Symposium 1: Doctoral education in a national network: providing an epistemic space?
DOI:
https://doi.org/10.54337/nlc.v13.8612Abstract
In 2018 the Swedish National Graduate School for Digital Technologies in Education (GRADE) was initiated as a cooperative venture between six Swedish universities. In 2020, the Swedish national research school for the digitalisation of teacher education (in short called UPGRADE) was initiated. GRADE and UPGRADE aims to strengthen the expertise in these areas on a national level in Sweden and, in doing so, increase both national and international cooperation in research training activities. One of the fundamental pillars of GRADE and UPGRADE is the networked character of the doctoral studies, with joint courses provided by the participating universities and arranged using an interdisciplinary approach. The doctoral students are admitted to different disciplines, among others Applied IT, Computer science, Curriculum studies, Education, Educational Work, Informatics, Media technology, Technology and Learning, and Work Integrated Learning. This implies that several issues with a bearing on the digitalization of education, will be researched by the doctoral students from different epistemological and analytical perspectives and with different methodological approaches. At the 2020 Networked Learning Conference in Kolding, a first symposium was held where six of the doctoral students from the GRADE research school presented their work (Lindberg & Lundin, 2020). These reported on theoretical frameworks ranging from the theory of practice architectures (Kemmis et al., 2014; Mahon, Francisco, & Kemmis, 2017), basic conceptual underpinnings of behaviorism (Skinner, 1974); Actor-Network Theory (ANT) (Latour, 2005); Wenger's expanded theory of Communities of Practice; a multimodal perspective including things-to-things, things-to-human and human-to-human connections (Bonderup Dohn, Cranmer, Sime, de Laat, and Ryberg, 2018; Jones, 2015); and a focus on the technologies and their functions.
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Copyright (c) 2022 J Ola Lindberg, Johan Lundin
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