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© University of Reading 2007 www.reading.ac.uk School of Systems Engineering 2 December 2007 Collaborative eLearning Assistant Network Caring agents are.

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Presentation on theme: "© University of Reading 2007 www.reading.ac.uk School of Systems Engineering 2 December 2007 Collaborative eLearning Assistant Network Caring agents are."— Presentation transcript:

1 © University of Reading School of Systems Engineering 2 December 2007 Collaborative eLearning Assistant Network Caring agents are conscious agents

2 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference2 Introduction The team: Patrick Parslow, Shirley Williams, Will Browne Contact details: My Background – – Cybernetics, Computer Science, Civil Engineering(!)

3 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Participation! Huge topic - Machine Consciousness (MC) & eLearning – Philosophy, Pedagogy, Computer Science, Psychology, Sociology, Ethics, Communities of Practice… Controversy about : – Whether MC is possible? – Whether MC is desirable? – Would MC improve an eLearning Assistant? – What is consciousness anyway? So – I will be asking for your opinions during the presentation. 3

4 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference What do I mean, Consciousness? It is hard to gain a consensus on what is meant by Consciousness – and hard to describe Features of a conscious system, by my working definition: – Aware of surroundings – Aware of self (an autonomous entity distinct from environment) – Aware of others (as autonomous agents in the environment) – Holding a Theory of Mind of others – Having a Theory of Mind of self 4

5 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference How conscious can a computer be? 5 1. Not at all 2. Aware of surroundings 3. Aware of self 4. Aware of others 5. Fully

6 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Why a conscious Assistant? Self (1999) advocated caring intelligent tutoring systems – Learner models – Prediction – Adaptive Conscious systems have – Theories of mind (models of the other) – Prediction – Adaptation – Self awareness (!) 6

7 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Hypothesis – consciousness is an emergent property Based on a certain minimum functionality – Machine Consciousness Capable (MCC) – can recognise, classify, model, communicate and predict Community – exist in an environment with others like them Advantage – there is an evolutionary advantage to modelling the other Model of self is a freebie – A result of associating ones own being with other similar agents – Using same processes that model other to model self 7

8 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Is it ethical? 8 1. No 2. If it can be proven safe 3. Human rights come first 4. If the MC has rights 5. Yes

9 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Motivation Motivation to use in eLearning – Caring agents need to be able to model and predict Thus they need to perceive, recognise, classify – Learners exist in communities Thus paired eLearning companions can exist in communities – The eLearning assistant works in a symbiotic relationship Benefits from providing the best advantage to its partner 9

10 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Complications Multiple strands of thought through different neural pathways – Only aware of one at a time Multiple interests – Like to keep on top of them all Multiple roles – In different contexts, family, social, academic, professional Multiple domains means multiple ontologies – Or does it? Folksonomies and context awareness… 10

11 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Complexity To deal with the complicated, use complexity. Not multiple MC agents, but multiple agents making up the machine consciousness – Accessing the same internal models Communicating with the user or learning partner But also with other MC agents in a network – Bringing experience from other learners – Building and exploiting a trust network – Generating meaning through folksonomical activity 11

12 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference In pictures 12

13 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Supporting Connectivism… 13

14 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Would a Machine Conscious eLearning agent help? No 2. Only some people 3. Many, but not all people 4. Yes

15 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Context, Meaning, Community First the Alternative view – Identity – Our roles in communities are given meaning by their context – Our identity is the aggregation of the meaning created – We define ourselves in the context of community Our sense of self, – the conscious feeling we are who we – defined and refined through continuous comparison, evaluation – Consciousness takes time to develop 15

16 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Context, Meaning, Community All things our MCC agent needs to be able to model – All embodied to some extent in a folksonomy if : it records when tags were created it records who created the tags it allows tags to be tagged it allows all the users resources and contacts to be tagged We are developing a folksonomical file system, FFS – Core technology behind the MeAggregator, a JISC sponsored project. 16

17 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference MeAggregator Designed to: – Interact with user-owned technologies – Build folksonomies – Provide a trust network - both permission and reliability – Allow peer-peer communication and publication – Run as a server or desktop solution Chosen as a backbone because it provides – Ontology – Trust – Peer – Search 17

18 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Thank you Any Questions? 18

19 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Learner model Building models of learning partner and self – Open learner modelling User control Reflective – Both learners, in partnership User can maintain a model of agent Helps agent learn about itself, its partner, and the relationship 19

20 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference CeLAN MC agents can support multiple roles. – Given a priori domain knowledge, can be intructivist – Can work as a mentor – Can be motivational – In a network, is connectivist My preference? – Research assistant – assessing sources for me – Conversational – seeming interested in what I am doing – Learns the subject area with me 20

21 Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference Use case Pat is researching Facebook and Blackboard, and searches for VLE – CeLAN observes him choose the last link on the results page – CeLAN Why that link? I trust JISC – CeLAN adds resources and relationships to its model – resA: relA: Pat searchedFor VLE relB: Pat choseLink resA relC: JISC trustedWRT relA relD: JISC relatedTo resA (etc.) – CeLAN interprets, and does a background search for VLE JISC 21


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