A Conceptual Model of the Research Methodology Domain - With a Focus on Computing Fields of Study

Colin Pilkington, Laurette Pretorius

2015

Abstract

Recognising the need for the development of research capacity and changing learning paradigms that include online and collaborative approaches, an ontology of research methodology needs to be developed to allow for the shared creation of knowledge in this domain. An ontology engineering approach is followed in developing a conceptual model of the domain using UML, with a focus on studies in the computing disciplines. A research scheme that is made up of a philosophical world view, a research design, and research methods is proposed. Appropriate relations between these are identified, as well as attributes of the various concepts in the conceptual model. A focus group consisting of senior researchers in the field of computing was utilised to validate the model.

References

  1. Balian, E. S. (2011). The Graduate Research Guidebook: A Practical Approach to Doctoral/Masters Research. Silver Sky Publishing, Encinitas, CA, 4th edition.
  2. Bera, P., Krasnoperova, A., and Wand, Y. (2010). Using ontology languages for conceptual modeling. Journal of Database Management, 21(1):1-28.
  3. Berners-Lee, T., Hall, W., Hendler, J. A., O'Hara, K., Shadbolt, N., and Weitzner, D. J. (2006). A framework for web science. Foundations and Trends in Web Science, 1(1):1-130.
  4. Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The semantic web. Scientific American, 284(5):34-43.
  5. Biggam, J. (2011). Succeeding With Your Master's Dissertation: A Step-By-Step Handbook. Open University Press, Maidenhead, 2nd edition.
  6. Borgida, A. and Brachman, R. J. (2003). Conceptual modeling with description logics. In Baader, F., McGuinness, D. L., Nardi, D., and Patel-Schneider, P. F., editors, The Description Logic Handbook: Theory, Implementation, and Applications, chapter 10, pages 359-381. Cambridge University Press, Cambridge.
  7. Chatti, M., Jarke, M., and Frosch-Wilke, D. (2007). The future of e-learning: A shift to knowledge networking and social software. International Journal of Knowledge and Learning, 3(4/5):404-420.
  8. Clarke, R. J. (2005). Research models and methodologies. HDR Seminar Series, Faculty of Commerce, Spring Session.
  9. Clough, P. and Nutbrown, C. (2007). A Student's Guide to Methodology. Sage, London.
  10. Cope, B. and Kalantzis, M. (2011). Creating an interlanguage of the social web. In Cope, B., Kalantzis, M., and Magee, L., editors, Towards a Semantic Web: Connecting Knowledge in Academic Research, pages 371-427. Oxford: Chandos.
  11. Corcho, O., Fernández-L ópez, M., and Gómez-Pérez, A. (2003). Methodologies, tools and languages for building ontologies. Where is their meeting point? Data & Knowledge Engineering, 46(1):41-64.
  12. Creswell, J. W. (2014). Reseach Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE, Thousand Oaks, 4th edition.
  13. Crossouard, B. (2008). Developing alternative models of doctoral supervision with online formative assessment. Studies in Continuing Education, 30(1):51-67.
  14. Cuéllar, M., Delgado, M., and Pegalajar, M. (2011). Improving learning management through semantic web and social networks in e-learning environments. Expert Systems with Applications, 38(4):4181-4189.
  15. De Leenheer, P. and Christiaens, S. (2007). Mind the gap!: Transcending the tunnel view on ontology engineering. In Proceedings of the 2nd International Conference on the Pragmatic Web, pages 75-82. ACM.
  16. Devedzic, V. (2002). Understanding ontological engineering. Communications of the ACM, 45(4):136-144.
  17. Di Maio, P. (2011). 'Just enough' ontology engineering. In Proceedings of the International Conference on Web Intelligence, Mining and Semantics, pages 1-10. ACM.
  18. DiGiuseppe, N., Pouchard, L. C., and Noy, N. F. (2014). Sweet ontology coverage for earth system sciences. Earth Science Informatics, 7(4):249-264.
  19. Dzbor, M., Stutt, A., Motta, E., and Collins, T. (2007). Representations for semantic learning webs: Semantic web technology in learning support. Journal of Computer Assisted Learning, 23(1):69-82.
  20. Ebersohn, L. (2011). Postgraduate supervision. Workshop presented at the University of South Africa, 9 July 2011.
  21. Engebretson, K., Smith, K., McLaughlin, D., Seibold, C., Terrett, G., and Ryan, E. (2008). The changing reality of research education in Australia and implications for supervision: A review of the literature. Teaching in Higher Education, 13(1):1-15.
  22. Feigenbaum, L. (2013a). The many names for the Semantic Web, Semantic University, Cambridge Semantics. http://www.cambridgesemantics.com/semanticuniversity/many-names-for-the-semantic-web.
  23. Feigenbaum, L. (2013b). Semantic Web misconceptions, Semantic University, Cambridge Semantics. http://www.cambridgesemantics.com/semanticuniversity/semantic-web-misconceptions.
  24. Gonzalez, R. (2013). Introduction to the Semantic Web, Semantic University, Cambridge Semantics. http://www.cambridgesemantics.com/semanticuniversity/introduction-to-the-semantic-web
  25. Green Paper (2012). Green paper for post-school education and training. Department of Higher Education and Training, Republic of South Africa.
  26. Grix, J. (2010). The Foundations of Research. Palgrave, Houndmills, Basingstoke, 2nd edition.
  27. Guarino, N. (2005). Ontology-driven conceptual modelling. 9th East-European Conference on Advances in Databases and Information Systems (ADBIS'2005).
  28. Guizzardi, G., Herre, H., and Wagner, G. (2002). On the general ontological foundations of conceptual modeling. In Proceedings of 21st International Conference on Conceptual Modelling, ER 2002, LNCS 2503, pages 65-78, Tampere, Finland.
  29. Häkkinen, P. and Hämäläinen, R. (2012). Shared and personal learning spaces: Challenges for pedagogical design. Internet and Higher Education, 15:231-236.
  30. Hammond, M. and Wellington, J. (2013). Research Methods: The Key Concepts. Routledge, Abingdon.
  31. Hennink, M. M. (2014). Focus Group Discussions. Series in Understanding Qualitative Research. Oxford.
  32. Hofstee, E. (2006). EPE, Sandton.
  33. Johnson, L., Adams Becker, S., Estrada, V., and Freeman, A. (2014). NMC Horizon Report: 2014 Higher Education Edition. Technical report, The New Media Consortium, Austin, Texas.
  34. Keet, C. M. and Artale, A. (2008). Representing and reasoning over a taxonomy of part-whole relations. Applied Ontology, 3(1):91-110.
  35. Keet, C. M., Khan, M. T., and Ghidini, C. (2013). Ontology authoring with FORZA. In Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pages 569-578. ACM.
  36. Kothari, C. R. (1985). Research Methodology: Methods and Techniques. Wiley Eastern, New Delhi.
  37. Krueger, R. E. and Casey, M. A. (2009). Focus Groups. A Practical Guide for Applied Research. Sage, Thousand Oaks, 4th edition.
  38. Limpens, F., Gandon, F., and Buffa, M. (2008). Bridging ontologies and folksonomies to leverage knowledge sharing on the social web: A brief survey. In 23rd IEEE/ACM International Conference on Automated Software Engineering-Workshops, 2008, pages 13-18. IEEE.
  39. Motik, B., Maedche, A., and Volz, R. (2002). A conceptual modeling approach for semantics-driven enterprise applications. In On the Move to Meaningful Internet Systems 2002: CoopIS, DOA, and ODBASE, LNCS 2519, pages 1082-1099.
  40. Mouton, J. (2001). How to Succeed in your Master's and Doctoral Studies: A South African Guide and Resource Book. Van Schaik, Pretoria.
  41. Naeve, A. (2005). The human semantic web shifting from knowledge push to knowledge pull. International Journal on Semantic Web and Information Systems, 1(3):1-30.
  42. Nagypál, G. (2007). Ontology development: Methodologies for ontology engineering. In Studer, R., Grimm, S., and Abecker, A., editors, Semantic Web Services: Concepts, Technologies and Applications, chapter 4, pages 107-134. Springer, Berlin.
  43. Noy, N. F. and McGuinness, D. L. (2001). Ontology development 101: A guide to creating your first ontology. Technical report, Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI2001-0880.
  44. Oates, B. J. (2006). Researching Information Systems and Computing. Sage, London.
  45. Olivier, M. S. (1999). Information Systems Research: A Practical Guide. Published by author.
  46. Partridge, C., Gonzalez-Perez, C., and Henderson-Sellers, B. (2013). Are conceptual models concept models? In Proceedings of ER 2013, Lecture Notes in Computer Science 8217, pages 96-105.
  47. Remenyi, D. and Money, A. (2004). Research Supervision for Suprevisors and their Students. Academic Publishing International, Reading.
  48. Sim, I., Tu, S. W., Carini, S., Lehmann, H. P., Pollock, B. H., Peleg, M., and Wittkowski, K. M. (2014). The ontology of clinical research (OCRe): An informatics foundation for the science of clinical research. Journal of Biomedical Informatics, 52:78-91.
  49. Stewart, D. W., Shamdasani, P. N., and Rook, D. W. (2007). Focus Groups. Sage, Thousand Oaks.
  50. Tremblay, M. C., Hevner, A. R., and Berndt, D. J. (2010). Focus groups for artifact refinement and evaluation in design research. Communications of the Association for Information Systems, 26(Article 27):599-618.
  51. Wahyuni, D. (2012). The research design maze: Understanding paradigms, cases, methods and methodologies. Journal of Applied Management Accounting Research, 10(1):69-80.
  52. Wand, Y., Storey, V. C., and Weber, R. (1999). An Ontological Analysis of the Relationship Construct in Conceptual Modeling. ACM Transactions on Database Systems, 24(4):494-528.
  53. Weber, R. (2003). Conceptual modelling and ontology: Possibilities and pitfalls. Journal of Database Management, 14(3):1-20.
  54. Welty, C. (2002). Ontology-driven conceptual modeling. Slide presentation at CAISE-02.
  55. Wen, L., Brayshaw, M., and Gordon, N. (2012). Personalized content provision for virtual learning environments via the semantic web. ITALICS Innovations in Teaching and Learning in Information and Computer Sciences, 11(1):14-26.
  56. Wisker, G. (2001). The Postgraduate Research Handbook. Succeed with your MA, MPhil, EdD and PhD, volume Palgrave Study Guides. Palgrave, Houndmills, Basingstoke.
  57. Wisker, G., Robinson, G., and Shacham, M. (2007). Postgraduate research success: Communities of practice involving cohorts, guardian supervisors and online communities. Innovations in Education and Teaching International, 44(3):301-320.
  58. Yew, K.-T., Ahmad, W., and Jaafar, J. (2011). A framework for designing postgraduate research supervision knowledge management systems. In National Postgraduate Conference (NPC), pages 1-6.
  59. Zedlitz, J. and Luttenberger, N. (2014). Conceptual modelling in UML and OWL-2. International Journal on Advances in Software, 7(1 and 2):182-196.
Download


Paper Citation


in Harvard Style

Pilkington C. and Pretorius L. (2015). A Conceptual Model of the Research Methodology Domain - With a Focus on Computing Fields of Study . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015) ISBN 978-989-758-158-8, pages 96-107. DOI: 10.5220/0005613100960107


in Bibtex Style

@conference{keod15,
author={Colin Pilkington and Laurette Pretorius},
title={A Conceptual Model of the Research Methodology Domain - With a Focus on Computing Fields of Study},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015)},
year={2015},
pages={96-107},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005613100960107},
isbn={978-989-758-158-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015)
TI - A Conceptual Model of the Research Methodology Domain - With a Focus on Computing Fields of Study
SN - 978-989-758-158-8
AU - Pilkington C.
AU - Pretorius L.
PY - 2015
SP - 96
EP - 107
DO - 10.5220/0005613100960107