Category Archives: Learning

IBIS meets MediaWiki

Some slides are now online at slideshare which are drawn from training materials for the Bloomer project which is a component in the collective intelligence platform being installed in some Millennium Project nodes. The IBIS MediaWiki extension can be added to any MediaWiki installation (though it’s not tested on the latest MediaWiki build); it should be possible for a good PHP developer to adapt its code to other platforms such as Drupal.

The extension presently is configured to maintain an index of conversations. Each conversation starts as a Wiki topic, and each question, answer, or argument (see below) is also an individual Wiki topic.

IBIS stands for Issue-based Information Systems, and it’s a target in my thesis research. IBIS conversations are structured, meaning each question, answer, or argument occupies its own node which is linked through a coherence-relation to another node. Some references are found at the Compendium website.

A lone question or idea can start a conversation; answers or questions respond to questions. Answers respond to other answers to expand on them. Pro or con arguments follow answers. As a conversational tool, online structured conversation platforms are part of the argument web. They are also highly appropriate to #CCK11 connectivist thought.

Examples of structured conversation platforms include Compendium, Cohere, DebategraphTruthMapping, Climate Collaboratorium, and Argument Mapping and an emerging list of others. It should be noted that Jane McGonigal has introduced IBIS as playing cards in her online games, including the MRF Game I mentioned here, and these.

MRF Game Results Posted

The Myelin Repair Foundation game on which I reported here and here is now discussed at the Robert Wood Johnson website. The 30 page pdf is found here. The report opens with this:

On October 7–8, and November 9–10, 2010, Institute for the Future (IFTF), in cooperation with the Myelin Repair Foundation and the Robert Wood Johnson  Foundation, hosted a Foresight Engine thought experiment called Breakthroughs to Cures.  Designed as an open, non-partisan environment where models for innovation in medical research can be freely explored and developed, the purpose was to generate  “outlier” ideas and strategies that could lead to more effective and efficient ways to fund  and conduct medical research with the goal of speeding up the development of patient  treatments and cures.

Played as a “card game” where each card resembles a node in an Issue-based information systems (IBIS) conversation as seen in, for example, Compendium which I illustrated from my own MRF game moves here, or at Debategraph, the game provided wide opportunity for journalistic discovery and reporting. The report says this:

In sum, what game play pointed to was a variety of opportunities—particularly in terms of technological infrastructure and in terms of the types of relationships that could be built to bring new ideas to basic science research and to make better use of current resources. Many of these ideas point toward long-term opportunities to facilitate connection and accelerate, and in this sense, provide the outlines for actions to take over time to accelerate medical research.

I believe that an important contribution provided by the MRF game report as produced by IFTF members is its illustration of how a crowd-sourced research project could produce results that journalists could then synthesize into a report worthy of any sensemaking project which leads to decision making.

Where could the MRF games go from here?  I believe the answer to that question lies in the hands of those who created, conducted, and funded that project. What value can those of us who research and practice the art and science of sensemaking through hypermedia discourse gain from the MRF game? The answer to that lies precisely in what we do with not only the report linked above, but also what we do as we study the game boards ourselves seeking to better understand the craft exhibited.

CCK11 Thinking about connectivism

I am sitting in on a MOOC (massive online open course–seriously cool!) about connectivism.  The term itself caught my eye, though I had to spend some time disambiguating it with “connectionist” (computational neural net) stuff. I now see it as extending learning theories that spanned behaviorist to constructivism, now connectivism. See  this document for the chart, and this page for the first week’s activities.

Actually, I’m fighting a battle with cognitive dissonance here. I’m wrestling with the notion that the chart linked above appears to be trying to answer the wrong question.  In my view, the issue is not about how connectivism is different from the other learning theories; rather, the question should be closer to how connectivism builds on earlier theories, since I believe that’s what it is trying to do.

My view is built upon notions of relational biology due to Rashevsky and Rosen.  In “Topology and life”*, Rashevsky, one of the founders of mathematical biology, realized that we can tease apart a living organism and count the components (which has the nasty side effect of killing it), but we cannot put it back together. Something in our knowledge of living (complex) things is missing. He set out to find out what that something is. Rosen came along and later and offered a mathematical model called the Metabolism-Repair System which serves as a candidate answer.

A central tenet in the Rashevsky-Rosen concept is that the action lies in the connections.

Rosen authored the book Anticipatory Systems (soon to be reprinted) which essentially (my view) offers the underlying basis for all learning theories: living entities are anticipatory by nature. From the lowest single cell creature to the largest living creatures on Earth, anticipatory behavior is in play, whether it’s simple chemical reactions to sunlight bending a plant to face the sun, or to complex neurological processes from neural firings to brains at work.  That model fits all the learning processes, be they conditioned-response or people in networks.

Ok, I just offered a highly reductionist explanation to a massively complex set of processes. I don’t see that as any different from someone saying that process X is better than process Y. At some point, as Rosen was fond of saying in his books, you have to keep asking “why”.  I believe that anticipation serves as a foundation on which “why” questions can best be understood and, perhaps, debated. My own answer to cognitive dissonance is to ignore the “my process is better than” arguments and spend time seeing how they each work together.

* Topology and life: In search of general mathematical principles in biology and sociology. Bulletin of Mathematical Biophysics 16 (1954): 317–348

Online games that matter

The Institute for the Future (IFTF) teamed with the Myelin Repair Foundation, funded by the Robert Wood Johnson Foundation to host a game with this title:

How would you advise the President to reinvent the process of medical discovery?

The game was played here, ending today. Following the game, as part of my thesis project, I wrote a quick summary report, found here.  At the same time, I created a new hashtag at Twitter: #ogtm for online games that matter.

My overall impression from playing the game is that online games that matter, with the Foresight Engine being a shiny new example, will play an increasingly important role in social sensemaking and learning.