Multimodal Data for Learning
I am on the review board for this special call for papers on "Multimodal Data for Learning" for the Journal of Computer Assisted Learning (JCAL). The special issue deals with new data sources coming from the Internet of Things (IoT), wearables, eye-trackers and other camera systems, self-programmable microcomputers such as Raspberry Pi and Arduino. How can these multimodal datasets that combine traditional learning data with different data from physical activity, physiological responses or contextual information be exploited for learning?
On these pages you find information about my personal and professional background as well as some features about my interests in technology-enhanced learning, knowledge creation, knowledge transfer, and networked universities.
Learning technology has come a long way, and provides organisations, learners, and teachers with enormous opportunities to innovate not only their technical environment, but also the teaching and learning methodologies as well as their business processes. Most of all, the introduction of new media technologies leads to reflections about inherited traditional systems versus new approaches. My work contributes to these reflections and pursues not only innovation but also the effects that this innovation has on education, learning, and people.
This is a fast moving area and research focus changes quickly and often unexpectedly. My publications page contains a list of works in the field over the years. To a great extent they too reflect the changing nature of education.
My views on technology-enhanced learning
I am a passionate believer in the opportunities that technology has to offer to the knowledge society, both in terms of enhancement of learning and in reaching out to new learners. In remote and rural communities it is often the only way for people to access higher education. However, I am also of the opinion that technology alone does not produce new knowledge or learning and that new developments need to have a pedagogic and learner-centred approach.
Experience in commerce and education has shown that online solutions are at their best when built upon a traditional well-established structure. The pedagogic concept of Blended Learning is increasingly supported by universities and governments who realise that it provides a more sustainable approach than purely online offerings. This goes some way towards recognising that we cannot ignore pedagogic concepts that have been successful for decades before the internet arrived and still are.
Areas of interest
Technology enhanced learning has made giant leaps forward over the past few years. In my work, I try to keep up-to-date with latest developments and newest technologies. My current research interests focus especially on Learning and Knowledge Analytics, Language Technologies for learning support, Learning Networks, and Mobile Learning, but I also have a keen interest in other topics, including open education, game mechanics, or the most recent debate about connectivism.
Read more about my views on e-learning developments.
Learning has become a lot more social. Whereas previously the focus has been largely on knowledge transfer, more recent pedagogic trends have emerged that recognise that this is not the only way to learn. Human interaction is a vital component in the process of acquiring new skills or knowledge, or for creative processes. Pedagogic theories like socio-constructivism or connectivsm explore and try to explain this and form the basis for a lot of our technology driven teaching and learning approaches.
Especially in the area of professional learning humans almost always act within communities, that is with people or experts with whom we discuss and share our knowledge. These communities of practice (CoP) or communities of interest (fanclubs etc.) are organised in online networks. For the purpose of learning, they are called learning networks. Learning networks show the right flexibility to support ad-hoc learning and other informal methods of knowledge building.
Learning networks, like other networks, are built upon links and connections, but, in learning networks, connections in turn depend largely on two human characteristics: trust and passion. While there is already a good stock of research looking into learning networks, these areas are still mainly unexplored. It is also still unclear what makes such a network successful. Mostly, success is understood in terms of scale, i.e. size of membership or volume of content, but this may actually be not the decisive criteria for a successful learning network. More research into these questions is required.
Being internet-based, learning networks utilise online social platforms, or, sometimes, purpose-built platforms. Twitter, Facebook and other social platforms have entered education and are increasingly used in courses. Because the internet is full of useful tools and technologies, more personal combinations of these are now possible that were not available before. This increasingly open way of providing tools for learning leads away from the traditional provision of tools and platforms to a personal learning enviroment that is centred around the learner, not around the institution.