09 SES 14 B JS, Educational Research Infrastructure
Joint Paper Session NW 09 and NW 12
The reuse of existing data and instruments from educational research becomes more and more popular. Funding organisations explicitly promote secondary analyses of already existing data before planning new research programs that include additional data collection. Furthermore the reuse of existing and tested research instruments as for example questionnaires prevents researchers from reinventing the wheel and allows the usage of charge free instruments. To foster and guide this process data repositories provide services for the exchange of data. Moreover, background information about the reuse of data and assessment instruments is provided. Following the ideas of FAIR data (Findable, Accessible, Interoperable, and Re-usable; see Wilkinson, M. D. et al. 2016) and open data (BDOAK 2003, EuropeanCommission 2013a) all scientific infrastructures providers are stimulated to engage in networking processes to expand national and international data infrastructures. This development also affects the daily work of university libraries, which need to build repositories for the storage of inhouse research data.
Researches benefit from this development in two ways: on the one hand researchers are able to find and get access to data/research instruments. On the other hand published research data and instruments receive a DOI number (persistent identifier), comparable to research papers in journals. Thus, these publications can be classified as regular publications, which represent an essential product of research. Furthermore trustworthy, transparent and legal ways of exchanging data and assessment instruments are offered by repositories, considering issues as copyrights and privacy of study participants. At the same time these services enhance the exchange of knowledge about the validity and reliability of instruments. The latter is particularly important for the continuing improvement of assessment instruments and the comparability of findings.
Investigating reuse behaviors of scientist`s Kim and Yoon (2017) showed that the perceived usefulness (i.e., quality of the data, matching of the existing data with the own research interests and needed time, costs and effort for the use of the data) is the most important factor that influences data reuse intensions. Another important factor to encourage scientists to reuse data was having external resources and supports, including data repositories. This finding is supported by previous studies that identified the important role of the availability of data repositories for the data reuse (Fear & Donaldson 2012, Yakel et al. 2013). Making research data and research instruments accessible via repositories is a substantial contribution to a European network for sharing and exchanging research data. From a European point of view the extension of a proper research infrastructure promises to be a powerful engine for the further development of international research activities and collaborations (see guidelines of Horizon 2020 program, European Commission 2013b). The present paper describes the offerings of the Research Data Centre Education (RDC Education) hosted by the German Institute for International Educational Research (DIPF). The RDC Education provides educational research instruments like questionnaires and standardized tests to support the scientific community in terms of assessment und evaluation. Based on this offer, researchers are able to combine already existing questionnaires and assessment tests resp. items and scales to create a new one according to their specific research questions. The documentation of statistical values allows the comparison of several instruments about the same subject as a preparation for a new questionnaire or assessment test. The aim is to build up and maintain an infrastructure for a sustainable storage of questionnaire and assessment items in a central open access repository as an approach to support questionnaire and assessment test development and reuse. Actually the database comprises a total of approx. 33,000 questionnaire items originated from several large- and small scale studies in various languages. Furthermore over 1,000 assessment items are accessible in the test archive of the RDC Education.
How the content is stored will be shown on the basis of the developed metadata scheme, which is derived from the standard DDI (data documentation initiative). Essential elements are literature references, answer formats, information about the target group, citation of origin and item statistics giving evidence about the item quality (according to classical test theory and item response theory). The usage of standards opens the system for interoperability to other related databases and systems in a national and international context and fosters the development of a Europe-wide confederated research data infrastructure like the “German Network for Educational Research Data“ did in Germany. This network provides a central access to background information of data and data itself to stimulate secondary analysis und the reuse of research instruments in the German educational research community.
BDOAK (2003, January 2018). Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities. Berlin. http://openaccess.mpg.de/Berlin-Declaration EuropeanCommission (2013a). Guidelines on Open Access to Scientific Publications and Research Data in Horizon 2020 Version 16 December 2013. European Commission (2013b, January 2018). Commission launches pilot to open up publicly funded research data. http://europa.eu/rapid/press-release_IP-13-1257_en.htm Fear, K. & Donaldson, D.R. (2012). Provenance and credibility in scientific data repositories. Archival Science, 12, 319-339. Kim, Y. & Yoon, A. (2017). Scientists’ Data Reuse Behaviors: A Multi-Level Analysis. Journal of the Association for Information Science and Technology (JASIST), 68(12), 2709–2719. DOI: 10.1002/asi.23892 Yakel E., Faniel, I.M., Kriesberg, A. & Yoon, A. (2003). Trust in digital repositories. International Journal of Digital Curation, 8, 143-156. Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).
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