eLearning systems on examples

Konstantin Filtschew @ Barcamp Mainz29.11.2009

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About me

Name: Konstantin Filtschew

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

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Agenda

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

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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!

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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)

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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

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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 Vocabulary Frequency

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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)

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● Who was Cristopher Columbus?

● In which year he started his travel?

● Was it India he found on his first travel?

● ...

+ +

+

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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

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Math eLearning

Some examples: Gehirntraining

Math quizzes: X + 11 = 23 126 / X = 42 sqrt(169) = X

Motivation: Points (Challenge) Success experience Not the same exercises

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Foreign Language

Common difficulties in languages: Prepositions

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

Both Parties had much to offer ________ a time of growth in the region.

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

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Interactive Tutor (1)

http://141.225.42.246/AutoTutorDemo/

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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 Not very ”human” in handling (no emotions)

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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

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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)

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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)

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Ambiguity

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

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Sentence Tree

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

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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

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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

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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

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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)

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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

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Thank you for your attention

Questions?

konstantin@filtschew.de http://konstantin.filtschew.de/blog/ http://twitter.com/Fa11enAngel

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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