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Education and Information Technologies

, Volume 20, Issue 1, pp 21–36 | Cite as

Finding potential problems in the thesis process in higher education: Analysis of e-mails to develop a support system

  • Naghmeh Aghaee
Article

Abstract

Autonomous learning hype has created much speculation in educational systems regarding how to develop the learning process. Final project (thesis) in Bachelor’s and Master’s levels is a significant part of study for students in higher education. However, there are some problems, which lead students not managing to do or finish their thesis. As a part of a solution to these problems, the Department of Computer and Systems Sciences (DSV) at Stockholm University, Sweden, has established an information and communication platform, called SciPro. The system was initiated in 2011 to support students and supervisors during the thesis process courses. This study contributes by exploring problems that learners have faced during the final project courses and analyzing discussed issues in the emails, sent to the SciPro support group, ThesisSupport. A random sample of one hundred emails has been analyzed with the help of a content analysis tool, in order to develop the categories, which cover the discussed issues. The result of the study shows six exhaustive and mutually exclusive categories of problems: 1) Thesis initiation (26 %), 2) Info-mail (4.7 %), 3) Technical issues (17.1 %), 4) Exemption (18.7 %), 5) Supervision (17.1 %), 6) Final seminar (16.4 %). Consequently, based on the significance of the categories, two groups of strategic suggestions are developed: 1) developing communications and 2) developing instructions. These strategies intend to enhance support for the autonomous learning process for the thesis courses in higher education.

Keywords

SciPro Idea-bank Thesis process Learning process Autonomous learning Communication platform 

Notes

Acknowledgments

I would like to express my appreciation to the DSV thesis coordinator, Associate Professor Henrik Hansson for his great supervision, guidelines and constructive comments, and to Associate Professor Matti Tedre for his guidelines for the methodology section of the study. In addition, my appreciation also goes to the SciPro ThesisSupport, Ulf Larsson and David Hallberg for their supports for the data collection. Moreover, since this paper had been sent to the IRIS conference 2012, I am grateful to assistant professor Christina Keller for her valuable comments, besides the workshops’ group members, especially the leader of the group, Professor Lars Svensson from University West. Special thanks to William Jobe and Aron Henriksson for the language improvements. And finally thanks to the students and faculty at the department of Computer and System Sciences (DSV), Stockholm University, who provided support to develop this paper.

References

  1. Aghaee, N., & Hansson, H. (2013). Peer portal: quality enhancement in thesis writing using self-managed peer review on a mass scale. The International Review of Research in Open and Distance Learning, 14(1), 186–203.Google Scholar
  2. Alexander, S. (2001). E-learning developments and experiences. Education and Training, 43(4/5), 240–248.CrossRefGoogle Scholar
  3. Anderson, T., & Elloumi, F. (Eds.). (2004). Theory and practice of online learning. Athabasca, BC. Canada: Athabasca University.Google Scholar
  4. Bates, A. W. (1997). Restructuring the university for technological change (pp. 207–228). London: Carnegie Foundation.Google Scholar
  5. Cho, S. K., & Berge, Z. L. (2002). Overcoming barriers to distance training and education. USDLA Journal, 16(1), 16–34.Google Scholar
  6. Collis, B., De-Boer, W., & Slotman, K. (2001). Feedback for web-based assignments. Journal of Computer Assisted Learning, 17(3), 306–313.CrossRefMATHGoogle Scholar
  7. Daniel, J. S. (1997). Why universities need technology strategies. Change: The Magazine of Higher Learning, 29(4), 11–17.CrossRefGoogle Scholar
  8. Duration, H., & Mason, A. (2012). The loneliness of the long-distance learner: social networking and student support. A case study of the distance-learning MA in translation at Bristol University. The Journal of Open and Distance Learning, 27(1), 81–87.CrossRefGoogle Scholar
  9. Fredericksen, E., Picket, A., Shea, P., Pelz, W., & Swan, K. (2000). Student satisfaction and perceived learning with on-line courses: principles and examples from the SUNY learning network. Journal of Asynchronous Learning Networks, 4(2), 7–41.Google Scholar
  10. Garrison, D. R., & Anderson, T. (2003). E-learning in the 21st century: A framework for research and practice. London: Routledge Falmer.CrossRefGoogle Scholar
  11. Gunasekaran, A., McNeil, R. D., & Shaul, D. (2002). E-learning: research and applications. Industrial and Commercial Training, 34(2), 44–53.CrossRefGoogle Scholar
  12. Hallberg, D., Hansson, H., Moberg, J., & Hewagamage, H. (2011). SciPro from a mobile perspective: Technology enhanced supervision of thesis work in emerging regions. Nairobi: Aitec East Africa ICT summit at Oshwal Centre.Google Scholar
  13. Hansson, H. (2012). 4-excellence: IT system for theses. Going Global: Internationalising higher education. London: British Council conference.Google Scholar
  14. Hansson, H, Moberg, J. (2011). Quality processes in technology enhanced thesis work: Negotiating knowledge interests and providing process support online. Bali, Indonesia: 24th ICDE World Conference on Open and Distance Learning.Google Scholar
  15. Hansson, H., Larsson, K., & Wettergren, G. (2009). Open and flexible ICT: Support for student thesis production: Design concept for the future. In A. Gaskell, R. Mills, & A. Tait (Eds.), The cambridge international conference on open and distance learning. Cambridge: The Open University.Google Scholar
  16. Hansson, H., Collin, J., Larsson, K., & Wettergren, G. (2010). Sci-Pro Improving Universities Core Activity with ICT Supporting the Scientific Thesis Writing Process. Budapest: Sixth European Distance and E-Learning Network (EDEN) Research Workshop.Google Scholar
  17. Hashim, N. & Hashim, H. (2010). Outcome based education performance evaluation on the final year degree project. Proceedings of the 7th WSEAS international conference on engineering education. Google Scholar
  18. Hiltz, S. R., Coppola, N., Rotter, N., Turoff, M., & Benbunan-Fich, R. (2000). Measuring the importance of collaborative learning for the effectiveness of ALN: a multi-measure, multi-method approach. Journal of Asynchronous Learning Networks, 4(2), 103–125.Google Scholar
  19. Hrastinski, S., & Keller, C. (2007). Computer-mediated communication in education: a review of recent research. Educational Media International, 44(1), 61–77.CrossRefGoogle Scholar
  20. Hrastinski, S., Keller, C., & Carlsson, S. A. (2010). Design exemplars for synchronous e-learning: a design theory approach. Computers in Education, 55(2), 652–662.CrossRefGoogle Scholar
  21. HSV (2010). Swedish universities & university colleges. Högskoleverket Report 2010:13 R (Swedish National Agency for Higher Education). Retrieved March 15, 2012, from http://www.hsv.se/download/18.ac0b56a12a53b8af858000847/1013R-swedish-universities-2010.pdf.
  22. Krippendorff, K. (1980). Content analysis. An introduction to its methodology. London: The Sage Context Series, Sage Publications.Google Scholar
  23. Krippendorff, K. (2004). Content analysis. An introduction to its methodology (2nd ed.). London: Sage Publications.Google Scholar
  24. Larsson, K., & Hansson, H. (2011). The Challenge for Supervision: Mass Individualization of the Thesis Writing Process with less Recourses. Online Educa Berlin 2011 - 17th International Conference on Technology Supported Learning & Training (ICWE, 2011).Google Scholar
  25. Moore, M. G. (1973). Toward a theory of independent learning and teaching. Journal of Higher Education, 44(9), 661–679.CrossRefGoogle Scholar
  26. Moore, M. G. (1989). Three types of interactions. The American Journal of Distance Education, 3(2), 1–6.CrossRefGoogle Scholar
  27. Muilenburg, L. Y., & Berge, Z. L. (2005). Student barriers to online learning: a factor analytic study. Distance Education, 26(1), 29–48.CrossRefGoogle Scholar
  28. Neuendorf, K. A. (2002). The content analysis guidebook. California: Sage Publications.Google Scholar
  29. Patton, M. Q. (2002). Qualitative research & evaluation methods (3rd ed.). California: Sage Publications.Google Scholar
  30. Randolph, J. J. (2008). Multidisciplinary methods in educational technology research and development: Published by HAMK Press.Google Scholar
  31. Salmon, G. (2000). Learning Submarines: Raising the Periscopes. Retrieved March 20, 2012 from http://nw2000.flexiblelearning.net.au/main/key03.htm.
  32. Saunders, M., Lewis, P., & Thornhill, A. (2007). Research methods for business students. Harlow: Pearson Education.Google Scholar
  33. Sherman, R. C. (1998). Using the world wide web to teach everyday applications of social psychology. Teaching of Psychology, 25, 212–216.CrossRefGoogle Scholar
  34. Tuovinen, J. E. (2000). Factors influencing the success of computer mediated communication (CMC) environments in university teaching: a review and case study. Educational Media International, 37(2), 16–24.CrossRefGoogle Scholar
  35. Ward, M., & Newlands, D. (1998). Use of the web in undergraduate teaching. Computers in Education, 31, 171–184.CrossRefGoogle Scholar
  36. Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  37. Wilson, E. V. (2000). Student characteristics and computer-mediated communication. Computers in Education, 34(2), 67–76.CrossRefGoogle Scholar
  38. Wu, D., & Hiltz, S. R. (2004). Predicting learning from asynchronous online discussions. Journal of Asynchronous Learning Networks, 8(2), 139–152.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Computer and Systems Sciences (DSV)Stockholm UniversityKistaSweden

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