Survival of the Fittest – Utilization of Natural selection Mechanisms for Improving PLE

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  • 1.Survival of the Fittest Utilization of Natural selection Mechanisms for Improving PLE
    • Behnam Taraghi,Christian Stickel, Martin Ebner

2. http://ple.tugraz.at Mashup of widgets 3. Darwins theory

  • - Survival of the fittest
  • - Selection, Variation
  • - Macro evolution
  • - Micro evolution

4. Selections

  • Evolution theory of natural selections:
    • - Reproduction rate
    • - Mortality
    • - Population size
    • - Environmental capacity
    • - Cycle of updates, replacements & new widgets
    • - # widgets
    • Max # widgets on UI & # users

Different probabilities for the survival are the base for theselection mechanism . 5. Selection Mechanisms* Stabilizing Selection : - Favorites the average. - Decrease of variability within the population.

  • Disruptive Selection :
  • Directed against the average.
  • Splits the population into new species.
  • Directed Selection :
  • Works against individuals on one side of distribution.

*Solbrig O.T. (1970). Principles and Methods of Plant Biosystematics. The Mac-Millan Company. Collier-Mac Millan Limited, London. *Solbrig O.T. & D.J Solbrig. (1979). Populationbiology and evolution. Addision-Wesley. Publ. Co. Reading Mass. 6. r/K Selection Theory* Tradeoff btw.quantity&qualityof offspring In long term K-strategy is superior. Quality succeeds in long run over quantity.

  • r-Strategy
  • Succeeds in unpredictable, unknown environments.
  • High reproduction rate short lifespan
  • K-Strategy
  • Succeeds in predictable, known environments.
  • Constant growth, ruled by population density & env. capacity
  • Usually close to the max. capacity
  • Slower adaptation longer lifespan

InPLEa mixed approach was applied. *Pianka E.R. (1970). On r and K selection. American naturalist 104, 592-597. *MacArthur, R. and Wilson, E.O. (1967). The Theory of Island Biography, Princeton University Press (2001 reprint). 7. Variations

  • Shift in genotypes or generic sequence
  • Mutation :
    • Random process aiming at generation of new alternatives
    • Ex. change in DNA structure
    • Continuously happening
  • Recombination :
    • Not random process
    • Combining & distributing genetic materials (DNA, RNA)

The Evolution never stops. InPLE : slight update of existing functionality or UI InPLE : combining code of different widgets to build new ones 8. Tracking module in PLE

  • Tracks users behavior on widgets
  • Deep retrieve of statistics data
    • Frequency of widgets usage
    • Features used in each widget
  • Realized via IWC
  • - App. 1000 users registered up to now.
  • - App. 30% active users
  • - Top 5 most used widgets out of 30:
  • - tugWidget, tccourses, tugllBlogs, mail, changeThemeColor
  • Top 5 most activated widgets:
    • weatherForcast, RSSReader, twitter, TUGLibrary, leoDictionary
  • weatherForcast & newsgroup are improved according to K-strategy

Most activated widgets are not necessarily most used ones 9. Conclusion & Future Work

  • Tracking module helps
    • To get knowledge about user behavior
    • To get user preferences
    • To categorize different user groups
    • Improve the PLE with variations & selections
  • Missing qualitative data
    • Qualitative rating system is needed in PLE
    • Small feedback questionnaire for each widget

10. SOCIAL LEARNING Computer and Information Services http://tugraz.at http:// elearning .tugraz.at Slides available at:http:// www.slideshare.net/behi_at b.taraghi(at)tugraz.at

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