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Training can better meet user needs by involving the potential users early in the process. Here, development of open science training for food science students and professionals began with 11 guided interviews of 15 beneficiaries in a European project aiming to build a ‘food cloud’ of datasets and services (FNS-Cloud, H2020 No. 863059). Discussions covered what partners want to learn, how they prefer to learn, and who are their ideal trainers. Inductive coding of interview transcripts with NVivo 12 qualitative analysis software revealed an inclination for technical training with a focus on data. Face-to-face learning and on-demand elearning offered by younger scientists were preferred methods and trainers. Most interviewees also talked about ‘food cloud’-specific fears and desires. These interviews are now the foundation of three well received elearning courses and two workshop series supporting the value of user input in early course development decisions.
course development, qualitative data, open science, lifelong learning
course development, qualitative data, open science, lifelong learning
citations 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). | 0 | |
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. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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