Darwin among the indices a report on COFIND, a self-organising resource base Jon Dron (jon.dron@brighton.ac.uk) Richard Mitchell, Chris Boyne, Phil Siviter University of Brighton, UK http://www.it.brighton.ac.uk/staff/jd29/cofind.html I am a toy maker, not a builder of serious adult machines. I'm going to talk about one of my favourite toys, but like all toys it has a serious purpose and one day I hope it will grow up into part of something more generally useful. I will be talking about the core of CoFIND, a larger system than I will portray which is designed to replace the role of the teacher through the combined individual contributions of its users. The use of the word Darwin in the title is not just for effect (it is incidentally a reference to a book which I haven't actually read by Samuel Butler, Darwin among the Machines, also not uncoincidentally the title of a more recent book by George Dyson which I have read). The system has components which evolve in the true sense of the word, involving selection of the fittest and reproduction with variation. THere has been much talk of ecologies, but here we have something very close to a true ecology, with variegated fitness landscapes.

A problem Seeking stuff from which to learn It is not enough just to classify: learners wish to know that discovered stuff is going to help them to learn Therefore: there is a need to rate the value of the stuff As I have suggested, this is part of a larger system and I am only looking at one of the roles of a teacher. Note that this is aimed at groups of learners becoming (not already) subject experts, discovering the subject. To start with they only have the vaguest idea of where to begin. I should also make it clear that I am aiming this at cohorts of adult learners

Two candidate solutions SOAPs Problems finding authorities Difficulties trusting authorities Recommender systems but learning is about change- today’s values and needs may not translate to tomorrow’s value is context dependant Seals of approval are the traditional ways we gauge the value of a resource- be it the recommendation of a friend and/or a teacher or formal peer reviews, or even citations in a paper, SOAPs are effective. However, if one of our problems is finding trusted authorities in the first place, they get us nowhere. Also, there is a lot of intellectual effort involved in perusing such reviews, and even when we have found what we are looking for we may not agree with the authority- authorities may have different agendas, learning styles etc. Recommender systems seek commonalities between individuals. Recommendations may be explicit (e.g. votes) or implicit (e.g. time spent looking at a resource. Sophisiticated ACFs match patterns of likes/dislikes and make predictions about what you will like next- e.g. firefly (RIP) or the more sophisitcated mechanisms used by amazon.

CoFIND A Collaborative Filter in N-dimensions Central concept: qualities beautiful amusing good-for-beginners reliable detailed useful Each quality is a dimension in value space Multiple qualities provide an n-dimensional view of the value of a resource For learners it is not enough to know that something is good or bad- good or bad in what way? For whom? CoFIND allows users to rate resources according to any set of values that they see fit.

A collaborative resource base What is CoFIND? A collaborative resource base Resources are entered, classified and rated by users of the system Metadata are entered by those users Useful metadata succeed in a complex fitness landscape defined by users, resources and competition with the other metadata in the system this is aimed at cohorts of learners with shared needs at a similar (but not identical) stage of development. All of the data and metadata are entered by the learners themselves. This includes not only resources but qualities and topics (set-based binary classifications) which relate to those resources. If they were allowed to grow unfettered then many useless topics and qualities might be generated. Therefore they can die through vote starvation. If no one uses a quality, it sinks to the bottom of the list of selectable qualities. If others are entered which are more successful, they eventually squeeze out the less popular metadata.

CoFIND Resources displayed in order of popularity according to currently selected quality Users may rate resources using the currently selected quality Qualities are selectable, displayed in order of popularity

Self-organisation... Learners enter resources New or existing qualities are used to rate resources Qualities compete- the more they are used, the more selectable (successful) they become So we are looking at a system with feedback loops, where the actions of the users have a profound effect on what and how thinks are displayed. The balance is still subject to tuning- still having troubles getting the balance between order and chaos to reach what the complex systems community knows as the edge of chaos. Too much order, nothing changes, stagnation. TO much chaos, change happens all the time and no stability is ever achieved. We need a balance to achieve evolution and dynamic change. Successful qualities produce lists of useful resources Success encourages re-use

Other features As well as URIs and qualities, users can add... Free-text (to create resources) Files Comments Topics (binary classifications) Asynchronous discussions of individual resources and topics (interesting messages may be added to the resource base)

Future directions CoFIND will be a fully self-organising learning environment There is a need to embody relationships between resources and to build paths More tuning needed- the algorithms are still not right More work needed on the interface Overcoming the “cold start” phenomenon

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