Published June 1, 2026 | Version v1
Dataset Open

Dataset: Conceptions about Deep Time in European First-Year University Students

Authors/Creators

  • 1. Justus-Liebig-University Giessen
  • 2. EDMO icon University of Bremen
  • 3. ROR icon University of Antwerp
  • 4. ROR icon Leiden University
  • 5. SWPS University
  • 6. Public & Science (VA)
  • 7. University of A Coruña
  • 8. Politécnico Do Porto
  • 9. Universidade de Aveiro
  • 10. ROR icon Usak University
  • 11. ROR icon University of Belgrade
  • 12. ROR icon University of Geneva
  • 13. ROR icon Jagiellonian University
  • 14. ROR icon National Academy for Public Administration under the President of Ukraine
  • 15. ROR icon Charles University
  • 16. ROR icon University of Trnava
  • 17. University of Paris
  • 18. EDMO icon Ruder Boškovic Institute Zagreb
  • 19. ROR icon University of Bucharest
  • 20. ROR icon Karlstad University
  • 21. ROR icon University of Parma
  • 22. ROR icon University of Cyprus
  • 23. ROR icon University of Debrecen
  • 24. ROR icon National and Kapodistrian University of Athens
  • 25. ROR icon University of Padua
  • 26. ROR icon Democritus University of Thrace
  • 27. EDMO icon University of Vienna
  • 28. University of Porto
  • 29. Geneva Botanic Garden
  • 30. ROR icon University of Bielsko-Biała
  • 31. Laboratorio Di Scienze Sperimentali
  • 32. ROR icon Babeș-Bolyai University
  • 33. ROR icon University of Warsaw
  • 34. ROR icon University of Sarajevo
  • 35. ROR icon University of Latvia
  • 36. University of Camerino
  • 37. ROR icon University of Aveiro
  • 38. ROR icon Université de Montpellier
  • 39. ROR icon University of Maribor
  • 40. ROR icon Lucian Blaga University of Sibiu
  • 41. ROR icon University of Ljubljana
  • 42. ROR icon University of Banja Luka
  • 43. ROR icon University of Helsinki
  • 44. ROR icon Eötvös Loránd University
  • 45. ROR icon University of Osijek
  • 46. ROR icon Universidade da Coruña
  • 47. ROR icon Universidad de Málaga
  • 48. Universität Salzburg
  • 49. ROR icon Sofia University "St. Kliment Ohridski"
  • 50. Spanish National Research Council (CSIC)
  • 51. ROR icon Utrecht University

Contributors

Data curator:

Description

This dataset provides cross-national data on first-year university students’ conceptions about deep time and evolutionary timescales collected within the framework of the European research project EuroScitizen. The data originate from a large-scale standardized survey conducted across 26 European countries among undergraduate students at the beginning of their university studies (see original publication: Kuschmierz et al., 2021). The present dataset specifically focuses on items addressing conceptions of deep time, including students’ understanding of temporal scales relevant to evolutionary processes and Earth history.

The data set includes N = 7215 participants from 23 countries. The questionnaire was administered in multiple national languages following a Translation–Review–Adjudication–Pre-test–Documentation (TRAPD) procedure to ensure conceptual and linguistic equivalence across participating countries. Data were collected using standardized online and paper-based survey procedures coordinated among national research teams. Participation was voluntary and anonymous, and all procedures complied with national ethical regulations and the General Data Protection Regulation (GDPR).

Data collection was based on the validated “Evolution Education Questionnaire” (EEQ; Beniermann et al., 2021), a comprehensive instrument designed to assess evolution-related knowledge, acceptance, and associated explanatory variables in a cross-cultural context. The presented dataset is based on the instrument “KAEVO 2.0” part C (Kuschmierz et al., 2020). In addition to the deep time items, the dataset contains information about the country of the participants as well as the sum scores of their knowledge about evolution (based on KAEVO 2.0 part A) and their attitudes towards evolution (based on ATEVO; Beniermann, 2019). These sum scores have been calculated based on the raw data published as supplementary material in Kuschmierz et al. (2021). These additional variables enable comparative analyses.

For more information about material and methods, please see the original publication (Kuschmierz et al., 2021).

For information about the used instrument KAEVO 2.0 part C, see the original publication of the instrument (Kuschmierz et al., 2020) as well as the method report about the EEQ (Beniermann et al., 2021).

This publication is based upon work from COST Action EuroScitizen, supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. www.cost.eu

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Additional details

References

  • Beniermann, A., Kuschmierz, P., Pinxten, R., Aivelo, T., Bohlin, G., Brennecke, J. S., ... & Graf, D. (2021). Evolution Education Questionnaire on Acceptance and Knowledge (EEQ)-Standardised and ready-to-use protocols to measure acceptance of evolution and knowledge about evolution in an international context. Zenodo. https://doi.org/10.5281/zenodo.4554742
  • Beniermann, A. (2019). Evolution–von Akzeptanz und Zweifeln. Springer Fachmedien Wiesbaden.
  • Kuschmierz, P., Beniermann, A., Bergmann, A., Pinxten, R., Aivelo, T., Berniak-Woźny, J., ... & Graf, D. (2021). European first-year university students accept evolution but lack substantial knowledge about it: a standardized European cross-country assessment. Evolution: Education and Outreach, 14(1), 17.
  • Kuschmierz, P., Beniermann, A., & Graf, D. (2020). Development and evaluation of the knowledge about evolution 2.0 instrument (KAEVO 2.0). International Journal of Science Education, 42(15), 2601-2629.