Transcript Learning Technologies Development Programme

Self-Organized Learning
Networks for Lifelong Learning
RTD Programme 2003-2008
Rob Koper, Peter Sloep, Colin Tattersall,
Peter van Rosmalen
Educational Technology Expertise Centre
Open University of the Netherlands
www.learningnetworks.org
Hannover, November, 24th 2003
Overview
Introduction to the
Programme
Rob Koper
Semantic Representation Rob Koper
of Nodes (IMS LD)
Agent technologies to
support teaching
functions in learning
networks
Peter Sloep
Navigation in Learning
Networks
Colin Tattersall
AlfaNet (use of LD in a
context of agent
technologies and
collaborative learning)
Peter van Rosmalen
Introduction
Open University of the Netherlands
- Started in 1984; National (Public) Institute
- Two missions:
1. provide open distance education and
2. innovate education (in general)
Open distance education
- 6 faculties, 23000 students (age avg 32),
- 9 bachelor/master programmes; students can make a
free selection of courses during their life
- 20 study centres in Netherlands and Belgium
- Develop self study materials in multidisciplinary
teams
- Deliver education through a variety of technologies
(print, cd-rom/DVD, telephone, internet, face to face
contact sessions, practicals, etc.)
Innovation
Educational Technology Expertise Center
- RTD programme into Learning Technologies
- RTD programmes into LT
1998-2002: Educational Modeling (EML, IMS LD, Edubox)
2003-2008: Learning Networks for LifeLong Learning
- Positioning:
a. Major expertise ‘educational technology’
b. Major focus is: innovation through development of new
learning technologies
c. Between Educational Science and ICT technologies
d. Bring in educational requirements that are specific
enough to be implemented in ICT environments
Learning Networks Programme
2003-2008
Basic activities
1. RTD projects in several themes
2. Standardization activities
3. International Expert groups
4. EU projects and national RTD projects
Objective of Programme
Develop a coherent set of learning technology
models, specifications & tools to establish a new
effective, efficient, attractive and accessible
approach for higher, distributed lifelong learning,
called learning networks.
Network in the interpretation of:
1. Network of interacting persons and resources:
heterogeneous lifelong learners, experts, tutors,
learning resources and tools in some knowledge domain
2. Network of interacting distributed devices (e.g.
computers, mobiles, …)
3. Network of interacting providers for lifelong learning
resources and services (institutions, libraries,
publishers, associations, companies, …)
Programme addresses two key issues
1. Establish the emergence of lifelong learning into
a distributed, heterogeneous network of learners,
providers and software agents
2. Help staff members to do their work more
effective and efficient (minimize staff work load)
Issue 1: Lifelong Learning
Some general questions:
- How do lifelong learners learn? What do
we know of the learning behaviours and
preferences of persons during their
lifetime and career
- How can we support lifelong learners
with new learning technologies?
Issue 2: Efficiency of Support
Basic Question.
How can we:
-
make learners more productive, responsible,
adapt to prior knowledge, provide freedom of
navigation (learner),
produce high quality learning resources (knowledge)
provide more formative feedback on the productions
(assessment)
can involve more experts and practitioners, handle
heterogeneity in groups (community)
…
without increasing (or better: decreasing) the workload
for the staff members involved.
Main instruments in programme
- Models, principles and rules to establish
self-organized, distributed lifelong learning
- agent technologies (in context of semantic
web) to support the actors in the learning
process (learners, tutors/experts,
developers) and
- interoperability specifications and standards
(e.g. for portable learner dossiers,
competencies, architectures, etc.)
Main programme themes
1.
2.
3.
Development and use of Activity Nodes
How to design, create, share, use units of learning
in the Learning Network
Learner Positioning in Learning Networks
How to position new and existing learners in a
Learning Network independent of curriculum or
institution
Navigation in Learning Networks
How to navigate in Learning Networks, using &
exchanging recorded learning tracks, learning
routes and learning patterns in Learning Networks
IMS Learning Design
In Short
- New standard from IMS (februari 2003)
www.imsglobal.org
- Based on our previous work on EML (Educational
Modelling Language; published december 2000)
- Objective is to model complete Units of Learning
that can be transferred to different systems and
contain the compete description of its designed
content and process.
- Provides an integrated framework for different
other IMS specifications (incl. LOM, QTI, LIP, CP,
RCD, SS)
What is a Learning Design?
- The learning design specifies the specific
workflow and content in the learning process:
which role has to performs which activities, using
which resources and services in which order
in order to attain the learning objectives in the
best way, taking care of individual differences
(LD is an instance of a pedagogical model:
a concrete application of a pedagogical model for a specific
target group, for specific learning objectives and a specific
domain)
Content Packaging & Learning Design
PACKAGE
Unit of Learning
Manifest
Manifest
Meta-data
Meta-data
Organizations:Organization
Organizations:L. Design
Resources:Resource
Resources:Resource
(sub)Manifest
(sub)Manifest
Physical Files
The actual content: HTML,
Media, Activity descriptions,
Collaboration and other files
Physical Files
The actual content: HTML,
Media, Activity descriptions,
Collaboration and other files
Why IMS LD?
- Pedagogical meta model
- Offers a level of abstraction enabling different
educational models to be described, including:
Learner, Knowledge, Assessment, Community Centered
Approaches (in the different ‘schools’)
- Software which knows about the meta-model can
interpret specific models—model an approach to
learning (eg problem based learning) and have it
executed (‘played’)
- Complete specification of a course (not only the
resource part; needed for automation and
interoperability)
- Moves the focus from Learning Objects to
Learning Activities
Some References
- IMS LD (download www.imsglobal.org)
- www.learningnetworks.org (EML)
- See: list with recent journal articles/books/chapters
Agents for Support Activities (ASA)
Peter van Rosmalen , Peter Sloep
November, 2003
Rationale for ASA
1. Support staff lends support to many
different kinds of Learning Activities.
2. This puts quite a strain on the support staff.
3. From an institutional point of view this
means that providing support for learners
rapidly becomes unaffordable.
Premises
- Establish learning related interactions between
distributed actors and distributed resources in a
Learning Network.
- Do so efficiently: minimally maintaining the
intensity and learning quality of the interactions
without increasing staff workload.
Objective
To develop learning technologies (agents) that
help tutors support their students in learning
networks by
1. Building an abstract change model that
provides entry points for the development of
tools
2. Developing functional prototypes of these tools
and test them in pilots.
Outcomes
• a model of how tutors will be supported in
their support activities for the Activity
Nodes in a Learning Network
• prototypical software modules that qualify
as generic support agents for tutors
• a model of how agents operate within the
context of a design specified in IMS-LD.
Some details
- Focus on the tutor: support the tutor, not the
learners directly
- Focus on agents that will build upon language
technologies (e.g. support for e-mail answering
and essay grading)
Navigation in Learning Networks
Colin Tattersall
Navigation in learning networks
-
-
Exploiting collective learner interactions to help learners
select paths through learning networks towards their
educational goals.
- “Others who went before you proceeded that way to
reach their educational goals”.
- A feedback loop which guides learners in deciding what
to do next.
- The idea is that an individual’s chances of reaching his
or her goals are improved through insights on how
others have successfully reached their goals.
Aim: to improve educational yield using principles of selforganisation
Educational yield
m learners
n learners
t0
t1
Time period t
Educational yield is the percentage of learners which successfully meet certain
criteria in a given timeframe. Success might be ‘accumulating study points’,
undergoing an oral examination, etc
Yield = ((n/m) * 100)
Positioning in Learning Networks
Goals = “Destination” = a position in a learning network which reflects
the mastery of certain competencies;
-the point of departure
(which competencies an
individual already possesses)
-destination (which
competencies are desired to
be gained)
-the assessment of whether
the destination has actually
been reached (i.e. testing
whether competencies have
been mastered)
Navigation vs Positioning
- Positioning:
- “I have these competencies and I want those”
- “I am here and I want to be there”
- Navigation: how to get from here to there
- (Must carry out all units of learning in a certain order)
- Must carry out all units of learning but can vary order
- Travelling Learner Problem
- Can select which units of learning to perform vs. which
to skip but must follow a particular order
- Can select which units of learning to perform and in
which order
Feedback
•Which information should be fed back (eg, success rate, time taken)
in
•How? As abstract directed graphs? Landscapes of competencies?
self-organising
•When? Always show everything?
learning
networks
Feedback to learners
Feedback to providers
Filters
Track1:
Track2:
Track3:
Track4:
AN1,
AN1,
AN1,
AN1,
AN4, AN6: learner1, learner6, …;
AN6: learner4, learner9,…;
AN10, AN2, AN4: learner7;
AN2: learner99, learner77, …
Learner/activity interaction
data
Presentation
of collective
learner
behaviour
Emergent,
macro-level
information
Micro-level
interactions
Interaction data
Inspiration: self-organisation by ants
Learning Tracks & Roadmap
Tracks are left
behind by learners
like the pheromones
left behind by ants
The intensity of the
track reflects
chances of success,
number of attempts,
time taken, … ?
Feedback to help answering …
-
Learners
- How did other learners progress in this learning network from
where am I now?
- Which path through the learning network offer the most chance
of success?
- What has been the fastest path taken by others through this
Learning Network?
-
Providers
- What percentage of learners followed the learning route(s)
prescribed in the curriculum through the learning network?
- Is the learning route the most efficient way to progress through
the learning network or are learners identifying better paths?
- Where are learners slowing down or dropping out?
ALFANET
Active Learning For Adaptive Internet
Peter van Rosmalen
Open University of the Netherlands
November,2003
Project Aims
Alfanet aims to develop new methods and services for active
and adaptive e-learning. The project’s target is to deliver a
tested set of components for e-learning providers that will
provide significantly enhanced individual learning, through
technologies with adaptive features and approaches.
Key issues:
• Adaptation – individual needs design- & runtime:
Links, contents & collaboration
• Feedback loop for the design
• Agent-supported architecture
• Standards: IMS-LD, ……
• Partners: SAGE, UNED, EDP, KLETT, ACE-BNET, OUNL
Core Components and Standards
OpenACS
- (UNED) provides facilities for collaborative
learning.
IMS-LD
- to enable advanced pedagogical designs
including adaptation
- to enable communication between the different
actors – designers, tutors & agents
IMS-LD authoring tool
- (ACE-BNET)
IMS-LD engine
- (OUNL)
Agents
Learning Adaptation Model (UNED)
- will support the learner in collaborative learning,
navigation and content selection.
Audit (OUNL)
- will support the design team with feedback
concerning the initial design and the actual use/results
Multi-Agent Pedagogical Model (OUNL)
-will support the design team with the selection & use
of LD-models.
- will support the learner during the execution of
selected activities.
IMS LD
IMS LD
Unit of Learning
IMS-LD
IMS-LD-engine
Authoring tool: design time
properties
Tutor:
• Designed role
• Observator role
Adaptation based
on the design
Audit feedback to
the design based on
runtime monitoring
Agents:
• Audit
• Adaptation
• MAPM
Adaptation based on
runtime monitoring of
agents and tutors
Presentation layer
Technical Architecture
LD
En
J2EE Application Server
Security Layer
Presentation Layer
Server
Tracker
Dispatcher
1…n
Services
Object Model
Common
Repositories
Authoring Tool
Data
Current Status
Current Status
Alfanet version 1 (1 January-2004)
Integrated:
- IMS LD Authoring Tool
- OpenACS (collaborative framework)
- IMS LD level A engine
Partly integrated / partly demonstrators
- Learning Adaptation
- Audit
- MAPM
Evaluation round 1 (January-March 2004)
- design and learner evaluation of two courses