Prof. dr. Rob Koper ([email protected]) Educational ... · PowerPoint-presentatie Author: Rob Koper...
Transcript of Prof. dr. Rob Koper ([email protected]) Educational ... · PowerPoint-presentatie Author: Rob Koper...
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Learning Networks for Lifelong Learning
Prof. dr. Rob Koper ([email protected])Educational Technology Expertise Center
Open University or the Netherlands
EADTU conferencne
Oct 22, 2004
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Content
Model and Simulation of a LN:preventing dropout by using indirect social interaction (see handout)
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Learning Networks for Lifelong Learning
A learning network is a group of persons who create, share, support and study learning resources ('units of learning') in a specific knowledge domain.
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LN Graph with a learner track
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Patterns of Collective Tracks Emerge
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use case
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Three Core Issues in a Learning Network
1. How to make & use pedagogical well designed, interoperable and reusable units of learning in the LN?
2. How to position learners in a LN? 3. How to help learners to navigate in the LN?
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Navigation questions within LNs
I want to know something more about topic X, is there an adequate unit of learning available?
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Model
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Netlogo Simulation of a LN
● Multiagent simulation environment for research● See Draft publication in handouts
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Learners + Units of Learning in a LN
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Properties
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One of the Experiments with the Simulation
● Problem: what is the effect of indirect navigational feedback on study success (number of students that attained objective)?
● 24 factorial design: pheromone (feedback) strength (0 or 100%) matching error (0 or 100%) disturbance in learner environment (0 or 100%) quality of the unit of learning (0100% or 100%)
● N=12 replications in every condition● Every replication runs 260 simulation weeks
(5 years). In total 49920 week cycles (runs about 10 hours on fast computer)
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Interaction Pher * Matchingerror
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best versus worst case
60
65
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Prop-attained
-25 0 25 50 75 100 125
pher-strength
no matching error, 100% quality and no disturbance (F = 0.7816)
100% matching error, 0% quality and 100% disturbance (F = <.0001)
10
15
20
25
30
35
40
Prop-attained
-25 0 25 50 75 100 125
pher-strength
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Outcome● Overall influence Pheromones: 9% increase in
proportion of students who attained their objective
● Matchingerrors are compensated by pheromones
● Some quality variance is compensated by pheromones
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Publication
● see: http://dspace.ou.nl
Title:
Increasing Learner Retention Using Indirect Social Interaction in a Simulated Learning Network
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