LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Gibbs, Graham R.
Languages: English
Types: Doctoral thesis
Subjects: H1
Over the past 20 years there have been rapid developments in IT to create software that supports both learning and qualitative research. This thesis examines the design and use of that software, and argues that the exploratory approach in both learning and analysis produces superior outcomes. As such, the exploratory approach is seen as one that is particularly well supported by the software. A range of learning software and objects is discussed: Correlation Explorer, coMentor, learning websites, reusable learning objects, open educational resources, and videos. These are successive attempts by myself, and others, to develop software and other objects that support high quality learning. They do this in a variety of ways: by creating learning tools\ud that promote exploration, by encouraging online collaboration and sharing, and by providing materials that can be used in a range of learning contexts. Some of the problems of their use are discussed, such as mistaken conceptions, and finding and adapting learning objects. In a parallel fashion, this thesis argues that the development of software to assist qualitative data analysis has supported a range of analytic approaches. By their very nature these tend to be exploratory – the thesis argues that the core of qualitative analysis involves exploration of the data. The new analytic tools the software offers afford especially good support to exploratory analyses. These tools include text searching, code hierarchies, code queries, and the use of charts and diagrams.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 2002 Qualitative Data Analysis: Explorations with NVivo. Buckingham: Open University Press. ISBN: 0-335-20084-2
    • Birks, M., & Mills, J. (2015). Grounded theory: A practical guide (Second ed.). London: Sage Publications.
    • Carroll, J. M. (1982) “The adventure of getting to know a computer” IEEE Comput. 15,11, 49-58.
    • Carroll, J.M. and Mack, R. L. (1984) “Learning to use a wordprocessor: by doing, by thinking and by knowing”. In J. Thomas & M. Schneider (Eds.) Human Factors in Computing systems. Norwood: Ablex.
    • Corbin, J. M., & Strauss, A. L. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory (Fourth ed.). Los Angeles: SAGE.
    • Freitas, S. d., & Neumann, T. (2009). The use of 'exploratory learning' for supporting immersive learning in virtual environments. Computers & Education, 52(2), 343- 352. doi:10.1016/j.compedu.2008.09.010
    • Gadamer, H-G., Barden, G., & Cumming, J. (1975). Truth and method. London: Sheed and Ward.
    • Gibson, J. J. (1986). The ecological approach to visual perception. London;Hillsdale, N.J;: Lawrence Erlbaum Associates.
    • Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. New York: Aldine de Gruyter.
    • Hall, C. J. (2003) 'Partnership lessons from the Climbié Inquiry', Conference: 'Partnership Working in Children's Services', York, Nuffield Institute of Health.
    • Ifenthaler, D., Isaias, P., Kinshuk, Sampson, D. G., & Spector, J. M. (2012). Technology supported cognition and exploratory learning. Educational Technology & Society, 15(1), 1.
    • Kahneman (2011) Thinking, Fast and Slow. Harmondsworth: Penguin.
    • Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, N.J;London;: Prentice-Hall.
    • MacMillan, K. (2005). More than just coding? Evaluating CAQDAS in a discourse analysis of new texts. FORUM: Qualitative Social Research, 6(3). Article 25. Retrieved from http://nbn-resolving.de/urn:nbn:de:0114-fqs0503257
    • Malone, T. W. (1982) “Heuristics for designing enjoyable user interfaces: Lessons from computer games”. In Proceedings of the Conference on Human Factors in Computing Systems. ACM, New York, 63-68
    • Marton, F. (1988) “Describing and improving learning”. In R.R. Schmeck (Ed.) Learning Strategies and Learning Styles. New York: Plenum.
    • Miles, M. B., & Huberman, A. M. (1984). Qualitative data analysis: A sourcebook of new methods. Beverly Hills: Sage Publications.
    • Parton, N. (2004) 'From Maria Colwell to Victoria Climbie: reflections on public inquiries into child abuse a generation apart', Child Abuse Review, 13, pp. 80-94
    • Ritchie, J., & Lewis, J. (2003). Qualitative research practice: A guide for social science students and researchers. London: SAGE.
    • Robson, C (1993) Real World Research: A Resource for Social Scientists and PractitionerResearchers. Oxford: Blackwell.
    • Rogoff, B, Matusov, E and White, C (1996) “Models of Teaching and Learning: Participation in a Community of Learners” in David R. Olson, D.R. (ed) The handbook of education
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

Share - Bookmark

Cite this article