Enhancing Online Discussion Forums with a Topic-driven Navigational Paradigm - A Plugin for the Moodle Learning Management System

Damiano Distante, Luigi Cerulo, Aaron Visaggio, Marco Leone

Abstract

One of the most popular means of asynchronous communication and most rich repository of user generated information over the Internet is represented by online discussion forums. The capability of a forum to satisfy users’ needs as an information source is mainly determined by its richness in information, but also by the way its content (messages and message threads) is organized and made navigable and searchable. To ease content navigation and information search in online discussion forums we propose an approach that introduces in them a complementary navigation structure which enables searching and navigating forum contents by topic of discussion, thus enabling a topic-driven navigational paradigm. Discussion topics and hierarchical relations between them are extracted from the forum textual content with a semi-automatic process, by applying Information Retrieval techniques, specifically Topic Models and Formal Concept Analysis. Then, forum messages and discussion threads are associated to discussion topics on a similarity score basis. In this paper we present an implementation of our approach for the Moodle learning management system, opening to the application of the approach to several real e-learning contexts. We also show with a case study that the new topic-driven navigation structure improves information search tasks with respect to using Moodle standard full-text search.

References

  1. Baeza-Yates, R. A. and Ribeiro-Neto, B. (1999). Modern Information Retrieval. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.
  2. Bakalov, A., McCallum, A., Wallach, H. M., and Mimno, D. M. (2012). Topic models for taxonomies. In Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 7812, Washington, DC, USA, June 10-14, 2012, pages 237-240.
  3. Birkhoff, G. (1967). Lattice theory. In Colloquium Publications, volume 25. Amer. Math. Soc., 3. edition.
  4. Blei, D. M. (2011). Introduction to probabilistic topic models. Communications of the ACM.
  5. Castro, F., Nebot, A., and Mugica, F. (2007a). Extraction of logical rules to describe students' learning behavior. In Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2, WBED'07, pages 164-169, Anaheim, CA, USA. ACTA Press.
  6. Castro, F., Vellido, A., Nebot, A., and Mugica, F. (2007b). Applying data mining techniques to e-learning problems. In Jain, L., Tedman, R., and Tedman, D., editors, Evolution of Teaching and Learning Paradigms in Intelligent Environment, volume 62 of Studies in Computational Intelligence, pages 183-221. Springer Berlin Heidelberg.
  7. Cerulo, L. and Distante, D. (2013). Topic-driven semiautomatic reorganization of online discussion forums: A case study in an e-learning context. In Global Engineering Education Conference (EDUCON), 2013 IEEE, pages 303-310.
  8. Dicheva, D. and Dichev, C. (2006). Tm4l: Creating and browsing educational topic maps. British Journal of Educational Technology, 37(3):391-404.
  9. dos Santos Machado, L. and Becker, K. (2003). Distance education: A web usage mining case study for the evaluation of learning sites. In 2003 IEEE International Conference on Advanced Learning Technologies (ICALT 2003), 9-11 July 2003, Athens, Greece, pages 360-361. IEEE Computer Society.
  10. Ganter, B. and Wille, R. (1999). Formal Concept Analysis: Mathematical Foundations. Springer.
  11. Ghenname, M., Ajhoun, R., Gravier, C., and Subercaze, J. (2012). Combining the semantic and the social web for intelligent learning systems. In Global Engineering Education Conference (EDUCON), 2012 IEEE, pages 1 -6.
  12. Gruen, T. W., Osmonbekov, T., and Czaplewski, A. J. (2006). eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business Research, 59:449456.
  13. Hanna, M. (2004). Data Mining in the e-Learning Domain. Campus-Wide Information Systems, 21(1):29-34.
  14. Hogo, M. A. (2010). Evaluation of e-learning systems based on fuzzy clustering models and statistical tools. Expert Syst. Appl., 37(10):6891-6903.
  15. Hrastinski, S. (2008). What is online learner participation? a literature review. Computers & Education, 51(4):1755 - 1765.
  16. Jakobsone, A., Kulmane, V., and Cakula, S. (2012). Structurization of information for group work in an online environment. In Global Engineering Education Conference (EDUCON), 2012 IEEE, pages 1 -7.
  17. Li, Q., Wang, J., Chen, Y. P., and Lin, Z. (2010). User comments for news recommendation in forum-based social media. Information Sciences, 180:49294939.
  18. Martin, A. and Leon, C. (2012). An intelligent e-learning scenario for knowledge retrieval. In Global Engineering Education Conference (EDUCON), 2012 IEEE, pages 1 -6.
  19. Meila, M. (2003). Comparing clusterings by the variation of information. In Computational Learning Theory and Kernel Machines, 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, pages 173-187.
  20. Otterbacher, J. (2008). Searching for product experience attributes in online information sources. In Proceedings of the International Conference on Information Systems (ICIS 2008). Association for Information Systems.
  21. Romero, C., Ventura, S., and Bra, P. D. (2005). Knowledge discovery with genetic programming for providing feedback to courseware authors. User Modeling and User-Adapted Interaction, 14(5):425-464.
  22. Stefan, H. (2009). A theory of online learning as online participation. Computers & Education, 52(1):78-82.
  23. Sudau, F., Friede, T., Grabowski, J., Koschack, J., Makedonski, P., and Himmel, W. (2014). Sources of information and behavioral patterns in online health forums: qualitative study. Journal of medical Internet research, 16:e10.
  24. Sung Ho Ha, Sung Min Bae, S. C. P. (2000). Web mining for distance education.
  25. Tang, T. and McCalla, G. (2005). Smart Recommendation for an Evolving e-Learning System: Architecture and Experiment. International Journal on e-Learning, 4(1):105-129.
  26. Tsai, C.-J., Tseng, S.-S., and Lin, C.-Y. (2001). A twophase fuzzy mining and learning algorithm for adaptive learning environment. In Proceedings of the International Conference on Computational SciencePart II, ICCS 7801, pages 429-438, London, UK, UK. Springer-Verlag.
  27. Wallach, H. M., Mimno, D. M., and McCallum, A. (2009). Rethinking lda: Why priors matter. In Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009, pages 1973-1981.
  28. Yang, Q., Sun, J., Wang, J., and Jin, Z. (2010). Semantic web-based personalized recommendation system of courses knowledge research. In Proceedings of the 2010 International Conference on Intelligent Computing and Cognitive Informatics, ICICCI 7810, pages 214-217, Washington, DC, USA. IEEE Computer Society.
  29. Zaíane, O. R. (2002). Building a recommender agent for elearning systems. In Proceedings of the International Conference on Computers in Education, ICCE 7802, pages 55-, Washington, DC, USA. IEEE Computer Society.
  30. Zhang, K. and Peck, K. (2003). The effects of peercontrolled or moderated online collaboration on group problem solving and related attitudes. Canadian Journal of Learning and Technology / La revue canadienne de lapprentissage et de la technologie, 29(3).
Download


Paper Citation


in Harvard Style

Distante D., Cerulo L., Visaggio A. and Leone M. (2014). Enhancing Online Discussion Forums with a Topic-driven Navigational Paradigm - A Plugin for the Moodle Learning Management System . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 97-106. DOI: 10.5220/0005078600970106


in Bibtex Style

@conference{kdir14,
author={Damiano Distante and Luigi Cerulo and Aaron Visaggio and Marco Leone},
title={Enhancing Online Discussion Forums with a Topic-driven Navigational Paradigm - A Plugin for the Moodle Learning Management System},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},
year={2014},
pages={97-106},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005078600970106},
isbn={978-989-758-048-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - Enhancing Online Discussion Forums with a Topic-driven Navigational Paradigm - A Plugin for the Moodle Learning Management System
SN - 978-989-758-048-2
AU - Distante D.
AU - Cerulo L.
AU - Visaggio A.
AU - Leone M.
PY - 2014
SP - 97
EP - 106
DO - 10.5220/0005078600970106