Enhancing Collaborative Learning with Gridcole Technologies

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 • Providean 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

6. 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

10. 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

16. 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

19. Scenario outline • 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, …

20. 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