Collaborative E Learning Assistant Network

Collaborative eLearning Assistant Network Caring agents are conscious agents 2 December 2007

Introduction
The team:
Patrick Parslow, Shirley Williams, Will Browne
Contact details:
[email_address]
My Background –
Cybernetics, Computer Science, Civil Engineering(!)

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.

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

How conscious can a computer be?
Not at all
Aware of surroundings
Aware of self
Aware of others
Fully

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 (!)

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 one’s own being with other similar agents
Using same processes that model ‘other’ to model ‘self’

Is it ethical?
No
If it can be proven safe
Human rights come first
If the MC has rights
Yes

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

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…

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

In pictures

Supporting Connectivism…

Would a Machine Conscious eLearning agent help?
No
Only some people
Many, but not all people
Yes

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

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.

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
http://meaggregator.googlecode.com/
Chosen as a backbone because it provides
Ontology
Trust
Peer – Peer
Search

Thank you
Any Questions?

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

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

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: http://www.jiscinfonet.ac.uk/InfoKits/effective-use-of-VLEs
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”

Collaborative E Learning Assistant Network

by Pat Parslow on Jan 30, 2008

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Collaborative E Learning Assistant Network — Presentation Transcript