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eLearming Systems on examples

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Almost every human must learn for success in their live and jobs. E-Learning is a way to support the hard learning and training process for people. I've shown some possible example in E-Learning systems and have shown some new ideas on Barcamp Mainz (http://www.barcampmainz.de/). Some Natural Language Processing (NLP) things were told too. In my opinion E-Learning will be the next big step in the Web for better user experience in learning.

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eLearming Systems on examples

  1. 1. eLearning systems on examples Konstantin Filtschew @ Barcamp Mainz 29.11.2009
  2. 2. About me  Name: Konstantin Filtschew  Interested in:  Innovation  eLearning Systems  Security in computer systems  Software design  New challenges  ... 2
  3. 3. Agenda  Motivation  Definition eLearning  Examples  Natural Language Processing (NLP)  Mobile learn experience  Conclusion 3
  4. 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. 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. 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. 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. 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. 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. 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. 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. 12. Interactive Tutor (1)  http://141.225.42.246/AutoTutorDemo/ 12
  13. 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. 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. 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. 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. 17. Ambiguity  http://de.wikipedia.org/wiki/Mehrdeutigkeit 17
  18. 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. 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. 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. 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. 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. 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. 24. Thank you for your attention  Questions?  konstantin@filtschew.de  http://konstantin.filtschew.de/blog/  http://twitter.com/Fa11enAngel 24
  25. 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

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