Evaluating the Effectiveness of Data Management Training: DataONE’s Survey Instrument
DOI:
https://doi.org/10.2218/ijdc.v12i2.508Abstract
Effective management is a key component for preparing data to be retained for future long term access, use, and reuse by a broader community. Developing the skills to plan and perform data management tasks is important for individuals and institutions. Teaching data literacy skills may also help to mitigate the impact of data deluge and other effects of being overexposed to and overwhelmed by data.
The process of learning how to manage data effectively for the entire research data lifecycle can be complex. There are often multiple stages involved within a lifecycle for managing data, and each stage may require specific knowledge, expertise, and resources. Additionally, although a range of organizations offers data management education and training resources, it can often be difficult to assess how effective the resources are for educating users to meet their data management requirements.
In the case of Data Observation Network for Earth (DataONE), DataONE’s extensive collaboration with individuals and organizations has informed the development of multiple educational resources. Through these interactions, DataONE understands that the process of creating and maintaining educational materials that remain responsive to community needs is reliant on careful evaluations. Therefore, the impetus for a comprehensive, customizable Education EVAluation instrument (EEVA) is grounded in the need for tools to assess and improve current and future training and educational resources for research data management.
In this paper, the authors outline and provide context for the background and motivations that led to creating EEVA for evaluating the effectiveness of data management educational resources. The paper details the process and results of the current version of EEVA. Finally, the paper highlights the key features, potential uses, and the next steps in order to improve future extensions and revisions of EEVA.
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