsgesellschaft (Salzburg, Austria). She studied educational science, psychology and computer science at the Ludwig-Maximilians University in Munich (M.A. 2000, PhD in educational research 2007). Since 2006 she works at Salzburg Research in (inter-)national projects as project manager as well as researcher. Sandra has already co-organized several online courses (MOOCs) as OER (open educational resources). The MOOC GOL14, a start for online learners had more than 3.000 participants and received the Austrian State Prizes for Adult Education 2015.  COER13, an OER MOOC, received the German OER Award 2015. Sandra also co-organized the first online course about “Making with children” in 2015 where more than 600 teacher and educators from German speaking countries participated. Sandra’s most recent work and research in innovative learning spaces and open education resources can be found at:

The basis for this blog is from original research:  Ebner, M., Schön, S. (2019) Inverse Blended Learning – a didactical concept for MOOCs and its positive effects on dropout-rates. In: The Impact of MOOCs on Distance Education in Malaysia and Beyond. Ally, M., Amin Embi, M., Norman, H. (eds.). Routledge. ISBN 9780367026615

Let’s sign you up!

Powered by Drexel University Online