A Grid Approach to Provide Effective Awareness to Online Collaborative Learning Teams

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A Grid Approach to Provide Effective Awareness to
On-line Collaborative Learning Teams
1st International Workshop on Distributed
e-Learning Environments 14th of March 2005

• by Santi Caballe, Thanasis Daradoumis, Claudi
  Paniagua and Fatos Xhafa

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Index

• Introduction the importance of providing
  effective awareness to on-line collaborative
  teams.
• Knowledge of group and individual
  activity,
• and coordination are central to successful
• cooperation. These factors are clearly critical
• concerns in the design of computer systems
• P. Dourish V. Bellotti (1992)

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Index

• Introduction the importance of providing
  effective awareness to on-line collaborative
  teams.
• Approach need for structuring and processing of
  large amounts of group activity information.

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Index

• Introduction the importance of providing
  effective awareness to on-line collaborative
  teams.
• Approach need for structuring and processing of
  large amounts of group activity information.
• Problem lack of computational resources.

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Index

• Introduction the importance of providing
  effective awareness to on-line collaborative
  teams.
• Approach need for structuring and processing of
  large amounts of group activity information.
• Problem lack of computational resources.
• Solution a Grid-based approach to process group
  activity information through an application of
  the Master-Worker paradigm using Planetlab
  platform.

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Index

• Introduction the importance of providing
  effective awareness to on-line collaborative
  teams.
• Approach need for structuring and processing of
  large amounts of group activity information.
• Problem lack of computational resources.
• Solution a Grid-based approach to process group
  activity information through an application of
  the Master-Worker paradigm using Planetlab
  platform.
• Experimental results the benefits of a parallel
  processing approach

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Index

• Introduction the importance of providing
  effective awareness to on-line collaborative
  teams.
• Approach the process of creating awareness.
• Problem lack of computational resources.
• Solution a Grid-based approach to process group
  activity information through an application of
  the Master-Worker paradigm using Planetlab
  platform.
• Experimental results the benefits of a parallel
  processing approach
• Conclusions and future work.

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Introduction (I) Providing awareness to on-line
learning teams

• Awareness of co-learners activities is essential
  to achieve a successful cooperation, in terms
  of
• implicit coordination
• collaborative learning
• informal and spontaneous communication
• Awareness allows tutors to track the
  collaborative learning process for several
  purposes such as
• scaffolding
• assessment
• monitoring
• Awareness enhances the collaboration in great
  deal in terms of decision-making, social
  engagement, support and so on.

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Introduction (II) Providing awareness to on-line
learning teams

• During the collaboration, learners need to be
  aware of what others are doing at the same time
  and what they did in the past. This implies that
  awareness can be done in both modes
• synchronous to provide real-time information
  (e.g. co-members location and availability, who
  is doing what, etc.).
• asynchronous to provide deferred information
  (e.g. who, when, how and where a shared resource
  has been created, changed, read, etc.).
• Supplying effective and transparent awareness to
  users in both modes is a significant challenge
  since
• users interact with the system all the time and
  generate a great amount of information.
• this information may include a great variety of
  types and formats.
• the information collected needs to be classified,
  processed and analyzed and make the analysis
  results available even in real time.
• This requires processing capacity beyond a single
  computer.

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Introduction (III)Context

• Group activity at Open University of Catalonia
  involves hundreds of students and dozens of
  tutors in several on-line courses.
• The complexity of the learning practices entails
  intensive collaboration activity.
• BSCW is used as a groupware system to capture
  group activity interaction in log files.
• BSCW does not provide log file processing nor
  statistical analysis capabilities.
• BSCW generates a huge daily single log file and
  does not classify nor structure data in any way.

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Approach (I) The process of creating
awarenessThe whole picture

• Four stages in information management
• Classification, processing, analysis and
  presentation.

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Approach (II) The process of creating awareness
Stage I Classification

• Collection of information.
• Extraction of actions.
• Identification of events.
• Categorization according to
• Learning product
• Group functioning
• Scaffolding
• Store as system log files.

Classification in synchronous environments is
very similar.
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Approach (III) The process of creating awareness
Stage II Processing

• Obtain event information from large log files.
• Process log files according to desired criteria.
  e.g.
• time
• workspace
• Store processing results in a suitable database.

Processing of events needs great computational
power.
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Approach (IV) The process of creating awareness
Stage III Analysis

• Need for extracting complex knowledge from the
  database.
• Define consulting criteria.
• Send criteria and data to external statistics
  package.
• Obtain useful statistical results from the
  analysis.

External analysis offers the best existing
statistical package.
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Approach (V) The process of creating awareness
Stage IV Presentation

• Predefine an XML coding to represent ad hoc
  statistical measurements.
• Structure statistical results into XML output.
• Convert XML into desired presentation format.
• Present results to users.

Users receive knowledge as awareness information.
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Statement of the problem (I) Need for processing
of event information

• Real on-line environments with a large number of
  students and tutors that are geographically
  distributed.
• High degree of user-user and user-system
  interaction generates lots of event information.
• Constant provision of awareness to group
  participants in real-time.
• Essential to monitor, track and evaluate real,
  complex, long-term, collaborative problem-solving
  situations.

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Statement of the problem (II)Lack of
computational resources

• Need for processing of a huge amount of event
  information gathered in single log files.
• Essential to dispose of the processing results of
  group activity in real-time.
• Event information in log files should be
  partitioned in multiple log files according to
  particular needs.
• Event information must be constantly processed in
  an efficient manner during the processing stage.
• Lack of sufficient computational resources is the
  main obstacle to the constant processing of
  multiple data log files in real time.

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Solution (I)Redefining the processing stage

• Obtain event information from large log files.
• Structure the information according to
  particular needs.
• Create log files of different degrees of
  granularity.
• Process all log files at the same time.
• Store results in the database.

Need for the processing of all log files to be
parallelized.
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Solution (II)A Grid-based solution

• Grid technology provides broad access to massive
  information and computational resources.
• In this context, Grid computing paradigm
• overcomes the lack of computational resources to
  process a large amount of event information.
• allows processing of the log files taking
  advantage of the parallelism inherent in the
  distributed nature of Grid.
• provides load balance in the processing of log
  files of different granularity.
• Master-Worker paradigm using Planetlab platform,
  a Grid-based approach for processing log files.

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A Grid approach (I)Master-Worker paradigm

• Distinguishes two types of processors
• master performs the control and coordination
  tasks.
• workers perform most of the computational work.
• Advantages
• flexibility workers can be implemented in
  different ways.
• scalability workers can be easily added.
• separation of concerns master does coordination
  and workers do specific tasks.
• Target parallel applications with weak
  synchronization and reasonably large grain size.

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A Grid approach (II)A prototype for processing
log files (I)

• EventExtractor extracting information from BSCW
• converts event information into well-formatted
  data.
• stores the extraction results in a database.
• needs a lot of time to process sequentially.
• MW model appropriate in this context given that
• log files of different granularity are processed.
• workers are not synchronized between them.
• communication load between master and workers are
  low.
• Planetlab platform using a real Grid environment
• by installing the Globus Toolkit 3 Grid service
  container,
• and deploying the prototype on Planetlab.

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A Grid approach (III)A prototype for
processing log files (II)

• A minimal Grid implementation made up of
• the worker as a Grid service that does the main
  work by the next steps
• wraps the EventExtractor routine,
• publishes an interface that the master calls in
  order to dispatch a task,
• passes a string representation of the events to
  be processed, and
• returns a data structure containing performance
  information.
• After completion the task, the worker is put
  back into a queue of idle workers
• the master first obtains the event log file to be
  processed, the available workers, the task size
  to be dispatched to workers and the number of
  workers to use that put in a idle queue. Then
  enters the next loop
• reads a specific number of events from a event
  log file,
• calls a idle worker and sends it the events to be
  processed,
• The master exits the loop when all events in the
  current log file have
• been read and all tasks to be dispatched have
  been finalized.

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Experimental results (I)Preliminaries

• An ad hoc test battery was designed made up of
• exhaustive collection of log files
• from the spring term of a course with 140
  students arranged in 5-member groups and 2
  tutors.
• a selected sample of a few log files
• as a representative stratum of file size and
  event complexity.
• All test battery was processed by the
  EventExtractor on single-processor nodes of
  Planetlab
• involving usual configurations.
• with different work load.
• repeating the execution several times.

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Experimental results (II)Parallel processing
results

• The parallel processing results were obtained by
• running tests for different task sizes and number
  of workers
• observing how much close each set of workers is
  to achieve its theoretic maximum speed-up.

• Relative speed-up for 5-event task and different
  number of workers

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Experimental results (III)Analysis of the
results

• Apart from very small task sizes, the speed up
  observed was very close to the maximum
  achievable.
• The more workers used in our tests the closer to
  the maximum was the speed up achieved by the
  smallest tasks.
• Results were a little biased due to the
  homogeneous behaviour observed in Planetlab and
  they should be adjusted to the dynamic workload
  of a real Grid.
• Event complexity is key to take advantage of the
  benefits of a Grid environment as BSCW system
  generates a very few different types of events.

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Conclusions and future work

• We have first argued how the provision of
  continuous awareness to on-line learning teams
  can greatly improve the group activity.
• We have also shown that in the process of
  creating awareness there is a strong need for
  computational resources to process large amounts
  of information.
• According the results obtained in this study, the
  benefits of Grid enhances depending on the volume
  and complexity of event log files to be
  processed.
• As ongoing work, we plan to improve our prototype
  in terms of communication master-workers,
  fault-tolerance and dynamic discovery of idle
  workers.

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• Thank you !
• Questions?