Katie first discussed several projects that she and her team have been involved in over the last years. Although the projects themselves were all interesting in their own right, it was the rubrics under which they were discussed that caught my attention. In terms of the classification that Knud Illeris makes in his book How we learn, they were all labels for specific kinds of learning environments:
- direct instruction environments, i.e. ordinary lecture theatre teaching enhanced with clickers or other 'learner catalysts'
- cooperative learning environments, enhanced by for instance websites or collaborative annotating suits
- environments for mastery learning, supported by for example interactive storyboards
- environments for (authentic) role play, such as case studies and Second Life
- environments for learning to think inductively, consisting of for instance mathematical simulation software and supported by dataverse software for publishing and sharing research data
- environments for exploratory learning, such as virtual and augmented reality environments, simulations, games
- environments for learning by doing, supported by facilities for peer tutoring, ePortfolios, etc.
- environments for inquiry learning, used to teach making inferences from data and working with the scientific method
Although not said so explicitly, the implicit message here is that technologies shape the environments in which we learn. The classification comes in handy to label what these technologies may achieve.
The second part of the talk was about the organisational aspects of putting together these environments, ensuring that faculty works with them and benefits of their use are disseminated. The problems encountered here sounded all very familiar, with the usual dilemmas. What is better, organise academic support at the level of faculties (colleges) or through a central service? Harvard has a central service, although it happens to spend most of its time with the science and arts people. What is better, to let faculty take the lead or should the initiative rest with the educational experts? In the former case innovations that are known from the literature, will be done anew, even innovations that have been shown not to work will be attempted again. In the second case, faculty will have no sense of ownership of their projects. Harvard has chosen for the former solution, prioritising sense of ownership over efficiency.
Finally, key to all that is done as a service to the Harvard academics is that it is seen as an opportunity to do research. This is perhaps most clear with the Harvard MOOC-experiments in edX. These have been set up as an opportunity to experiment on a large scale with direct, instruction-based, distance learning. Harvard has decades of experience with distance learning through its extension programme, so is unlikely to go at this with the naivety that some of the other xMOOCers do. Indeed, it is perhaps necessary to acknowledge that, though the dichotomy of xMOOCs and cMOOCs may still be valid, the xMOOC comes in two varieties: the for-profit ones, such as Udacity and Coursera, that are funded by venture capital; and the-not-for profit ones, that are funded through donations. edX exemplifies this second kind. Making the distinction is necessary when evaluating the value of these xMOOCs. I am anxious to learn how Harvard will evaluate their edX MOOC.