Adobe Stock/merklicht.de
From audio and video recordings in the classroom to columns of figures from surveys, performance measurements and material from educational statistics – as empirical educational research expands, so does the variety of different research data. This trend is being reinforced by digitalisation. ‘New’ forms of data (for example, log file data, eye-tracking data, learning analytics) and large amounts of data are produced. Collecting data is cost-intensive and time-consuming for both the research and the educational institutions involved. At the same time, it is becoming increasingly difficult to convince educational institutions to participate in research projects involving data collection – and compliance with data protection is also rigorous.
The Framework Programme for Empirical Educational Research therefore aims to make existing and future data more accessible for research purposes. Good research data infrastructure with quality-assured research data relieves the burden on educational institutions and ensures that funding is used more efficiently. In addition, this also contributes to the goals of maintaining the most open scientific endeavour possible in which research data and its documentation are accessible for the replication of results and subsequent use for further lines of enquiry.
In particular, extensive, quantitative data sets from (international) large-scale surveys (such as PIRLS/IGLU, TIMSS, PISA or PIAAC) and large panel surveys (such as SOEP or NEPS), as well as data sets from smaller or qualitative research projects, offer a wealth of information that cannot always be evaluated comprehensively by primary researchers. The secondary use of these data sets can contribute to answering content-related and methodological enquiries in educational research and generate further research questions. For projects funded under the educational research programme it is therefore necessary to check at an early stage whether data is already available that can be used to answer the research question or partial aspects of it. However, this does not exclude the possibility of collecting new data in research projects if this is necessary to answer the research question.
Research data management plans must be drawn up at the latest during concrete project planning. Such plans contain all the basic information on the collection, storage, documentation and archiving of the research data collected in the project. In addition, data protection, personal rights, copyrights and, last but not least, ethical issues must be taken into account. The „Verbund Forschungsdaten Bildung“ (German Network for Educational Research Data) offers a range of handouts and consulting and training services on these complex issues of creating data management plans.
A data management plan is a living document which is updated and developed during the course of the project. It is used not only for the traceability of the data by downstream researchers, but also for the orientation and documentation of the research data within the project.
Grant recipients undertake to make the data obtained as part of the project available to a research data centre to enable long-term data backup in the interests of good scientific practice. In the research data centres, the data is archived, documented and made findable. The data is available to the scientific community on request for replication and secondary evaluation.
In order to harness the data from BMBF-funded projects in educational research for reanalysis and secondary analysis, the BMBF provided funding for the VerbundFDB (German Network for Educational Research Data) from 2013 to 2021. This project built up a uniform infrastructure for educational research. The infrastructure ensures that the data from research projects can be transferred to the appropriate institution. The network of participating research data centres ensures that all types of data are archived, documented and made available with the necessary professional and methodological expertise. The scientific community can access a large pool of quality-assured data and use it for further research.
In 2022, the VerbundFDB project was extended in a permanent form at the DIPF | Leibniz Institute for Education and Human Development. It provides the basis for a cooperative network with a unified research data infrastructure for educational research.
Related Links:
