GRIDCOLE: a Grid Collaborative Learning Environment

1
GRIDCOLE a Grid Collaborative Learning
Environment

• M.L. Bote-Lorenzo, L.M. Vaquero-González, G.
  Vega-Gorgojo, J.I. Asensio-Pérez, E.
  Gómez-Sánchez, Y.A. Dimitriadis
• University of Valladolid, Spain
• CLAG 2004

2
Index

• Collaborative Learning Systems
• Gridcole
• Approach
• Functionality
• Implementation
• Sample Collaborative Learning Scenario
• Conclusions and Future work

3
Index

• Collaborative Learning Systems
• Gridcole
• Approach
• Functionality
• Implementation
• Sample Collaborative Learning Scenario
• Conclusions and Future work

4
Collaborative Learning Systems

• Provide an environment with suitable tools in
  order to support a given collaborative learning
  scenario
• E.g C-CHENE
• Promotes learning of concepts related to energy
  in physics
• Provides a free chat, a structured chat, and a
  collaborative energy chain editor
• CSCL researchers have developed many
  Collaborative Learning System

5
Drawbacks of most CLSs

• Lack of tailorability
• A tailorable CLS enables easy integration of
  suitable tools within a single environment in
  order to support a given collaborative learning
  scenario
• E.g DARE, Symba
• Use of tools requiring supercomputing
  capabilities is not allowed
• Needed in many natural sciences and medical areas
• E.g weather forecasting (CoVis Collaboratory)
• Use of tools requiring specific hardware
  resources not allowed
• Employed in many collaborative learning scenarios
• E.g integration of seismographic sensors (Coldex
  Project)
• Interpretation of collaboration scripts not
  allowed
• Script interpretation enhances the effectiveness
  of learning
• E.g COW, Coppercore

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Gridcole

• A new CLS that aims to overcome the drawbacks of
  current systems
• Based on two standards
• IMS Learning Design (IMS-LD)
• Enables formal description of teaching-learning
  processes
• Open Grid Services Architecture (OGSA)
• Defines a service-oriented structure for grid
  computing environments

7
Index

• Collaborative Learning Systems
• Gridcole
• Approach
• Functionality
• Implementation
• Sample Collaborative Learning Scenario
• Conclusions and Future work

8
Gridcole Technologies

• OGSA-based grids
• Service-oriented architecture
• Enable transparent access to
• Large amounts of computing power
• Specific hardware resources
• IMS-LD documents
• Describe a learning scenario
• Roles to be played by each participant
• Sequence of learning activities to be performed
  by each role
• Tools and documents that support each activity
• Supports a wide range of pedagogies
• Can be applied to collaborative learning

9
Gridcole Approach

• OGSA-based grid used as a pool of tools
• Tools not limited in supercomputing or specific
  hardware needs
• Tools without such needs can also be employed
• IMS-LD documents employed as
• A tailoring script describing the tools to be
  integrated
• A collaboration script to be interpreted in order
  to structure interactions between students

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Suitability of Approach
11
Index

• Collaborative Learning Systems
• Gridcole
• Approach
• Functionality
• Implementation
• Sample Collaborative Learning Scenario
• Conclusions and Future work

12
Tailoring

• Educators can tailor Gridcole providing an IMS-LD
  document
• The system follows IMS-LD document to find tools
  in a grid
• Educator can choose between different tool
  implementations

13
Support

• Gridcole supports the scenario following the
  IMS-LD document
• The sequence of activities to be carried out by
  each student is determined
• A personalized desktop is provided for each
  activity
• Desktop enables the use of grid service tools
  through graphical interface panes

14
Index

• Collaborative Learning Systems
• Gridcole
• Approach
• Functionality
• Implementation
• Sample Collaborative Learning Scenario
• Conclusions and Future work

15
Architecture
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Prototype

• Gridcole is currently under development using GT3
  and Java
• A first prototype has been built
• Shows the feasibility of our system

17
Index

• Collaborative Learning Systems
• Gridcole
• Approach
• Functionality
• Implementation
• Sample Collaborative Learning Scenario
• Conclusions and Future work

18
Educational context

• Course on Computer Architecture for undergraduate
  students
• Organized around a design project (three
  subprojects)
• Groups of four pairs collaboratively play the
  role of consultants
• Have to advise a given customer on a computing
  solution (machine, operating system, software,
  etc)
• The scenario applies for the first subproject,
  with clear learning objectives
• Contents
• Learn how to use benchmarks
• Get a quantitative impression on a few real
  machines
• Skills
• Interpreting and selecting information
• Arguing
• Taking compromise solutions

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Scenario outline

• Designed by course teachers
• Learning activities
• Model customers presumed computational load
• Test real machines using benchmarks
• Debate best solution for customer
• Tools
• Collaborative group formation, concept map, task
  assignment, debate
• Non-collaborative text editor,
• Specific hardware needs benchmarking tool,

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Scenario realization

• Gridcole support will be evaluated from
  educational point of view next fall semester
• Tools offered in a grid shared by three
  Universities
• A limited version of this scenario has been
  realized using Gridcole prototype
• Includes four activities
• Employs three tools
• Collaborative task
• assignment tool
• Benchmarking tool
• Chat tool

21
Index

• Collaborative Learning Systems
• Gridcole
• Approach
• Functionality
• Implementation
• Sample Collaborative Learning Scenario
• Conclusions and Future work

22
Conclusions

• Tailoring, scripting, supercomputing
  capabilities, and specific resources are not
  supported by most CLS
• IMS-LD and OGSA technologies can be combined to
  address these issues
• Gridcole is a new CLS that builds upon IMS-LD and
  OGSA
• Gridcole can provide valuable support in real
  collaborative learning scenarios

23
Future Work

• Complete development of Gridcole
• Evaluation from educational point of view
• Characterization of tool services using the
  Learning Object Management (LOM) standard
• QoS provision

24
GRIDCOLE a Grid Collaborative Learning
Environment

• M.L. Bote-Lorenzo, L.M. Vaquero-González, G.
  Vega-Gorgojo, J.I. Asensio-Pérez, E.
  Gómez-Sánchez, Y.A. Dimitriadis
• University of Valladolid, Spain
• CLAG 2004