Innovating Pedagogy 2013 Report from Open University
The “Innovating Pedagogy” series of reports from Open University explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation.
This second report update proposes ten innovations that are already in currency but have not yet had a profound influence on education.
In the past year, massive open online courses (MOOCs) have attracted interest from universities and from venture capital investors. MOOC platforms have been announced from Australia to the UK, but the focus is still currently on North America. The US-based providers Coursera, Udacity and edX are exploring business models involving paid-for assessment, the award of recognised credit, and recruitment of students to campus courses. Typically, around 20,000 learners register for a MOOC, with 5-10 percent reaching the end point. In terms of pedagogy, the currently dominant approach is a transmission model involving video lectures, recommended readings and staged assessment. MOOCs are an evolving and expanding area with new developments likely to offer greater variety of courses and more innovative social learning pedagogies. They also offer the chance to run experiments that compare teaching methods.
To accredit learning: Badging offers a flexible mechanism for recognising achievements as steps towards more substantial goals. Badging can also provide an informal alternative to accreditation. During 2012, the initial infrastructure and profile for badges became established. In 2013, there are encouraging signs that the tools and infrastructure are improving, with implementations appearing for mainstream learning environments. Educators are increasing their experience of using badging to help courses run successfully online and to motivate learners. Badging implementation requires further development, for example to offer more flexible ways to provide evidence. Lack of structures that can combine badges into a common accreditation framework currently limits their use. Greater awareness and presence of badging through social networks is still required, but the core technology of a ‘badge backpack’ has already been refined.
Learning analytics involve the collection, analysis and reporting of large datasets relating to learners and their contexts. Current developments are focused on three areas: understanding the scope and uses of learning analytics; integrating analytics into existing courses; and expansion of learning analytics to new areas, particularly MOOCs. A central challenge is to develop analytics that are driven by key questions, rather than just querying data collected from online systems. The relation of learning design to learning analytics is also being considered, so that new teaching methods and curricula are informed by analysis of previous experience. Methods of learning analytics not only examine past interactions but also support future outcomes for students and educators. Other key issues include secure data storage, appropriate levels of access, and providing the necessary infrastructure for storing and querying large data sets.
Seamless learning (connecting learning experiences across the contexts of location, time, device and social setting) is moving from research to mainstream adoption. Mobile technologies enable learners of all ages to operate across contexts, for example schools allowing students to bring their own devices. Pedagogy is emerging, based on learners starting an investigation in class, then collecting data at home or outdoors, constructing new knowledge with assistance from the software, and sharing findings in the classroom. There is also a broader notion of seamless learning arising from connected experience. Our activities online are increasingly matched to our interests: search pages order responses based on previous queries; websites recommend content related to our past viewing. The benefits are that personally relevant information may be ready to hand, but the danger is that we may come to believe that our views, preferences and connections are not just the most relevant, but all there is.
Crowd learning describes the process of learning from the expertise and opinions of others, shared through online social spaces, websites, and activities. Such learning is often informal and spontaneous, and may not be recognised by the participants as a learning activity. In this model virtually anybody can be a teacher or source of knowledge, learning occurs flexibly and sporadically, can be driven by chance or specific goals, and always has direct contextual relevance to the learner. It places responsibility on individual learners to find a path through sources of knowledge and to manage the objectives of their learning. Crowd learning encourages people to be active in setting personal objectives, seeking resources, and recording achievements. It can also develop the skills needed for lifelong learning, such as self-motivation and reflection on performance. The challenge is to provide learners with ways to manage their learning and offer valuable contributions to others.
Digital scholarship refers to those changes in scholarly practice made possible by digital and networked technologies: open access publishing, open science, digital humanities, the use of social media by academics, digital and citizen science. In the information and library sciences, a focus on digital curation reflects an interest in the ability of scholars to assemble, search across and publish annotated collections of interconnected multimedia artefacts. Digital scholarship demonstrates many elements of open and networked forms of scholarship. Open-access publishing and open peer review enable sharing of knowledge. Open publishing of research datasets supports reproducible research. Engagement in open educational practices has the potential to support moves towards a more free and collegiate teaching practice.
Sensors built into mobile devices, such as smartphones and tablets, can determine a user’s location and provide, or trigger, context-aware educational resources in the surrounding environment. These can enable both formal and informal learning within physical ‘real-world’ settings.They may also enhance and frame the subject matter being studied. For example, learning about an historical event could be situated in the place where that event occurred, giving a rich sensory experience of being in the scene. Fieldwork activities have long encompassed ‘geo-learning’ as away of providing information that exploits the surroundings and landscape. Geo-learningis not new, however technologies sensitive to location, or embedded in objects near the learner, now allow greater mixing of digital information with the physical world, to produce‘blended spaces’. We need to consider carefully how we employ these opportunities for learning. Current theories are somewhat limited, but several approaches, including research into learning spaces, provide ways to model the richness of these environments and our interactions within them.
Learning from gaming
There is increasing interest in the connections between games and education. When implemented as ‘edutainment’ or ‘gamification’ of learning,teaching practices can gain superficial elements of entertainment and reward. This may encourage learners to continue, however misses the power of digital games for engagement, reflection and self-regulation. New approaches of ‘intrinsic integration’are linking the motivational elements of games with specific learning activities and outcomes, so that the game-play is both engaging and educationally effective. Game designers can achieve this by developing games with elements of challenge, personal control, fantasy, and curiosity that match the pedagogy. They can manipulate aspects of ‘flow’ (a player’s feeling of absorption in the game) and strategy to produce a productive cycle of engagement and reflection. The shared endeavours, goals and practices in games also help build affinity groups gathering learners into productive and self-organising communities.
Maker culture encourages informal, shared social learning focused on the construction of artefacts ranging from robots and 3D-printed models to clothing and more traditional handicrafts. Maker culture emphasises experimentation, innovation, and the testing of theory through practical, self directed tasks. It is characterised by playful learning and encourages both the acceptance of risk taking (learning by making mistakes) and rapid iterative development. Feedback is provided through immediate testing, personal reflection, and peer validation. Learning is supported via informal mentoring and progression through a community of practice. Its popularity has increased due to the recent proliferation of affordable computing hardware and 3D printers, and available opensource software. Critics argue it is simply a rebranding of traditional hobby pursuits. Proponents contend that recent evolutions in networking technologies and hardware have enabled wider dissemination and sharing of ideas for maker learning, underpinned by a powerful pedagogy that emphasises learning through social making.
Citizen inquiry refers to mass participation of members of the public in structured investigations. It fuses the creative knowledge building of inquiry learning with the mass collaborative participation exemplified by citizen science, changing the consumer relationship that most people have with research to one of active engagement. The concept is that people who are not research professionals engage in collaborative, inquiry based projects. For each investigation, they gather evidence of similar successful projects, create a plan of action, carry out a controlled intervention if appropriate, collect data using desktop and mobile technologies as research tools, and validate and share findings. Citizen inquiry not only engages people in personally meaningful inquiry, it can also offer the potential to examine complex dynamic problems, such as mapping the effects of climate change, by means of thousands of people collecting and sharing local data.
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