The Network Sense

The learning network infrastructure

While at Learning 2008 I got to thinking about the learning implications of Kevin Kelly’s concept of the ‘One Machine’, or the idea that the increasing global, interconnected, virtual world is leading to an emerging global ‘machine’ with the Internet as its operating system. Metaphorically, this concept can be conceived as cloud-shape brain that scaffolds the planet. In Kelly’s words:

There are 20 billion visible, searchable web pages and another 900 billion dark, unsearchable, or deep web pages (for instance pages behind passwords or the kind of dynamic page that Amazon will produce when you query it). The average number of links found on each searchable web page is 62. Assuming the same count for dynamic pages that means there’s 55 trillion links in the full web. We could think of each link as a synapse — a potential connection waiting to me made. There is roughly between 100 billion and 100 trillion synapses in the human brain, which puts the Machine in the same neighborhood as our brains.

The learning node

Judy Breck is a thought-leader promoting the unbundling of online learning resources into individual ‘learning nodes’ so that they can be discovered by search engines and linked to by others.

By using podcast XML distribution, Praxis initially let the characteristics of the medium define the form that our lesson media would take. Each individual XML item in an RSS feed is modular by nature, so it made sense to design each lesson as an individual, non-sequential object. By designing lesson objects in this fashion, it was thought that it would be possible to empower others, such as teachers, to re-mix individual lessons into courses that would be more tailored for the needs of their students. Adults adopting kids from China could get one type of course, business professionals could get another.

A second-characteristic of podcast technology is the ability to push content out to users. Instead of investing in a static archive of a hundred, or a thousand lessons, we have found it important to publish new lessons daily, not only to keep the overall lesson archive fresh, but importantly to help focus student attention and fuel community conversation. The down-side of this approach is that a less self-motivated student will, by habit, default to the publication schedule as a pseudo-course - an unintentional result. We see this phenomenon with our products as the vast majority of student attention focus on the most, recently published podcast lessons.

Language students may be drawn to individual lessons that they are interested in, but ambitious students need courses and structured pathways to help them reach their learning goals. While lesson modularity provides the basic building blocks for high levels of customization, the fact is teachers, software agents or the community need to fill the gap of course construction. A balance needs to be struck between modularity and tailored structure. Social networks combined with learning frameworks can fill that gap.

Social Learning Networks

In a recent post, Breck argues that while learning objects should be broken down for the above reasons, there is value in the course as a bundle - or as she carried on an analogy from network science, a ‘hairball’.

From a curriculum design perspective her logic is clear, but one wonders where the interactions and motivations of students and teachers come into play. From our experience with individual, adult students motivation is absolutely critical. This motivation may be internally-driven (aspirational) or standards-driven (e.g. HSK), but social networks can also definitely amplify socially-driven forces (e.g. camaraderie, competitive pressure, etc) to provide further nudges. With all the competing demands for one’s time from work, to family, to hobbies a helpful nudge or two is often necessary to play that next lesson on your MP3 player, rather than you favorite song.

Jay Cross’ argument, that learning is increasingly seen as optimizing one’s network, further points to social networks for inspiration:

Schooling has confused us into thinking that learning was equivalent to pouring content into people’s heads. It’s more practical to think of learning as optimizing our networks.

Define social networks as self-forming organizations around tasks its members like to do and - again - it is obvious the importance of user contribution. The fact is human motivation, measured in attention, is what powers social networks.

In addition to focusing on instructional design, new learning models need to start incorporating users wants/needs/preferences to ensure student motivation. Instead of a ‘hairball’, something more akin to a ’solar system’ metaphor seems appropriate where a structured learning course (sun) needs to attract (as with gravity) the students that orbit it.