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eLearning systems on examples




  Konstantin Filtschew @ Barcamp Mainz
                 29.11.2009
About me

   Name: Konstantin Filtschew

   Interested in:
       Innovation
       eLearning Systems
       Security in computer systems
       Software design
       New challenges
       ...
                                       2
Agenda

   Motivation
   Definition eLearning
   Examples
   Natural Language Processing (NLP)
   Mobile learn experience
   Conclusion



                                        3
Do we need ”eLearning”?

   Wissensgesellschaft

   General Knowledge
   Specific Knowdledge


   Transfer of knowledge to the next generation
       cp -r / remotebrain: # maybe in future

   We can't stop learning!

                                                   4
Definitions of eLearning
   Internet-enabled learning that encompasses training, education, just-in-
    time information, and communication.
    (http://www.eng.wayne.edu/page.php?id=1263)

   Any learning supported by digital means.
    (http://azelearning.org/glossary/3)

   E-learning (or electronic learning or eLearning) encompasses forms of
    technology-enhanced learning (TEL) or very specific types of TEL such
    as online or Web-based learning.
    (http://en.wikipedia.org/wiki/E-learning)


   eLearning kann verstanden werden als ein Lernprozess, der durch
    Informations- und Kommunikationstechnologie unterstützt wird
    (http://www.uni-hildesheim.de/de/9808.htm)
                                                                               5
Assistance through eLearning

   People must try to get better user experience
   People must do exercises for better knowledge
    and understanding

   Some examples
       Vocabulary
       History
       Math
       Foreign languages
                                                    6
Vocabulary Assistance

   Vocabulary trainer
       Does the user really know the word?

   Interactive trainer
       Enter vocabulary once
        (semi automatic possible)
       Shows vocabulary randomly
       Shows/checks correct answer
        instantly
       Can analyze time for answers
                                              7
       Vocabulary Frequency
History eLearning example (1)

   We shouldn't try to replace books and paper
   Add interactive media (sound/video)
   Ineractive questions to text
       Multiple choice
       Plain text answers (keyword NLP)


                                    ●
                                                                  +
                                        Who was Cristopher Columbus?

                                        In which year he started his travel?
              +                 +
                                    ●



                                    ●   Was it India he found on his first travel?
                                                                            8
                                    ●   ...
History eLearning example (2)

   We have some problems to solve first!

   Many different books used
   People are lazy to search for more information
       Need to reference the learners book, text and part

   Need help to create tasks (NLP can help)
       Questions and multiple choice generation

   Help: Google books scan project                          9
Math eLearning

   Some examples:
       Gehirntraining

   Math quizzes:
       X + 11 = 23
       126 / X = 42
       sqrt(169) = X
   Motivation:
       Points (Challenge)
       Success experience
                                 10
       Not the same exercises
Foreign Language

   Common difficulties in languages: Prepositions
        Both Parties had much to offer ________ a time of growth in the region.

                             (a) in    (b) at   (c) about


   Part of Speech Tagger or Parser
       Can recognize prepositions
   Corpora
       Help identify wrong prepositions:
                       Check whether this combination is really wrong
                       Common with left word of prepositions but not
                         with right and vice versa                                11
Interactive Tutor (1)




   http://141.225.42.246/AutoTutorDemo/
                                           12
Interactive Tutor (2)

   Natural Language Processing (NLP)
   Questions by tutor
   Answers in plain text
   Tutor helps to ...
       find answer
       Helps to remember all important points

   Problems:
       Still need to reference the lecture
                                                     13
       Not very ”human” in handling (no emotions)
Natural Language Processing

   NLP is a great help:
       Analyze Text and extract important information
       Can generate questions (almost automatic)
       Can analyze answers

   Need:
       Corpora: digital texts
       Part of Speech Tagger and Parser
       A lot of computer power for given tasks
       Human control for results                        14
NLP: Corpora

   We have a lot of digital text:
       Wikipedia (and other wikis)
       Blogs
       Google book scan

   Problems:
       Common Speech (Umgangssrpache)
       Errors
       (Internet) slang → :) :/ ;) cu
       Ambiguity (Ambiguitäten)         15
Part of Speech Tagger and Parser

   Part of Speech (POS) Tagger (Wortart Tagger)
       Analyzes only words
       Not so precise (about 80-90%)
       Faster than parser


   Parser
       Additionally to POS: sentence structure
       More precise (up to 96%)
       Sentence tree (word relations)
                                                  16
Ambiguity

   http://de.wikipedia.org/wiki/Mehrdeutigkeit




                                                  17
Sentence Tree




From Phineas Q. Phlogiston, “Cartoon Theories of Linguistics, Part ж—The Trouble with NLP“,
Speculative                                                                            18
Grammarian, CLIII(4), March 2008
Human control

   Let people learn errors is a very bad learning
    experience
   Wrong answers can be still right
   Computer can't decide about uncommon tasks /
    questions / answers

   Advantage:
       Automatic generation of tasks
       Teacher has only to check the
        written tasks                                19
Digital Books / Newspapers

   Add interactive tasks to common media
   Digital Books:
       We can add additional information (Video/Audio)
       Add exercises and quizzes

   Digital Newspapers:
       Schools can use for lessons (teacher selects)
       Teacher can create semi automatic tasks
       Advantage for newspapers: children learn to read
        newspapers                                         20
Mobile learn experience (1)

   We have:
       Powerful mobile phones: IPhone / Android / …
       Book/Newspaper readers
        (not yet open for extensions)


   We have to travel
       Home → Work → Home
       Business travels
       Time slots for education
                                                       21
Mobile learn experience (2)

   Busy people use every free minute

   Maybe you can't work, but you can learn

   Allready in use as eLearning:
       Podcasts
       Video and audio tutorials
       Already filtered information
                   (Read it later add-on)
                                              22
Conclusion

   We have a lot to learn
   We have to use our free time slots
   We allready use eLearning
   eLearning is at the very beginning

   Politics say: Wissensgesellschaft



                                         23
Thank you for your attention

   Questions?




   konstantin@filtschew.de
   http://konstantin.filtschew.de/blog/
   http://twitter.com/Fa11enAngel
                                           24
Sources
   http://upload.wikimedia.org/wikipedia/commons/6/6e/Latin_dictionary.jpg (GPL) //Books

   http://media.photobucket.com/image/ship/MODELSHIPCONSTRUCTION/17Th%20Century%20Man-of-War/NewBritishShip.jpg
    //Ship

   http://en.wikipedia.org/wiki/File:Ridolfo_Ghirlandaio_Columbus.jpg // Christopher Columbus

   http://web.airgamer.de/fileadmin/airgamer/images/spiele/01-gehirntraining/ss_gehirntraining_01.png //Gehirntraining

   http://upload.wikimedia.org/wikipedia/commons/3/38/Gregor_Reisch%2C_Margarita_Philosophica%2C_1508_%281230x1615%29.png
     // Gregor Reisch, Margarita Philosophica

   http://openclipart.org/people/StefanvonHalenbach/StefanvonHalenbach_Teacher_L_mpel.png // Teacher

   From Phineas Q. Phlogiston, “Cartoon Theories of Linguistics, Part ж—The Trouble with NLP“, Speculative Grammarian,
    CLIII(4), March 2008 // Pretty little girl




                                                                                                                          25

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eLearning Systems on examples

  • 1. eLearning systems on examples Konstantin Filtschew @ Barcamp Mainz 29.11.2009
  • 2. About me  Name: Konstantin Filtschew  Interested in:  Innovation  eLearning Systems  Security in computer systems  Software design  New challenges  ... 2
  • 3. Agenda  Motivation  Definition eLearning  Examples  Natural Language Processing (NLP)  Mobile learn experience  Conclusion 3
  • 4. Do we need ”eLearning”?  Wissensgesellschaft  General Knowledge  Specific Knowdledge  Transfer of knowledge to the next generation  cp -r / remotebrain: # maybe in future  We can't stop learning! 4
  • 5. Definitions of eLearning  Internet-enabled learning that encompasses training, education, just-in- time information, and communication. (http://www.eng.wayne.edu/page.php?id=1263)  Any learning supported by digital means. (http://azelearning.org/glossary/3)  E-learning (or electronic learning or eLearning) encompasses forms of technology-enhanced learning (TEL) or very specific types of TEL such as online or Web-based learning. (http://en.wikipedia.org/wiki/E-learning)  eLearning kann verstanden werden als ein Lernprozess, der durch Informations- und Kommunikationstechnologie unterstützt wird (http://www.uni-hildesheim.de/de/9808.htm) 5
  • 6. Assistance through eLearning  People must try to get better user experience  People must do exercises for better knowledge and understanding  Some examples  Vocabulary  History  Math  Foreign languages 6
  • 7. Vocabulary Assistance  Vocabulary trainer  Does the user really know the word?  Interactive trainer  Enter vocabulary once (semi automatic possible)  Shows vocabulary randomly  Shows/checks correct answer instantly  Can analyze time for answers 7  Vocabulary Frequency
  • 8. History eLearning example (1)  We shouldn't try to replace books and paper  Add interactive media (sound/video)  Ineractive questions to text  Multiple choice  Plain text answers (keyword NLP) ● + Who was Cristopher Columbus? In which year he started his travel? + + ● ● Was it India he found on his first travel? 8 ● ...
  • 9. History eLearning example (2)  We have some problems to solve first!  Many different books used  People are lazy to search for more information  Need to reference the learners book, text and part  Need help to create tasks (NLP can help)  Questions and multiple choice generation  Help: Google books scan project 9
  • 10. Math eLearning  Some examples:  Gehirntraining  Math quizzes:  X + 11 = 23  126 / X = 42  sqrt(169) = X  Motivation:  Points (Challenge)  Success experience 10  Not the same exercises
  • 11. Foreign Language  Common difficulties in languages: Prepositions Both Parties had much to offer ________ a time of growth in the region. (a) in (b) at (c) about  Part of Speech Tagger or Parser  Can recognize prepositions  Corpora  Help identify wrong prepositions:  Check whether this combination is really wrong  Common with left word of prepositions but not with right and vice versa 11
  • 12. Interactive Tutor (1)  http://141.225.42.246/AutoTutorDemo/ 12
  • 13. Interactive Tutor (2)  Natural Language Processing (NLP)  Questions by tutor  Answers in plain text  Tutor helps to ...  find answer  Helps to remember all important points  Problems:  Still need to reference the lecture 13  Not very ”human” in handling (no emotions)
  • 14. Natural Language Processing  NLP is a great help:  Analyze Text and extract important information  Can generate questions (almost automatic)  Can analyze answers  Need:  Corpora: digital texts  Part of Speech Tagger and Parser  A lot of computer power for given tasks  Human control for results 14
  • 15. NLP: Corpora  We have a lot of digital text:  Wikipedia (and other wikis)  Blogs  Google book scan  Problems:  Common Speech (Umgangssrpache)  Errors  (Internet) slang → :) :/ ;) cu  Ambiguity (Ambiguitäten) 15
  • 16. Part of Speech Tagger and Parser  Part of Speech (POS) Tagger (Wortart Tagger)  Analyzes only words  Not so precise (about 80-90%)  Faster than parser  Parser  Additionally to POS: sentence structure  More precise (up to 96%)  Sentence tree (word relations) 16
  • 17. Ambiguity  http://de.wikipedia.org/wiki/Mehrdeutigkeit 17
  • 18. Sentence Tree From Phineas Q. Phlogiston, “Cartoon Theories of Linguistics, Part ж—The Trouble with NLP“, Speculative 18 Grammarian, CLIII(4), March 2008
  • 19. Human control  Let people learn errors is a very bad learning experience  Wrong answers can be still right  Computer can't decide about uncommon tasks / questions / answers  Advantage:  Automatic generation of tasks  Teacher has only to check the written tasks 19
  • 20. Digital Books / Newspapers  Add interactive tasks to common media  Digital Books:  We can add additional information (Video/Audio)  Add exercises and quizzes  Digital Newspapers:  Schools can use for lessons (teacher selects)  Teacher can create semi automatic tasks  Advantage for newspapers: children learn to read newspapers 20
  • 21. Mobile learn experience (1)  We have:  Powerful mobile phones: IPhone / Android / …  Book/Newspaper readers (not yet open for extensions)  We have to travel  Home → Work → Home  Business travels  Time slots for education 21
  • 22. Mobile learn experience (2)  Busy people use every free minute  Maybe you can't work, but you can learn  Allready in use as eLearning:  Podcasts  Video and audio tutorials  Already filtered information  (Read it later add-on) 22
  • 23. Conclusion  We have a lot to learn  We have to use our free time slots  We allready use eLearning  eLearning is at the very beginning  Politics say: Wissensgesellschaft 23
  • 24. Thank you for your attention  Questions?  konstantin@filtschew.de  http://konstantin.filtschew.de/blog/  http://twitter.com/Fa11enAngel 24
  • 25. Sources  http://upload.wikimedia.org/wikipedia/commons/6/6e/Latin_dictionary.jpg (GPL) //Books  http://media.photobucket.com/image/ship/MODELSHIPCONSTRUCTION/17Th%20Century%20Man-of-War/NewBritishShip.jpg //Ship  http://en.wikipedia.org/wiki/File:Ridolfo_Ghirlandaio_Columbus.jpg // Christopher Columbus  http://web.airgamer.de/fileadmin/airgamer/images/spiele/01-gehirntraining/ss_gehirntraining_01.png //Gehirntraining  http://upload.wikimedia.org/wikipedia/commons/3/38/Gregor_Reisch%2C_Margarita_Philosophica%2C_1508_%281230x1615%29.png // Gregor Reisch, Margarita Philosophica  http://openclipart.org/people/StefanvonHalenbach/StefanvonHalenbach_Teacher_L_mpel.png // Teacher  From Phineas Q. Phlogiston, “Cartoon Theories of Linguistics, Part ж—The Trouble with NLP“, Speculative Grammarian, CLIII(4), March 2008 // Pretty little girl 25