Finding potential problems in the thesis process in higher education: Analysis of e-mails to develop a support system
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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.
KeywordsSciPro Idea-bank Thesis process Learning process Autonomous learning Communication platform
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.
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