Jump to ContentJump to Main Navigation
Show Summary Details
More options …

International Journal of Applied Mathematics and Computer Science

Journal of University of Zielona Gora and Lubuskie Scientific Society

4 Issues per year


IMPACT FACTOR 2016: 1.420
5-year IMPACT FACTOR: 1.597

CiteScore 2016: 1.81

SCImago Journal Rank (SJR) 2016: 0.524
Source Normalized Impact per Paper (SNIP) 2016: 1.440

Mathematical Citation Quotient (MCQ) 2016: 0.08

Open Access
Online
ISSN
2083-8492
See all formats and pricing
More options …
Volume 25, Issue 2 (Jun 2015)

Issues

An application framework to systematically develop complex learning resources based on collaborative knowledge engineering

David Gañán
  • Corresponding author
  • Department of Computer Science, Multimedia, and Telecommunications Open University of Catalonia, Rambla Poblenou, 156, 08018, Barcelona, Spain
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Santi Caballé
  • Department of Computer Science, Multimedia, and Telecommunications Open University of Catalonia, Rambla Poblenou, 156, 08018, Barcelona, Spain
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jordi Conesa
  • Department of Computer Science, Multimedia, and Telecommunications Open University of Catalonia, Rambla Poblenou, 156, 08018, Barcelona, Spain
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Fatos Xhafa
  • Department of Languages and Informatic Systems Technical University of Catalonia, C/ Jordi Girona, 1–3, 08034, Barcelona, Spain
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-06-25 | DOI: https://doi.org/10.1515/amcs-2015-0028

Abstract

This contribution proposes software infrastructure to support new types of learning methodologies and resources based on collaborative knowledge engineering by means of an innovative application framework called the virtualized collaborative sessions framework (VCSF). The VCSF helps meet challenging collaborative knowledge engineering requirements in online learning, such as increasing group members’ learning performance during the on-line collaborative learning process. In turn, systematic application of the VCSF platform enriched with semantic knowledge engineering technologies enables e-learning developers to leverage successful collaborative learning experiences in a software reuse fashion while saving development time and effort. The framework is prototyped and successfully tested in real environments, thus showing the software reuse capability and the collaborative knowledge engineering benefits of the VCSF approach. The research reported in this paper was undertaken within the ALICE project funded through the European 7th Framework Program (FP7).

Keywords : software infrastructure; application framework; collaborative knowledge engineering; on-line collaborative learning; discussion forums; virtualization; collaborative sessions; collaborative complex learning resources

References

  • Abad, C.L. (2008). Learning through creating learning objects: Experiences with a class project in a distributed systems course, Proceedings of the 13th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE’08, Madrid, Spain, pp. 255-259, DOI: 10.1149/1384271.1384340.CrossrefGoogle Scholar

  • Abdullah, S. and Abbas, M. (2006). The effects of inquirybased computer simulation with cooperative learning on scientific thinking and conceptual understanding, Eurasia Journal of Mathematics, Science and Technology Education 4(4): 387-398.Google Scholar

  • Al-Khalifa, H.S. and Davis, H.C. (2006). The evolution of metadata from standards to semantics in e-learning applications, Proceedings of the 17th Conference on Hypertext and Hypermedia, HYPERTEXT’06, Odense, Denmark, pp. 69-72, DOI: 10.1145/1149941.1149956.Google Scholar

  • Alexander, M., Graybill, F.A. and Duane, C. (1974). Introduction to the Theory of Statistics, McGraw-Hill, New York, NY.Google Scholar

  • Babic, F., Wagner, J. and Paralic, J. (2008). The role of ontologies in collaborative systems, 6th International Symposium on Applied Machine Intelligence and Informatics, SAMI 2008, Herl’any, Slovakia, pp. 119-124.Google Scholar

  • Bao-Qing, G., Xiu-Fen, F. and Su-Xia, X. (2007). P2P distributed cooperative work model based on JXTA platform, in M. Xu, Y. Zhan, J. Cao and Y. Liu (Eds.), Advanced Parallel Processing Technologies, Lecture Notes in Computer Science, Vol. 4847, Springer, Berlin/Heidelberg, pp. 658-665.Google Scholar

  • Bentley, R., Horstmann, T. and Trevor, J. (1997). The world wide web as enabling technology for CSCW: The case of BSCW, Computer Supported Cooperative Work 6(2-3): 111-134.Google Scholar

  • Brase, J. (2005). Usage of Metadata, Ph.D. thesis, Universit¨at Hannover, Hannover.Google Scholar

  • Brooke, J. (1996). SUS: A quick and dirty usability scale, in P.W. Jordan, B. Weerdmeester, A. Thomas and I.L. Mclelland (Eds.), Usability Evaluation in Industry, Taylor and Francis, London.Google Scholar

  • Caballé, S., Jiménez, D.G., Dunwell, I., Pierri, A. and Daradoumis, T. (2012). CC-LO: Embedding interactivity, challenge and empowerment into collaborative learning sessions, Journal of Universal Computer Science 18(1): 25-43.Google Scholar

  • Caballé, S., Lapedriza, À ., Masip, D., Xhafa, F. and Abraham, A. (2009). Enabling automatic just-in-time evaluation of in-class discussions in on-line collaborative learning practices, Journal of Digital Information Management 7(5): 290-297.Google Scholar

  • Caballé, S., Mora, N., Feidakis, M., Ga˜nán, D., Conesa, J., Daradoumis, T. and Prieto, J. (2013). CC-LR: Providing interactive, challenging and attractive collaborative complex learning resources, Journal of Computer Assisted Learning 30(1): 51-67.Web of ScienceGoogle Scholar

  • Caballé, S. and Xhafa, F. (2010). CLPL: Providing software infrastructure for the systematic and effective construction of complex collaborative learning systems, Journal of Systems and Software 83(11): 2083-2097.Web of ScienceGoogle Scholar

  • Christie, M. and Jurado, R.G. (2009). Barriers to innovation in online pedagogy, European Journal of Engineering Education 34(3): 273-279.CrossrefGoogle Scholar

  • Conesa, J., Caballé, S., Ga˜nán, D. and Prieto, J. (2012). Exploiting the semantic web to represent information from on-line collaborative learning, International Journal of Computational Intelligence Systems 5(4): 653-667.CrossrefWeb of ScienceGoogle Scholar

  • Czarnecki, K. and Eisenecker, U.W. (2000). Generative Programming: Methods, Tools and Applications, Addison-Wesley, New York, NY.Google Scholar

  • Dillenbourg, P. (Ed.) (1999a). Collaborative Learning: Cognitive and Computational Approaches, Advances in Learning and Instruction Series, Elsevier Science Ltd, New York, NY.Google Scholar

  • Dillenbourg, P. (1999b). What do you mean by collaborative learning?, in P. Dillenbourg (Ed.) Collaborative Learning: Cognitive and Computational Approaches, Elsevier, Oxford, pp. 1-19.Google Scholar

  • Dodero, J.M., del Val, Á.M. and Torres, J. (2010). An extensible approach to visually editing adaptive learning activities and designs based on services, Journal of Visual Languages & Computing 21(6): 332-346.Web of ScienceGoogle Scholar

  • Dodero, J.M., Díaz, P., Aedo, I. and Cabezuelo, A.S. (2005).Integrating ontologies into the collaborative authoring of learning objects, Journal of Universal Computer Science 11(9): 1568-1578.Google Scholar

  • Dodero, J.M., Ruiz-Rube, I., Palomo-Duarte, M. and Cabot, J. (2012). Model-driven learning design, Journal of Research and Practice in Information Technology 44(3): 267-288.Google Scholar

  • Fayad, M.E., Schmidt, D.C. and Johnson, R.E. (1999). Building Application Frameworks: Object-oriented Foundations of Framework Design, John Wiley & Sons, Inc., Hoboken, NJ.Google Scholar

  • Feidakis, M., Daradoumis, T., Caballé, S. and Conesa, J. (2012).Design of an emotion aware e-learning system, International Journal of Knowledge and Learning 8(3): 219-238.Google Scholar

  • Fonseca, B., Paredes, H., Sousa, J.P., Martins, F.M. and Carrapatoso, E. (2009). Saga reloaded: Towards a generic platform for developing cooperative applications, 13th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2009), Santiago, Chile, pp. 331-337.Google Scholar

  • Ganán, D., Caballé, S. and Conesa, J. (2013). Towards software infrastructure for the systematic virtualization of collaborative learning sessions, 5th International Conference on Intelligent Networking and Collaborative Systems (INCoS), Xi’an, China, pp. 422-429.Google Scholar

  • Gamma, E., Helm, R., Johnson, R. and Vlissides, J. (1995). Design Patterns: Elements of Reusable Software Architecture, Addison-Wesley, Reading, MA.Google Scholar

  • Gomaa, H. (2005). Designing Software Product Lines with UML: From Use Cases to Pattern Based Software Architectures, Addison-Wesley, Reading, MA.Google Scholar

  • Goodsell, A.S., Maher, M., Tinto, V., Leigh Snith, B. and MacGregor, J. (1992). Collaborative Learning: A Sourcebook for Higher Education, Pennsylvania State University, University Park, PA.Google Scholar

  • Inaba, A., Supnithi, T., Ikeda, M., Mizoguchi, R. and Toyoda, J. (2000). An overview of learning goal ontology, Proceedings of the Workshop on Analysis and Modelling of Collaborative Learning Interactions/European Conference on Artificial Intelligence ECAI-2000, Berlin, Germany.Google Scholar

  • Kay, R.H. and Loverock, S. (2008). Assessing emotions related to learning new software: The computer emotion scale, Computers in Human Behavior 24(4): 1605-1623.CrossrefWeb of ScienceGoogle Scholar

  • Lukosch, S. and Sch¨ummer, T. (2006). Groupware development support with technology patterns, International Journal of Human-Computer Studies 64(7): 599-610.Google Scholar

  • Mora, N., Caballe, S., Daradoumis, T. and Ganan, D. (2012). Towards a multi-fold assessment approach to enrich the virtualization of collaborative learning, 6th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), Palermo, Italy, pp. 935-940.Google Scholar

  • Moscinska, K. and Rutkowski, J. (2011). Barriers to introduction of e-learning: A case study, 2011 IEEE Global Engineering Education Conference (EDUCON), Amman, Jordan, pp. 460-465.Google Scholar

  • Mosley, P. (2005). A taxonomy for learning object technology, Journal of Computing Sciences in Colleges 20(3): 204-216.Google Scholar

  • Penichet, V.M.R., Lozano, M.D., Gallud, J.A. and Tesoriero, R. (2010). Requirement-based approach for groupware environments design, Journal of Systems and Software 83(8): 1478-1488, DOI: 10.1016/j.jss.2010.03.029.Web of ScienceCrossrefGoogle Scholar

  • Petropoulakis, L. and Flood, F. (2007). Design and development of a general purpose collaborative environment, International Journal of Computer Applications in Technology 29(1): 2-10, DOI: 10.1504/IJCAT.2007.014055.CrossrefGoogle Scholar

  • Rius, A., Conesa, J., García-Barriocanal, E. and Sicília, M.-A. (2013). Specifying patterns of educational settings by means of ontologies, Journal of Universal Computer Science 19(3): 353-382.Google Scholar

  • Rodriguez, M., Conesa, J. and Sicilia, M. (2009). Clarifying the semantics of relationships between learning objects, in F. Sartori, M. Sicilia and N. Manouselis (Eds.), Metadata and Semantic Research, Communications in Computer and Information Science, Vol. 46, Springer, Berlin/Heidelberg, pp. 35-47.Google Scholar

  • Schmidt, D.C. (1995). Using design patterns to develop reusable object-oriented communication software, Communications of the ACM 38(10): 65-74.CrossrefGoogle Scholar

  • Stahl, G. (2006). Group Cognition: Computer Support for Building Collaborative Knowledge (Acting with Technology), MIT Press, Cambridge, MA.Google Scholar

  • Ullrich, C. (2005). The learning-resource-type is dead, long live the learning-resource-type, Learning Objects and Learning Designs 1(1): 7-15.Google Scholar

  • Wilson, R. (2004). The role of ontologies in teaching and learning, TechWatch Reports, TSW0402.Google Scholar

  • Zarraonandía, T., Dodero, J., Díaz, P. and Sarasa, A. (2004). Domain ontologies integration into the learning objects annotation process, Proceedings of the Workshop on Applications of Semantic Web Technologies for e-Learning, Maceió-Alagoas, Brazil, pp. 35-40.Google Scholar

  • Zyda, M. (2005). From visual simulation to virtual reality to games, Computer 38(9): 25-32. CrossrefGoogle Scholar

About the article

Received: 2013-12-25

Revised: 2014-07-01

Published Online: 2015-06-25

Published in Print: 2015-06-01


Citation Information: International Journal of Applied Mathematics and Computer Science, ISSN (Online) 2083-8492, DOI: https://doi.org/10.1515/amcs-2015-0028.

Export Citation

© by David Gañán. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

Comments (0)

Please log in or register to comment.
Log in