gridcole: a grid collaborative learning environment
DESCRIPTION
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. Index. Collaborative Learning Systems Gridcole Approach Functionality - PowerPoint PPT PresentationTRANSCRIPT
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
1. Collaborative Learning Systems2. Gridcole
a. Approachb. Functionalityc. Implementation
3. Sample Collaborative Learning Scenario4. Conclusions and Future work
3
Index
1. Collaborative Learning Systems2. Gridcole
a. Approachb. Functionalityc. Implementation
3. Sample Collaborative Learning Scenario4. 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
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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
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Index
1. Collaborative Learning Systems2. Gridcole
a. Approachb. Functionalityc. Implementation
3. Sample Collaborative Learning Scenario4. 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
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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
CSCL problems OGSA IMS-LD
Difficult integration
Defines a set of conventions and uniform
semantics
-
Scarce reuse High-level building blocksfit educator’s mental
model
Promotes learning design reuse and thus tool reuse
Technification Service provider in charge of deployment and set-up
Authoring tools enable easy edition of IMS-LD
documents
11
Index
1. Collaborative Learning Systems2. Gridcole
a. Approachb. Functionalityc. Implementation
3. Sample Collaborative Learning Scenario4. 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
E d u c ato rG rid c o le
1. S tore IM S -L D doc um e nt
2 . S e le c t IM S -L D doc um e nt
4 . S e le c t tools3 . S e a rc h too ls
O G S A -b a s e d grid5. L is t o f pa r tic ipa nts
6 . S ta r t e xe c ution
S tu d e n t
7. J o in e xe c utionT o o l A
T o o l B
T o o l D
T o o l C
T o o l E
T o o l F
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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
S tu de n t 1
D es k to p
O G S A -b a s e d grid
T o o l A
T o o l F
T o o l C
P an e A P an e F
S tu de n t 2
D es k to p
P an e A P an e C
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Index
1. Collaborative Learning Systems2. Gridcole
a. Approachb. Functionalityc. Implementation
3. Sample Collaborative Learning Scenario4. Conclusions and Future work
15
Architecture
Learning Flow
Engine
Index Service
Tool Grid Services
Index Service
Content Documents
Application
Web Browser
Service Clients
Document Browsers
Application
Client
Learning Object Index Service
Learning Design Repository
User Database
Tool Searcher
Service Clients
Document Browsers
User computers Gridcole computational resources
Third-party computational resources
Web Browsers
Web Portal
Learning Flow
Engine
Index Service
Tool Grid Services
Index Service
Content Documents
Applications
Application Desktops
Tool Index Service
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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
1. Collaborative Learning Systems2. Gridcole
a. Approachb. Functionalityc. Implementation
3. Sample Collaborative Learning Scenario4. 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
O rganiz e in groups S upervis e organiz at ion
S tudy c us tom er needs C larify c us tom er needs
M odel c om putat ional load
W eight ing benc hm ark s
D is t ribute m ac hines
E x ec ute benc hm ark s
Debate
L e a rn e rs Ed u ca to r Designed by course teachers Learning activities
Model customer’s 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 taskassignment tool Benchmarking tool Chat tool
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Index
1. Collaborative Learning Systems2. Gridcole
a. Approachb. Functionalityc. Implementation
3. Sample Collaborative Learning Scenario4. 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
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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
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