In examining the usefulness of open, online resources for learning, we have to look not only at the resource but also relationships between resources, users, and the ways resources were used (Engestron, 2007: Littlejohn, Falconer & McGill, 2008; ).
Use is critical because online resources do not encapsulate the scientific and instrumental knowledge needed to support learning and development (Francis, 2013; Falconer & Littlejohn, 2007). Scientific knowledge is (generally) explicit and codified while instrumental knowledge involves solving specialist, practical problems (Boshuizen & van de Wiel, 2013). Learning scientific and instrumental knowledge requires open interactions with other people (teachers, experts, peers) (Engeström, 1999). Paavola & Hakkarainen’s (2005) work illustrates learning interactions around online resources to gain scientific and instrumental expertise through collaborative knowledge construction. In these examples open, online resources serve as a focal point for the co-ordination of learning (either by a teacher or expert, or by learners themselves), rather than as ‘learning materials’ in the conventional sense.
As learners gain expertise there is a qualitative change in the way they use resources to realise activities, moving from rule-based actions to fluid, self-directed activities (Dreyfus and Dreyfus, 2000). Therefore expertise is illustrated by the ways an individual uses the resources and how they relate to other people in their environment (Holland et al, 1998, p121; Edwards, 2010a, p25).
While working on a new book exploring the reuse of open, online resources for learning (Littlejohn & Pegler, 2014) I’ve been reflecting upon the different types of digital resources available for learning in networks, revisiting the idea of use.
Resources serve different purposes depending on how they are used, therefore resources could be characterised by use. Use can be viewed broadly at three levels: knowledge, experiential and analytic resources:
The education domain has pioneered the open release of knowledge resources often created by teachers or experts for learners. With these resources, users are largely are unknown to the resource creators, since users can be anyone, anywhere, using the resource in any context; students registered for a course, professionals learning for work or lifelong learners. Knowledge resources are typified by (though not limited to) Open Educational Resources (OER), Open CourseWare (OCW) or Open Courses, including Massive Open Online Courses (MOOCs). Thee resources are available in a range of media, from textual materials (articles, e-textbooks, blogs, micro-blogs) to images, videos, audio and aggregations of these, generally sourced via search engines. Resources were created and released by universities, notably MIT (USA) and the Open University (UK), though many other universities, companies, charities and professional bodies are now producing and releasing resources, often under Creative Commons licences (McGill et al, 2013; Falconer et al, 2013). Materials are purposefully created to support learning, however open learning resources can also include dynamic resources that form and morph in a less predictable way than traditional educational resources. Knowledge resources can be created or co-created and adapted by learners themselves. Beyond this are other types of open, online information resources that are routinely created and shared with others (or contributed to the collective) in ways that enable their reuse. For example the creation and development of a base of common or shared knowledge for professional learning or learning for work (Johnson et al, 1999). Professionals create codified resources as an output of work activity. Some resources have restricted access (emails, classified reports, and so on) but other resources are open, including reports, blogs, microblogs (for example hosted on Twitter or Yammer), images (for example Flickr, Slideshare), videos (for example YouTube), audio files and bookmarks (for example Delicious).
Experiential resources are widely used for professional and lifelong learning. These resources support the development of expertise that underpins practice. Experiential resources range from simulations in serious games or virtual worlds to digitally mediated interactions with people with relevant expertise. Interactions around these sorts of resources are sometimes qualitatively different than with knowledge resources. For example the linux community – a community of people distributed around the world who share programming expertise by working collaboratively on the linux kernel computer code – use code as an experiential resource (Moon & Sproull, 2002). The openness of the kernel and fragments of code serve provide resources supported by community forums and others as learning resources for people who want to extend their programming expertise.
Analytic resources support learners in planning and instantiate their learning. As learners interact online, learning choices and behaviours can be captured, analysed and released as analytics data to allow individuals to plan and manage their learning. Systems and tools based on analytics provide an organising focus for learning (Littlejohn, Milligan and Margaryan, 2011). Each learner can manage his/her interaction with the people and resources that are important for learning, developing a personal view of learning which, in turn, relates to the learning of others. The significance of this sort of open system is that it brings together the individual with the collective in ways that are impossible with conventional closed (restricted access) learning resources. These data resources include user identity data generated through direct entry by the user, cross-referencing of identity information from different sites or from user behaviour. These resources can be used to support learners in expanding their relational expertise – or their capacity to understand who or what to connect to accelerate their learning – capitalizing on the collective expertise of people and knowledge resources within the network (Littlejohn, Milligan and Margaryan, 2012). Though relational expertise extends beyond the rational decision-making afforded through systems based on Artificial Intelligence and involves human interactions with the environment medicated by expertise (Edwards, 2010, p21).
Learners use and reuse open resources in and across these diverse contexts – education, work and lifelong learning- which provide the framework for exploration of reusing open learning resources in the ‘Reusing Open Resources’ published in May 2014 (Littlejohn & Pegler, 2014).
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