Quality processes in technology enhanced thesis work: Negotiating knowledge interests and providing process support online
2011 (English)In: 24 ICDE World Conference 2011, 2011Conference paper (Refereed)
A thesis at the Bachelor's, Master's or PhD levels in higher education is the final, independent and applied scientific work necessary for each student who wants an academic degree. There are a number of issues related to successful support of thesis work. Basically, a campus student and distance student face the same problems when writing a thesis. They need to structure their own learning, they are ”alone” with their particular project, and they need similar support. In this paper an approach for efficient support of both campus and distance thesis writing students is suggested. The aim is to facilitate self-directed learning, peer-interaction and provide supervisors with qualified support. The model includes a matching system that initially negotiates the different knowledge interests presented by the student, the supervisor, the university and work life/industry. All four interests need to be addressed in order to motivate the student and supervisor, to adhere to university rules and regulations and to be relevant for the business sector. The IT-system (SciPro) constructed for this purpose has been used to match >300 students with >70 supervisors. It is a scalable system usable for both distance and campus based supervisors and students. Furthermore, this article presents the SciPro-system´s functionalities supporting the actual thesis work process. This includes a new pedagogical design and innovative technical implementation of: a) a dynamic peer-review system, b) anti-plagiarism software, c) mobile phone apps d) student controlled ”state of mind indicator”, e) dynamic checklists for each phase in the scientific process, f) video lectures and other resources.
Place, publisher, year, edition, pages
Quality and ODL, Management, Supervision, Processes, Self regulated learning
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-67177OAI: oai:DiVA.org:su-67177DiVA: diva2:469596