Dataset: Conceptions about Deep Time in European First-Year University Students
Authors/Creators
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Kuschmierz, Paul
(Data collector)1
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Beniermann, Anna
(Data collector)2
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Pinxten, Rianne
(Data collector)3
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Aivelo, Tuomas
(Data collector)4
- Berniak-Woźny, Justyna (Data collector)5
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Bohlin, Gustav
(Data collector)6
- Bugallo-Rodriguez, Anxela (Data collector)7
- Cardia, Pedro (Data collector)8
- Cavadas, Bento Filipe Barreiras Pinto (Data collector)9
- Cebesoy, Umran Betul (Data collector)10
- Cvetković, Dragana D. (Data collector)11
- Demarsy, Emilie (Data collector)12
- Đorđević, Mirko S. (Data collector)11
- Drobniak, Szymon M. (Data collector)13
- Dubchak, Liudmyla (Data collector)14
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Dvořáková, Radka M.
(Data collector)15
- Fančovičová, Jana (Data collector)16
- Fortin, Corinne (Data collector)17
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Futo, Momir
(Data collector)18
- Geamănă, Nicoleta Adriana (Data collector)19
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Gericke, Niklas
(Data collector)20
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Grasso, Donato A.
(Data collector)21
- Korfiatis, Konstantinos (Data collector)22
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Lendvai, Ádám Z.
(Data collector)23
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Mavrikaki, Evangelia
(Data collector)24
- Meneganzin, Andra (Data collector)25
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Mogias, Athanasios
(Data collector)26
- Möller, Andrea (Data collector)27
- Mota, Paulo G. (Data collector)28
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Naciri, Yamama
(Data collector)29
- Németh, Zoltán (Data collector)23
- Ożańska-Ponikwia, Katarzyna (Data collector)30
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Paolucci, Silvia
(Data collector)31
- Pap, Péter László (Data collector)32
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Petersson, Maria
(Data collector)20
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Pietrzak, Barbara
(Data collector)33
- Pievani, Telmo (Data collector)25
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Pobric, Alma
(Data collector)34
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Porozovs, Juris
(Data collector)35
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Realdon, Giulia
(Data collector)36
- Sá-Pinto, Xana (Data collector)37
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Savković, Uroš B.
(Data collector)11
- Sicard, Mathieu (Data collector)38
- Sofonea, Mircea T. (Data collector)38
- Sorgo, Andrej (Data collector)39
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Stermin, Alexandru N.
(Data collector)32
- Tăușan, Ioan (Data collector)40
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Torkar, Gregor
(Data collector)41
- Türkmen, Lütfullah (Data collector)10
- Tutnjević, Slavica (Data collector)42
- Uitto, Anna E. (Data collector)43
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Varga, Máté
(Data collector)44
- Varga, Mirna (Data collector)45
- Vazquez-Ben, Lucia (Data collector)46
- Viguera, Enrique (Data collector)47
- Virtbauer, Lisa Christine (Data collector)48
- Vutsova, Albena (Data collector)49
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Yruela, Inmaculada
(Data collector)50
- Zandveld, Jelle (Data collector)51
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Graf, Dittmar
(Data collector)1
- 1. Justus-Liebig-University Giessen
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2.
University of Bremen
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3.
University of Antwerp
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4.
Leiden University
- 5. SWPS University
- 6. Public & Science (VA)
- 7. University of A Coruña
- 8. Politécnico Do Porto
- 9. Universidade de Aveiro
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10.
Usak University
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11.
University of Belgrade
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12.
University of Geneva
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13.
Jagiellonian University
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14.
National Academy for Public Administration under the President of Ukraine
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15.
Charles University
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16.
University of Trnava
- 17. University of Paris
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18.
Ruder Boškovic Institute Zagreb
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19.
University of Bucharest
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20.
Karlstad University
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21.
University of Parma
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22.
University of Cyprus
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23.
University of Debrecen
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24.
National and Kapodistrian University of Athens
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25.
University of Padua
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26.
Democritus University of Thrace
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27.
University of Vienna
- 28. University of Porto
- 29. Geneva Botanic Garden
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30.
University of Bielsko-Biała
- 31. Laboratorio Di Scienze Sperimentali
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32.
Babeș-Bolyai University
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33.
University of Warsaw
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34.
University of Sarajevo
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35.
University of Latvia
- 36. University of Camerino
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37.
University of Aveiro
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38.
Université de Montpellier
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39.
University of Maribor
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40.
Lucian Blaga University of Sibiu
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41.
University of Ljubljana
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42.
University of Banja Luka
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43.
University of Helsinki
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44.
Eötvös Loránd University
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45.
University of Osijek
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46.
Universidade da Coruña
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47.
Universidad de Málaga
- 48. Universität Salzburg
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49.
Sofia University "St. Kliment Ohridski"
- 50. Spanish National Research Council (CSIC)
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51.
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.