On Recommending Web 2.0 Tools to Personalise Learning.

The paper aims to present research results on using Web 2.0 tools for learning personali- sation. In the work, personalised Web 2.0 tools selection method is presented. This method takes into account student's learning preferences for content and communication modes tailored to the learning activities with a view to help the learner to quickly and accurately find the right educa - tional tools, and to implement this method in prototype of knowledge-based recommender system. In the research, first of all, personalised e-learning technological peculiarities i.e. recommender systems applications for learning personalisation and those systems components were investi- gated. After that, selection methods for Web 2.0 tools suitable for implementing learning activities were analysed. The novel method of integrating Web 2.0 tools into personalised learning activities according to students learning styles was created, and prototype of the recommender system that implements the method proposed was developed. Finally, the expert evaluation of the developed system prototype that implements the method proposed was performed.

[1]  James N. Druckman,et al.  The Implications of Framing Effects for Citizen Competence , 2001 .

[2]  M. McDaniel,et al.  Learning Styles , 2008, Psychological science in the public interest : a journal of the American Psychological Society.

[3]  Hei-Chia Wang,et al.  Personalized e-learning environment for bioinformatics , 2013, Interact. Learn. Environ..

[4]  P. Converse The Nature of Belief Systems in Mass Publics , 2004 .

[5]  Harald Reiterer,et al.  Software evaluation using the 9241 evaluator , 1997, Behav. Inf. Technol..

[6]  R. Guimerà,et al.  Complex Systems View of Educational Policy Research , 2010, Science.

[7]  Márta Turcsányi-Szabó,et al.  Towards a personalised, learning style based collaborative blended learning model with individual assessment , 2012, Informatics Educ..

[8]  U. Wilensky,et al.  Thinking Like a Wolf, a Sheep, or a Firefly: Learning Biology Through Constructing and Testing Computational Theories—An Embodied Modeling Approach , 2006 .

[9]  M. Resnick,et al.  Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World , 1999 .

[10]  J Michael Vollers,et al.  Teaching and Learning Styles , 2008, International anesthesiology clinics.

[11]  Vincent Wade,et al.  Towards a Standards-based Approach to e-Learning Personalization using Reusable Learning Objects , 2002 .

[12]  Eugenijus Kurilovas,et al.  Expert centred vs learner centred approach for evaluating quality and reusability of learning objects , 2014, Comput. Hum. Behav..

[13]  Olena Kupenko,et al.  Approach to Dynamic Assembling of Individualized Learning Paths , 2012, Informatics Educ..

[14]  Uri Wilensky,et al.  Crossing Levels and Representations: The Connected Chemistry (CC1) Curriculum , 2009 .

[15]  Mike Stieff,et al.  Connected Chemistry—Incorporating Interactive Simulations into the Chemistry Classroom , 2003 .

[16]  Learning, Understanding, and Acceptance: The Case of Evolution , 2008 .

[17]  Jiyan Wu,et al.  Semantic Learning Service Personalized , 2012, Int. J. Comput. Intell. Syst..

[18]  F. Coffield Learning styles and pedagogy in post-16 learning: a systematic and critical review , 2004 .

[19]  Sarah Cohen,et al.  Changing Global Warming Beliefs with Scientific Information: Knowledge, Attitudes, and RTMD (Reinforced Theistic Manifest Destiny Theory) , 2012, CogSci.

[20]  Bhaskar Kapoor,et al.  A Comparative Study of Ontology building Tools in Semantic Web Applications , 2010 .

[21]  Federica Cena,et al.  The Role of Ontologies in Context-Aware Recommender Systems , 2006, 7th International Conference on Mobile Data Management (MDM'06).

[22]  Lior Rokach,et al.  Recommender Systems Handbook , 2010 .

[23]  Elvira Popescu Diagnosing Students' Learning Style in an Educational Hypermedia System , 2009 .

[24]  Abdellah Bennane,et al.  Adaptive Educational Software by Applying Reinforcement Learning , 2013, Informatics Educ..

[25]  Alessandro Micarelli,et al.  User Profiles for Personalized Information Access , 2007, The Adaptive Web.

[26]  湯淺 太一,et al.  20世紀の名著名論:Seymour Papert: Mindstorms:Children Computers and Powerful Ideas Basic Books New York 1980 , 2005 .

[27]  Joshua M. Epstein Agent-based computational models and generative social science , 1999 .

[28]  Eugenijus Kurilovas,et al.  New MCEQLS TFN method for evaluating quality and reusability of learning objects , 2013 .

[29]  Steffen Staab,et al.  On-To-Knowledge Methodology (OTKM) , 2004, Handbook on Ontologies.

[30]  Dennis McLeod,et al.  Ontology Development Tools for Ontology- Based Knowledge Management , 2006 .

[31]  Daryl Diamond,et al.  Digital Solidarity in Education: Promoting Equity, Diversity, and Academic Excellence through Innovative Instructional Programs , 2013 .

[32]  Rajendra M. Sonar,et al.  An Integrated Rule-Based and Case-Based Reasoning Approach for Selection of the Software Packages , 2009, ICISTM.

[33]  Lior Rokach,et al.  Introduction to Recommender Systems Handbook , 2011, Recommender Systems Handbook.

[34]  Asunción Gómez-Pérez,et al.  Building a chemical ontology using Methontology and the Ontology Design Environment , 1999, IEEE Intell. Syst..

[35]  Pratim Sengupta,et al.  Learning Electricity with NIELS: Thinking with Electrons and Thinking in Levels , 2009, Int. J. Comput. Math. Learn..

[36]  Yannis A. Dimitriadis,et al.  Ontoolcole: Supporting Educators in the Semantic Search of CSCL Tools , 2008, J. Univers. Comput. Sci..

[37]  Andrew Shtulman,et al.  Cognitive Constraints on the Understanding and Acceptance of Evolution , 2011 .

[38]  P. Converse The nature of belief systems in mass publics (1964) , 2006, The Nature of Belief Systems Reconsidered.

[39]  K. Ecclestone,et al.  Learning styles and pedagogy in post-16 learning , 2004 .

[40]  U. Wilensky,et al.  Social and Task Interdependencies in the Street-Level Implementation of Innovation , 2015 .

[41]  B. Bloom,et al.  Taxonomy of Educational Objectives. Handbook I: Cognitive Domain , 1966 .

[42]  Boris Motik,et al.  Query Answering for OWL-DL with Rules , 2004, SEMWEB.

[43]  Joshua M. Epstein,et al.  Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity) , 2007 .

[44]  Stuart E. Middleton,et al.  Ontology-based Recommender Systems , 2004, Handbook on Ontologies.

[45]  John G. Hedberg,et al.  A framework for Web 2.0 learning design , 2010 .

[46]  Wahidah Husain,et al.  A Framework of a Personalized Location-based Traveler Recommendation System in Mobile Application , 2012 .

[47]  Lillian Buus,et al.  Facilitating Adoption of Web Tools for Problem and Project Based Learning Activities , 2012 .

[48]  Seymour Papert,et al.  Mindstorms: Children, Computers, and Powerful Ideas , 1981 .

[49]  M. Freeden What Should the ‘Political’ in Political Theory Explore?* , 2005 .

[50]  Sarah K. Brem,et al.  Evolution challenges : integrating research and practice in teaching and learning about evolution , 2012 .

[51]  Gráinne Conole,et al.  A learning design toolkit to create pedagogically effective learning activities. (in Special Issue on Advances in Learning Design) , 2005 .

[52]  Steffen Staab,et al.  Handbook on Ontologies (International Handbooks on Information Systems) , 2004 .

[53]  Federico Liévano Martínez,et al.  Agent-based simulation approach to urban dynamics modeling , 2012, Rev. Avances en Sistemas Informática.

[54]  Jeannette A. Colyvas,et al.  Moving from an Exception to a Rule:Analyzing Mechanisms in Emergence-based Institutionalization , 2013 .

[55]  U. Wilensky,et al.  Complex Systems in Education: Scientific and Educational Importance and Implications for the Learning Sciences , 2006 .

[56]  Luciano Vieira Lima,et al.  A Stochastic Approach for Automatic and Dynamic Modeling of Students' Learning Styles in Adaptive Educational Systems , 2012, Informatics Educ..

[57]  Yarden Katz,et al.  Pellet: A practical OWL-DL reasoner , 2007, J. Web Semant..

[58]  Zoran Budimac,et al.  Ontology-based architecture with recommendation strategy in java tutoring system , 2013, Comput. Sci. Inf. Syst..

[59]  Zoran Budimac,et al.  Protus 2.0: Ontology-based semantic recommendation in programming tutoring system , 2012, Expert Syst. Appl..

[60]  Joshua M. Epstein,et al.  Growing Artificial Societies: Social Science from the Bottom Up , 1996 .

[61]  Louise Starkey,et al.  Evaluating learning in the 21st century: a digital age learning matrix , 2011 .

[62]  Ian Horrocks,et al.  From SHIQ and RDF to OWL: the making of a Web Ontology Language , 2003, J. Web Semant..

[63]  Peter Brusilovsky Methods and Techniques of Adaptive Hypermedia , 1996 .

[64]  Robert C. Luskin Explaining political sophistication , 1990 .

[65]  Michael Gruninger,et al.  Methodology for the Design and Evaluation of Ontologies , 1995, IJCAI 1995.

[66]  Robert C. Luskin Measuring Political Sophistication , 1987 .