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D2.1 – The DIOSI Model for Doctoral Learning: A holistic approach

Authors: Kersschot, Margaux;

D2.1 – The DIOSI Model for Doctoral Learning: A holistic approach

Abstract

In this policy paper, a holistic approach to doctoral learning in terms of research, self-development and training formats is argued for. Based on finding from the literature and expert interviews, four main arguments are made: Pressures on the doctoral process (be it by funding, time restrictions, formal obligations etc.) are thereby pressures on the quality of doctorates and the experience of the doctoral candidate. Therefore, the DIOSI model emphasises the learning outcomes to be acquired and synthesises these components into a comprehensible and manageable guided process. The DIOSI model emphasizes creativity and critical thinking as essential to building innovation in doctorates, and promotes open science practices as part of the new normal. At the same time, the development of the doctoral candidate (DC) is placed centrally, following Mowbray & Halse’s (2010) conceptualisation of doctoral learning within Aristoteles’ Virtue theory. The benefit is that this allows to ‘shift the lens from the instrumental production of the skilled PhD graduate to the progressive building of virtuous individuals who contribute to society through their productive actions’ (Mowbray & Halse 2010). A vision where the doctoral candidate stands at the centre of the doctoral universe emerges, where they are comprehensively supported by the supervisor and the institution. Supervisors take several roles in the doctoral process: that of director, mentor, coach and supporter (Link Edu-Res project – toolbox). Moreover, career guidance is essential to alleviate the employability-related stress of DCs. Therefore, the formation of supervisory teams is proposed, that include a mentor with specific remit for career guidance and formal training opportunities. Acknowledging diverging models and perspectives on formal training within doctorates, it is recommended for institutions to use a mix containing both informal learning and formal training. For those institutions that have no formal training installed and/or could use inspiration, a training programme for the DC is proposed. This recommendation is inspired by the benefits that this can bring: Courses are an efficient and financially viable way to disseminate knowledge, crucial in guiding doctoral candidates (e.g., by providing an overview of all existing methods, or existing communication methods to valorise their PhD) and limiting the time to completion of the degree (time-to-degree) Training courses allow for exchange with peers outside the research group/domain and the cross -fertilisation of knowledgebases. Courses enable the development of a learning cohort and builds community. In conclusion, this paper proposes a joint vision and framework for doctoral learning at the DIOSI partner institutions, providing a common language and understanding for the partners. Furthermore, this new framework propels doctoral learning into a future where universities are fully engaged in society, and where society can also engage at the level of doctoral learning. The next steps are to develop implementation roadmaps that consider the individual context of each institution (foreseen in the DIOSI-project) and to run (small) pilots to test the DIOSI-model in practice.

Keywords

transferable skills, Open Science, Doctoral training, graduate tracking, entrepreneurship, innovation, Early Career Researchers

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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