Group items tagged

The wide range of approaches and learning paths that are available to redesign curricula cause friction for educators and instructional designers who are required to deliver course materials in accordance with learning outcomes prescribed and mandated by educational institutions.

Connectivism stresses that two important skills that contribute to learning are the ability to seek out current information, and the ability to filter secondary and extraneous information.  Simply put, “The capacity to know is more critical than what is actually known” (Siemens, 2008, para. 6)

The developmental implications of Downes’ definitions of learning and knowledge are far-reaching.  If learning transpires via connections to nodes on the network, then it follows that the maximization of learning can best be achieved through identifying the properties of effective networks, which is precisely what Downes sets out to achieve in Learning Networks and Connective Knowledge.

Siemens (2006b) highlights other factors that may inform the development of a new learning theory, namely “how we teach, how we design curriculum, the spaces and structures of learning, and the manner in which we foster and direct critical and creative thought in our redesign of education” (p. 6).

roponents of connectivism are “exploring a model of learning that reflects the network-like structure evident in online interactions,” (p. 12) but is this enough to constitute its formulation as a new learning theory, and does connectivism have anything new to offer?

the way in which global networks and communities of interest are currently being formed through emerging technologies is encouraging young people, in particular, to develop new, creative, and different forms of communication and knowledge creation outside formal education

A paradigm shift, indeed, may be occurring in educational theory, and a new epistemology may be emerging, but it does not seem that connectivism’s contributions to the new paradigm warrant it being treated as a separate learning theory in and of its own right.  Connectivism, however, continues to play an important role in the development and emergence of new pedagogies, where control is shifting from the tutor to an increasingly more autonomous learner.

Although there is little conclusive evidence to support some of the more outrageous claims being made, there is at least a distinct possibility that while information is everywhere, knowledge is declining and technology is to blame.

So perhaps what is more important is not whether technology is making us stupid but if educational systems need to shift from teaching us what to think, to showing us how to think

In terms of what this means for education, psychologist Robert Bjork and his team at UCLA have been investigating what they call “desirable difficulties”. A desirable difficulty is a feature of a learning situation that is deliberately made more challenging to enhance learning.

Kahneman’s research on dual process theory suggests we mostly rely on what he calls “system one” thinking. That is thinking that is fast, efficient, mostly automated, and very good at detecting patterns, relying on short cuts or heuristics wherever possible. “System two”, on the other hand, requires slow, deliberate thought and is much more taxing of cognitive resources. System two is where the heavy lifting is done.

Traditional, lecture-based classrooms are designed as passive learning environments in which the teacher conveys knowledge and the student responds (Chen, 2009).

"He or she supports the students in their search and supply of relevant material, coordinates the students' presentations of individual milestones of their projects, moderates discussions, consults in all kinds of problem-solving and seeking for solutions, lectures on topics that are selected in plenary discussions with the students and conforms to the curriculum" (Motschnig-Pitrik & Holzinger, 2002, p. 166).

scaffold the learning process

Examples of emerging web applications for each of these categories are highlighted. The Networked Student Model establishes a baseline that begins to address what level of structure is needed to facilitate networked learning while providing a foundation for greater student control over the personal learning environment.

Networked learning, constructivism, and principles of connectivism inform the instructional design and provide a foundation on which future studies can explore the impact of networked learning on K-12 students and teachers.

It is the combination of these connections, especially in concert with human to human contact, that provide the most powerful learning potential (Goodyear, 2005).

The significant connections in Couros' view of the network include colleagues, popular media, print and digital resources, the local community, blogs, wikis, video conferencing, chat/IRC, social networking services, online communities, social bookmarking, digital photo sharing, and content development communities (Couros, 2008).

The networked student follows a constructivist approach to learning.

The Networked Student Model of constructing personal learning environments is reflected in many connectivist principles.

The networked student constructs knowledge that can be built upon in other contexts. That knowledge resides within the network to be activated by the learner at any time in the future. There is always the capacity to add nodes to the network (Siemens, 2009).

Ultimately, meaningful learning occurs with knowledge construction, not reproduction; conversation, not reception; articulation, not repetition; collaboration, not competition; and reflection, not prescription (Jonassen et al., 2003).

Learning potential exists in what the student does with the compilation of content and how it is synthesised.

exploring problems, asking questions, making discoveries, achieving new understanding and fulfilling personal curiosity" (National Science Foundation, as quoted by Chang & Wang, 2009, p. 169)

The networked student test case follows a single iteration, design based research process (Ma & Harmon, 2009) for analysing a problem, developing a solution, testing a prototype, and reflecting on the results.

The students had never participated in networked learning, so a significant amount of time was allotted at the beginning of the project to address digital literacy as well as task and organisational skills that would be required in the online environment.

The process and tools are overwhelming to students if presented all at once.

Achieving the delicate balance between teacher control and student autonomy is an ongoing challenge when facilitating student use of new technologies for self-regulated learning

e expected to be

The following are several specific examples of what the open standards and services must enable to make this new architecture for learning a reality: Digital content and applications must be easily, quickly (ideally, within a few minutes versus months), and seamlessly integrated into any platform that supports a set of vendor-neutral open standards and, importantly, are not trapped inside a single platform. User, course, and context information must be synchronized among selected applications so that neither the manual transfer of information nor multiple logins to different applications are required—thus making set-up and use of new software much easier for all concerned. Data that describes usage, activities, and outcomes must flow from learning content apps to the enterprise system of record, learning platforms, and analytics platforms. Systems, services, and tools must be virtualized and must increasingly move toward the elastic computing model that enables sharing scenarios across systems or other federations of users.Imagine what would happen if CIOs could safely add services and applications in a matter of days instead of months, if instructors could seamlessly combine these tools into their courses with one click, and if analytics data would begin to flow immediately thereafter. This new IT architecture would revolutionize the support for academic technology in the same way that the app movement has revolutionized what is available on mobile devices. A key difference with the new IT architecture, however, is that these educational apps are built using standards adopted and managed by the educational community and would be connected into the educational enterprise IT infrastructure.

The rise of the MOOC illustrates how important innovations often happen outside of established channels: by faculty who, interested in innovation, put together their own technology solutions outside their college or university. This should be a wake-up call for the higher education community to do better. Enterprise IT organizations need to enable such innovation, not stand in its way.

is links to the point made by Goodyear et al (2014) Unless learning is very closely supervised and directed (which it rarely is), there will usually be some slippage between task and activity, for good and bad reasons. This is important to acknowledge, when designing, because what people learn is a consequence of their actual activity, and therefore only indirectly a result of the task set for them. Tasks are designable, activities are not – they are emergent. (p. 1

Goodyear et al (2014) pick up on the term affordance as both important, but also as “a term that is also very widely critiqued and contested” (p. 137). The idea is that particular technologies afford different possibilities dependent on people’s perceptions of a technology. But an affordance isn’t a single set of possibilities seen by every person. Taking what Goodyear et al (2014) describe as a “relational-materialist” the idea of affordance becomes much more complex and emergent.