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Computer-Assisted Learning Based on Cumulative Vocabularies, Conceptual Networks and Wikipedia Linkage Aalto Un Iversity

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Computer-Assisted Learning Based on Cumulative Vocabularies, Conceptual Networks and Wikipedia Linkage Aalto Un Iversity Departm en t of Com pu ter Scien ce Aa lto- Lauri Lahti Lahti Lauri In this doctoral dissertation Lauri Lahti proposes new methods and frameworks for DD 48 Computer-Assisted Learning computer-assisted learning relying on / knowledge structures inspired by the 2015 processes and structure of Wikipedia online and Wikipedia Linkage Conceptual Networks Vocabularies, Computer-Assisted Learning Based on Cumulative Based on Cumulative encyclopedia, supplied with experimental results. Complementing approaches include lists of concepts and conceptual Vocabularies, Conceptual r ela ti on s hi p s , colla b or a tor r oles , g en er a ti on of con cep t m a p s f r om the hy p er li n k n etwor k Networks and Wikipedia of Wikipedia, parallel rankings based on the statistics of the articles, branching structures and temporal versions of the Linkage articles. Approaches extend to wiki environments for editing concept maps, covering the perspectives of the learner, the context and the objective, exploring the Lauri Lahti shortest hyperlink chains between corresponding Wikipedia articles and recommending routings with a tailored variation and repetition of spaced learning and visualizations. Cumulatively explored conceptual networks, recall effects and language ability levels are contrasted with a review about measures of human learning process and representation of knowledge. 9HSTFMG*agbgde+ 9HSTFMG*agbgde+ ISBN 978-952-60-6163-4 (printed) BUSINESS + ISBN 978-952-60-6164-1 (pdf) ECONOMY ISSN-L 1799-4934 ISSN 1799-4934 (printed) ART + ISSN 1799-4942 (pdf) DESIGN + ARCHITECTURE Aalto Un iversity Aalto University School of Science SCIENCE + Department of Computer Science TECHNOLOGY www.aalto.fi CROSSOVER DOCTORAL DOCTORAL DISSERTATIONS DISSERTATIONS Aa lto Un iver sity pu blica tion ser ies DOCTORAL DISSERTATIONS 48 /2015 Computer-Assisted Learning Based on Cumulative Vocabularies, Conceptual Networks and Wikipedia Linkage Lau ri Lahti A doctor a l disser ta tion com pleted for the degr ee of Doctor of Scien ce (Techn ology) to be defen ded, with the per m ission of the Aa lto Un iver sity School of Scien ce, a t a pu blic exa m in a tion held a t the lectu r e ha ll T2 of the Depa r tm en t of Com pu ter Scien ce on 10 Apr il 2015 a t n oon . Aalto Un iversity School of Scien ce Departm en t of Com pu ter Scien ce Su pervisin g professor Abstract Professor Jorma Tarhio, Aalto University School of Science, Finland Aalto Un iversity, P.O. B ox 11000, FI-00076 Aalto www.aalto.fi Prelim in ary exam in ers Au thor Professor Jari Multisilta, Tampere University of Technology, Finland La u r i La hti Associate Professor Mike Joy, University of Warwick, United Kingdom Name of the doctoral dissertation Oppon en t Associate Professor Piet Kommers, University of Twente, The Netherlands Pu blisher S chool of S ci en ce Un it Dep a r tm en t of C om p u ter S ci en ce Series A a lto Un i v er s i ty p u b li ca ti on s er i es DOCTORAL DISSERTATIONS 48/2 015 Field of research Man u script su bm itted 19 August 2014 Date of the defen ce 10 A p r i l 2 015 Perm ission to pu blish gran ted (date) 6 March 2015 Lan gu age English Mon ograph Article dissertation (su m m ary + origin al articles) Abstract In this doctoral dissertation we propose new methods and frameworks for computer-assisted learning based on self-designed and self-implemented software prototypes supplied with user testing. Motivated by previous research identifying possibly similar scale-free small-world properties in Wikipedia online encyclopedia, social networks and human brain networks, we suggest that collaboratively generated knowledge structures of Wikipedia can be used to support learning. After reviewing background of computer-assisted and collaborative network- based learning we introduce using lists of concepts and conceptual relationships generated by students and comparison through rankings. We propose supporting collaborator roles in a collaborative learning environment relying on text-based discussion chains illustrated cumulatively as concept maps. Next, we propose guided generation of concept maps from the hyperlink network of Wikipedia. Then, we propose generating personalized learning paths from Wikipedia by following hyperlinks between articles based on various rankings of the s ta ti s ti cs of the a r ti cles . W e ex ten d thi s to m a n a g e p a r a llel r a n k i n g li s ts , b r a n chi n g s tr u ctu r es and different temporal versions of Wikipedia articles. Next, we propose a wiki environment r ep r es en ti n g p ed a g og i c k n owled g e wi th a colla b or a ti v ely ed i ted collecti on of con cep t m a p s enabling to analyze maturing of knowledge and to define pedagogically motivated learning paths and educational games. Then, we propose three kinds of learning concept networks, r ep r es en ti n g the lea r n er 's k n owled g e, the lea r n i n g con tex t a n d the lea r n i n g ob j ecti v e, a n d letting the learner to explore them with ranking-based routings based on the shortest hyperlink chains between corresponding Wikipedia articles. We extend this by proposing pedagogic con cep tu a l n etwor k s g en er a ted b a s ed on the s hor tes t con n ecti n g p a ths i n the hy p er li n k Aa lto Un iver sity pu blica tion ser ies network of Wikipedia and traversing hyperlinks with a tailored variation and repetition based DOCTORAL DISSERTATIONS 48 /2015 on theory of spaced learning supplied with visualizations. Then, we propose cumulative conceptual networks based on the hyperlink network of Wikipedia connecting concepts of the © La u r i La hti vocabulary about the current learning topic and alternating the distribution of traversable hy p er li n k s letti n g the lea r n er to ex p lor e the s hor tes t p a ths b etween the con cep ts of the v oca b u la r y . W e m ea s u r ed lea r n i n g ef f ects f or r eca ll of s elected a n d s hown hy p er li n k ed ISB N 978 -952-60-6163 -4 (pr in ted) con cep ts a n d r eca ll f or s hown hy p er li n k ed con cep ts f or m i n g the s hor tes t p a ths . W e a ls o ISB N 978 -952-60-6164-1 (pdf) estimated conceptual networks for alternative language ability levels and contrasted them with ISSN-L 1799-493 4 a review about measures of human learning process and representation of knowledge. ISSN 1799-493 4 (pr in ted) ISSN 1799-4942 (pdf) http://u r n .fi/URN:ISB N:978 -952-60-6164-1 Keywords intelligent tutoring; adaptive hypermedia; Wikipedia; learning environment; language acquisition; associative network; concept map; wiki; spaced learning ISB N (prin ted) 978-952-60-6163-4 ISB N (pdf) 978-952-60-6164-1 Un igr a fia Oy ISSN-L 1799-4934 ISSN (prin ted) 1799-4934 ISSN (pdf) 1799-4942 Helsin ki 2015 Location of pu blisher Hels i n k i Location of prin tin g Hels i n k i Year 2 015 Fin la n d Pages 520 u rn http ://u r n .fi /UR N :IS B N :9 7 8 -9 5 2 -6 0-6 16 4 -1 Su pervisin g professor Abstract Aalto Un iversity, P.O. B ox 11000, FI-00076 Aalto www.aalto.fi Prelim in ary exam in ers Au thor La u r i La hti Name of the doctoral dissertation Computer-Assisted Learning Based on Cumulative Vocabularies, Conceptual Networks and Oppon en t Wikipedia Linkage Pu blisher S chool of S ci en ce Un it Dep a r tm en t of C om p u ter S ci en ce Series A a lto Un i v er s i ty p u b li ca ti on s er i es DOCTORAL DISSERTATIONS 48/2 015 Field of research Computer Science and Engineering Man u script su bm itted 19 August 2014 Date of the defen ce 10 A p r i l 2 015 Perm ission to pu blish gran ted (date) 6 March 2015 Lan gu age English Mon ograph Article dissertation (su m m ary + origin al articles) Abstract In this doctoral dissertation we propose new methods and frameworks for computer-assisted learning based on self-designed and self-implemented software prototypes supplied with user testing. Motivated by previous research identifying possibly similar scale-free small-world properties in Wikipedia online encyclopedia, social networks and human brain networks, we suggest that collaboratively generated knowledge structures of Wikipedia can be used to support learning. After reviewing background of computer-assisted and collaborative network- based learning we introduce using lists of concepts and conceptual relationships generated by students and comparison through rankings. We propose supporting collaborator roles in a collaborative learning environment relying on text-based discussion chains illustrated cumulatively as concept maps.
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