IDEAS home Printed from https://ideas.repec.org/a/gam/jscscx/v9y2020i9p157-d411886.html
   My bibliography  Save this article

Towards a Comprehensive School Effectiveness Model of Citizenship Education: An Empirical Analysis of Secondary Schools in The Netherlands

Author

Listed:
  • Manja Coopmans

    (Department of Child Development and Education, University of Amsterdam, 1018 WS Amsterdam, The Netherlands)

  • Geert Ten Dam

    (Department of Child Development and Education, University of Amsterdam, 1018 WS Amsterdam, The Netherlands)

  • Anne Bert Dijkstra

    (Department of Child Development and Education, University of Amsterdam, 1018 WS Amsterdam, The Netherlands)

  • Ineke Van der Veen

    (Kohnstamm Institute, University of Amsterdam, 1018 WB Amsterdam, The Netherlands)

Abstract

We still have only a limited understanding of the effectiveness of schools in promoting citizenship, the factors explaining this effectiveness and the way in which these aspects interact. Using elaborate cross-sectional data from students, teachers, team leaders and school leaders at 78 Dutch secondary schools, this study empirically examines a school effectiveness model of citizenship education in order to achieve a more comprehensive explanation of citizenship competence acquisition. Using multilevel structural equation models, we analyze direct and indirect school-level predictors of student knowledge, attitudes and self-evaluated skills regarding citizenship. Four aspects of citizenship education are examined: the school’s policies regarding citizenship education, its teaching practices, and its professional and pedagogical learning environment (i.e., teaching community and classroom climate). With respect to school policies, positive effects are found for the attention paid to citizenship education in staff meetings. The professional learning environment is related to students’ citizenship competences mainly indirectly, via the average classroom climate. Effects of teaching practices vary: more emphasis on monitoring is more frequently found at schools with lower average levels of citizenship competences, whereas schools that let students choose their own topics in class have on average higher levels of citizenship competences.

Suggested Citation

  • Manja Coopmans & Geert Ten Dam & Anne Bert Dijkstra & Ineke Van der Veen, 2020. "Towards a Comprehensive School Effectiveness Model of Citizenship Education: An Empirical Analysis of Secondary Schools in The Netherlands," Social Sciences, MDPI, vol. 9(9), pages 1-32, September.
    • Handle: RePEc:gam:jscscx:v:9:y:2020:i:9:p:157-:d:411886
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2076-0760/9/9/157/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2076-0760/9/9/157/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Anders Skrondal & Petter Laake, 2001. "Regression among factor scores," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 563-575, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. José María Álvarez-Martínez-Iglesias & Pedro Miralles-Martínez & Jesús Molina-Saorín & Francisco Javier Trigueros-Cano, 2021. "Secondary School Students’ Perception of the Acquisition of Social Science Skill," Social Sciences, MDPI, vol. 10(4), pages 1-12, March.
    2. Liyuan Liu & Steven Donbavand & Bryony Hoskins & Jan Germen Janmaat & Dimokritos Kavadias, 2021. "Measuring and Evaluating the Effectiveness of Active Citizenship Education Programmes to Support Disadvantaged Youth," Social Sciences, MDPI, vol. 10(10), pages 1-10, October.
    3. Geert Ten Dam & Anne Bert Dijkstra & Ineke Van der Veen & Anne Van Goethem, 2020. "What Do Adolescents Know about Citizenship? Measuring Student’s Knowledge of the Social and Political Aspects of Citizenship," Social Sciences, MDPI, vol. 9(12), pages 1-24, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rajdeep Grewal & Murali Chandrashekaran & F. Robert Dwyer, 2008. "Navigating Local Environments with Global Strategies: A Contingency Model of Multinational Subsidiary Performance," Marketing Science, INFORMS, vol. 27(5), pages 886-902, 09-10.
    2. Anastasiia Laskovaia & Galina Shirokova & Michael H. Morris, 2017. "National culture, effectuation, and new venture performance: global evidence from student entrepreneurs," Small Business Economics, Springer, vol. 49(3), pages 687-709, October.
    3. Zsuzsa Bakk & Jouni Kuha, 2018. "Two-Step Estimation of Models Between Latent Classes and External Variables," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 871-892, December.
    4. Marco Castillo & John A. List & Ragan Petrie & Anya Samek, 2020. "Detecting Drivers of Behavior at an Early Age: Evidence from a Longitudinal Field Experiment," NBER Working Papers 28288, National Bureau of Economic Research, Inc.
    5. Anna Aizer & Flávio Cunha, 2012. "The Production of Human Capital: Endowments, Investments and Fertility," NBER Working Papers 18429, National Bureau of Economic Research, Inc.
    6. Janne Petersen & Karen Bandeen-Roche & Esben Budtz-Jørgensen & Klaus Groes Larsen, 2012. "Predicting Latent Class Scores for Subsequent Analysis," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 244-262, April.
    7. Tatiana Beliaeva & Galina Shirokova & William Wales & Elena Gafforova, 2020. "Benefiting from economic crisis? Strategic orientation effects, trade-offs, and configurations with resource availability on SME performance," International Entrepreneurship and Management Journal, Springer, vol. 16(1), pages 165-194, March.
    8. Bernal, Pedro & Mittag, Nikolas & Qureshi, Javaeria A., 2016. "Estimating effects of school quality using multiple proxies," Labour Economics, Elsevier, vol. 39(C), pages 1-10.
    9. Alexandre J. S. Morin & Daniel G. Gallagher & John P. Meyer & David Litalien & Paul F. Clark, 2021. "Investigating the Dimensionality and Stability of Union Commitment Profiles over a 10-Year Period: A Latent Transition Analysis," ILR Review, Cornell University, ILR School, vol. 74(1), pages 224-254, January.
    10. Ke-Hai Yuan & Zhiyong Zhang & Lijuan Wang, 2024. "Signal-to-Noise Ratio in Estimating and Testing the Mediation Effect: Structural Equation Modeling versus Path Analysis with Weighted Composites," Psychometrika, Springer;The Psychometric Society, vol. 89(3), pages 974-1006, September.
    11. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
    12. Wu, Jianmin & Bentler, Peter M., 2013. "Limited information estimation in binary factor analysis: A review and extension," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 392-403.
    13. Yang, Lianping & Liu, Chaojie & Ferrier, J. Adamm & Zhang, Xinping, 2015. "Organizational barriers associated with the implementation of national essential medicines policy: A cross-sectional study of township hospitals in China," Social Science & Medicine, Elsevier, vol. 145(C), pages 201-208.
    14. Cecilie Thøgersen-Ntoumani & Andreas Stenling & Esther Izett & Eleanor Quested, 2022. "Personality, Risk Perceptions, and Health Behaviors: A Two-Wave Study on Reciprocal Relations in Adults," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    15. Mihretie, Fekremariam Asargew & Tsunekawa, Atsushi & Haregeweyn, Nigussie & Adgo, Enyew & Tsubo, Mitsuru & Masunaga, Tsugiyuki & Meshesha, Derege Tsegaye & Ebabu, Kindiye & Nigussie, Zerihun & Sato, S, 2022. "Exploring teff yield variability related with farm management and soil property in contrasting agro-ecologies in Ethiopia," Agricultural Systems, Elsevier, vol. 196(C).
    16. Heijdra Suasnabar, Jan M. & Finch, Aureliano Paolo & Mulhern, Brendan & van den Akker-van Marle, M. Elske, 2024. "Exploring the measurement of health related quality of life and broader instruments: A dimensionality analysis," Social Science & Medicine, Elsevier, vol. 346(C).
    17. Bakk, Zsuzsa & Kuha, Jouni, 2018. "Two-step estimation of models between latent classes and external variables," LSE Research Online Documents on Economics 85161, London School of Economics and Political Science, LSE Library.
    18. Marie-Ann Sengewald & Steffi Pohl, 2019. "Compensation and Amplification of Attenuation Bias in Causal Effect Estimates," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 589-610, June.
    19. Seohee Park & Seongeun Kim & Ji Hoon Ryoo, 2020. "Latent Class Regression Utilizing Fuzzy Clusterwise Generalized Structured Component Analysis," Mathematics, MDPI, vol. 8(11), pages 1-16, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jscscx:v:9:y:2020:i:9:p:157-:d:411886. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.