…learning in which information and communications technology (ICT) is used to promote connections: between one learner and other learners, between learners and tutors; between a learning community and its learning resources. (Goodyear et al. 2004, p. 1)
The key term in this definition is connections and the emphasis is on the technology-mediated interactions between people and between people and resources. Connections include interactions between people and material technologies and resources. However, interactions with technologies and resources are not sufficient in themselves to constitute networked learning. Networked learning requires some element of human-human interaction even when mediated through digital networks.
There are differences of emphasis about the nature of the field and how networked learning should be defined (see, e.g., Dirckinck-Holmfeld et al. 2012, Chap 17); however the definition has provided a consistent point of reference for an international conference and a book series. The papers from the international Networked Learning Conference are freely available in an online archive from the first conference held in 1998.
Synonyms for Networked Learning and Related Areas
An alternative term that has greater currency in North America has been learning networks (Hiltz et al. 2007). Originating in the work by Hiltz and Turoff in the late 1970s, learning networks and asynchronous learning networks have developed into an area that overlaps with networked learning but has its own distinct approach. Learning networks and networked learning are both terms that have informed the development of the idea of connectivism and cMOOCs in the work of Siemens and Downes from Canada (Jones 2015, p. 65). A useful distinction has been drawn by Carvalho and Goodyear (2014) who use the term learning networks to identify specific instances of networked learning. These can be investigated and analyzed to inform future designs with the aim of generating a repertoire of properly understood examples illustrating the complex processes and assemblages in which networked learning takes place. This distinction suggests that networked learning can be used as the term describing the general phenomenon and learning networks to describe with greater precision the various ways that networked learning is enacted.
Connected learning is another term that covers a similar area to networked learning, but it is largely focused on young people of school age (Jones 2015, p. 7). In contrast networked learning has traditionally focused on adult learning, higher education, and professional or lifelong learning. The difference between connected learning in compulsory school age settings, even where these involve informal learning, is important. Networked learning has generally been applied to adult learners who are learning in formal settings that are generally voluntary and not as prescribed as school age activities. Adult learners can also be considered as being different in character to those who are school aged. In terms of informal activities, school-aged learners are often more free to engage in a range of voluntary activities than adult professional learners who are more often constrained by their primary work activities.
A distinctive feature of networked learning is its clear research focus and a willingness to draw on a wide range of disciplines for theoretical inspiration. Networked learning can easily be confused with other approaches, but networked learning is not simply another term that equates with e-learning or technology-enhanced learning (TEL). For networked learning the connectivity enabled by digital networks and the potential for interactions between people, and between people and their resources, is absolutely central. Learning technologies are a means to this end rather than the primary focus of research. Although networked learning does not subscribe to one particular learning theory or pedagogy, networked learning is an approach underpinned by a set of pedagogical values, whereas TEL or e-learning is a broader area with multiple and heterogeneous theoretical views and pedagogical practices. Furthermore networked learning is not restricted by the normative position suggested by terms such as “enhancement.”
Networked learning has a close relationship with computer-supported collaborative learning (CSCL), in that both fields have a keen interest in collaborative orchestrations of learning. However, CSCL tends to focus on smaller groups, including dyads, whereas networked learning extends to medium- to large-scale groupings. Also CSCL has a strong connection with formal learning in education, whereas networked learning has been picked up in a wider context, for example, lifelong learning, professional development, and organizational learning.
Social learning and communities of practice are other areas close to networked learning. Although communities and networks are often thought of as two different types of social structure, networked learning thinks of community and network as two aspects of social structures in which learning can take place (Wenger et al. 2011). Network refers to the set of relationships (see below) such as information flows, helpful linkages, joint problem solving, and knowledge creation. Community is a special case of networks and refers to the development of a shared identity around a topic or set of challenges. It represents a collective intention – however tacit and distributed – to steward a domain of knowledge and to sustain learning about it. Networked learning differs from other related fields because of its research focus on networks, critical pedagogy, and learning.
The mathematical approach to network analysis can provide a number of tools for the analysis and description of large networks and flows of data, such as those generated by large online and distance courses and massive open online courses (MOOCs).
Social networks can be described in various historical periods and differing social contexts, but networked learning is concerned with learning in relation to the digital and networked technologies developed in the late twentieth and early twenty-first centuries. Networked learning draws on several different theories and intellectual traditions concerned with networks including social network analysis (SNA). SNA builds on the principles of analysis from network or graph theory and on sociology and communications theory. SNA explores how relationships between people and organized groups of people form networks and how these networks affect access to opportunities such as jobs, knowledge, and information. Haythornthwaite and De Laat (2011) identify the basic building blocks of SNA as actors, ties, relations, and networks. An actor in these networks can be organized groups and they are not necessarily individual people or even people at all. Actors in SNA can sometimes be computer agents and relationships can be mediated forms of human-human interaction or hybrid human-machine configurations. Currently there is no settled position in networked learning on this question. Haythornthwaite and De Laat (2011) are cautious about the inclusion of inanimate and hybrid actors because currently there has been little work that has applied SNA to include objects or to develop interpretations of the social aspects of networks to include hybrid actors and/or inanimate objects. To settle this question further, analysis drawing on actor-network theory and related sociomaterial and post-human approaches will be needed to examine the role of these kinds of actors in SNA (Jones 2015).
Cooperation and collaboration in the learning process
Working in groups and in communities
Discussion and dialogue
Self-determination in the learning process
Difference and its place as a central learning process
Trust and relationships, weak and strong ties
Reflexivity and investment of self in the networked learning processes
The role technology plays in connecting and mediating
This view of learning is in sharp contrast to the tradition of instructional design and various forms of learning design which assume that learning is open to more direct interventions. Although learning itself cannot be designed, existing learning networks can be analyzed so that they can inform the future designs of those elements (tasks, spaces, tools, and organizations) open to design activity (Carvalho and Goodyear 2014).
Issues and Trends
Initially networked learning studies were preoccupied with various forms of open distance online learning in higher education, e.g., in courses where students would sit at home and connect and discuss resources with tutors and other students mediated by conferencing systems or virtual learning environments (Hiltz et al. 2007). This was how and when networked learning technologies entered higher education (Steeples and Jones 2002; Goodyear et al. 2004). It is now clear that networked technologies are much more than the desktop computers we use to connect to virtual classrooms. Education today is saturated with omnipresent and pervasive access to digital networked technologies, via various devices (phones, tablets, etc.) and in various locations (at home, on public transport, on campus, or in the lecture hall). Contemporary networked learning actively crosses the boundaries of traditional settings to understand how mobile and ubiquitous technologies can allow learners to couple learning and everyday lived contexts and how participants though colocated (face to face) can simultaneously collaborate online.
A major issue for networked learning is the relationship between technologies understood as material entities and the social life and learning related to these material forms. Technology is generally understood in networked learning as a complex sociomaterial entity involving a history of design, a social pattern of adoption, and a complex hybridity of humans and machines (including code and software) in technologies, such as the Internet, the Web, and a range of local networks and infrastructures such as a learning management system (LMS). The idea of affordance has proved useful to understand these socio-technical relationships between technologies and those that make use of them, but this term is slippery and there are continuing debates about how best to use it, and indeed whether to use the idea of affordance at all (Jones 2015). Because technologies are designed with purposes in mind, they embed properties and features that are intended to be taken up in particular kinds of use. Some argue that technologies “possess” affordances, but networked learning theorists argue that the properties of technologies are not determinant of the uses made of them, even though they act as limits to them. Thus, affordances can be thought of as relational properties that emerge from the interactions between different elements, and they are not essential characteristics of any object, technology, artifact, or system.
Networked learning is an emerging perspective in the area of professional development that aims to understand social learning processes by asking how people develop and maintain a “web” of social relations used for their learning and development (Goodyear et al. 2004; Haythornthwaite and De Laat 2011; Steeples and Jones 2002). The reasons for this development are the increasing complexity of work and the constant change of knowledge and procedures that stimulate professionals to work together to actively cocreate and innovate their domain and practice. This is related to the take-up of social (business) media which allows professionals to connect and interact with peers inside and outside their organizations to learn, to solve work-related problems, and to innovate. A networked learning approach helps organizations and professionals to understand knowledge management from a learning perspective and provides ways in which professionals can be supported.
A developing area of research in networked learning concerns ways that digital world is different because it relies on code, the lines of instructions, and algorithms that combine and generate complex digital functions which produce real and tangible effects. Code is the “governing power” of digital networks because it makes things happen and shapes future actions through self-governing feedback loops which give code a co-constituting and shaping role in networked learning (Jones 2015, p. 141). Networked learning research is interested in tracing activity within educational settings and it is interested in these at various levels of scale. Interactions within small groups, modules, and courses have previously been studied using a number of different methods. The newer kinds of data, often summarized as “big data,” are being subject to various kinds of analytics, including learner analytics or learning analytics. This means that there are new opportunities for insights into levels of activity of significantly larger groups, in institutions, large organizations, and dispersed social networks. The use of this kind of data will require careful development by ethically informed researchers who will need to explore the detail of data collection and data manipulation to ensure that the data they use is fit for research purposes and does not harm participants. This also requires close scrutiny from a critical perspective and a continuous questioning of: Who will benefit? Who will such analytics empower? And who – or which understandings of learning – might be marginalized? These are the kinds of questions that have been asked within networked learning in the past – and will be in the years to come.
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