IDEAS home Printed from https://ideas.repec.org/a/zbw/espost/140878.html
   My bibliography  Save this article

Patterns of Literacy and Numeracy Activities in Preschool and Their Relation to Structural Characteristics and Children's Home Activities

Author

Listed:
  • Lehrl, Simone
  • Smidt, Wilfried
  • Grosse, Christiane
  • Richter, David

Abstract

Early literacy and numeracy activities in family and preschool are considered important for promoting children’s early literacy and numeracy skills. However, little research exists, especially in Germany, on the frequency of such activities in different contexts. The current study identified patterns of literacy and numeracy activities in preschools and their relation to structural preschool characteristics and to attributes of the home learning environment. Four hundred twenty-one children attending 89 preschool classes in two German federal states were examined. The results indicate that preschools fall into three different profiles of literacy and numeracy activities: low levels of engagement in both domains, numeracy-oriented engagement and literacy-oriented engagement. Additionally, structural characteristics of the preschools, family literacy and numeracy activities were found to predict children’s profile membership. The study’s implications for future research and early education are discussed.

Suggested Citation

  • Lehrl, Simone & Smidt, Wilfried & Grosse, Christiane & Richter, David, 2014. "Patterns of Literacy and Numeracy Activities in Preschool and Their Relation to Structural Characteristics and Children's Home Activities," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29(5), pages 577-597.
    • Handle: RePEc:zbw:espost:140878
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/140878/1/Lehrl_2014_Patterns-Literacy-Numeracy.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Linzer, Drew A. & Lewis, Jeffrey B., 2011. "poLCA: An R Package for Polytomous Variable Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i10).
    2. Bolck, Annabel & Croon, Marcel & Hagenaars, Jacques, 2004. "Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators," Political Analysis, Cambridge University Press, vol. 12(1), pages 3-27, January.
    3. Ganzeboom, H.B.G. & de Graaf, P.M. & Treiman, D.J. & de Leeuw, J., 1992. "A standard international socio-economic index of occupational status," WORC Paper 92.01.001/1, Tilburg University, Work and Organization Research Centre.
    4. Rick L. Williams, 2000. "A Note on Robust Variance Estimation for Cluster-Correlated Data," Biometrics, The International Biometric Society, vol. 56(2), pages 645-646, June.
    5. Stanley Sclove, 1987. "Application of model-selection criteria to some problems in multivariate analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 333-343, September.
    6. Kamel Jedidi & Venkatram Ramaswamy & Wayne Desarbo, 1993. "A maximum likelihood method for latent class regression involving a censored dependent variable," Psychometrika, Springer;The Psychometric Society, vol. 58(3), pages 375-394, September.
    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. Kuger, Susanne & Marcus, Jan & Spiess, C. Katharina, 2019. "Day care quality and changes in the home learning environment of children," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 27(3), pages 265-286.
    2. Susanne Kuger & Jan Marcus & C. Katharina Spiess, 2017. "Does Quality of Early Childhood Education and Care Affect the Home Learning Environment of Children?," Discussion Papers of DIW Berlin 1687, DIW Berlin, German Institute for Economic Research.

    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. Guangchao Feng, 2014. "Estimating intercoder reliability: a structural equation modeling approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2355-2369, July.
    2. Aurélie Bertrand & Christian Hafner, 2014. "On heterogeneous latent class models with applications to the analysis of rating scores," Computational Statistics, Springer, vol. 29(1), pages 307-330, February.
    3. 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.
    4. Durante, Daniele & Canale, Antonio & Rigon, Tommaso, 2019. "A nested expectation–maximization algorithm for latent class models with covariates," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 97-103.
    5. Laurent Ott & Mehdi Farsi & Sylvain Weber, 2021. "Beyond political divides: analyzing public opinion on carbon taxation in Switzerland," Chapters, in: Axel Franzen & Sebastian Mader (ed.), Research Handbook on Environmental Sociology, chapter 17, pages 313-339, Edward Elgar Publishing.
    6. Janez Dolšak & Nevenka Hrovatin & Jelena Zorić, 2020. "Analysing Consumer Preferences, Characteristics, and Behaviour to Identify Energy-Efficient Consumers," Sustainability, MDPI, vol. 12(23), pages 1-19, November.
    7. Aline Riboli Marasca & Maurício Scopel Hoffmann & Anelise Reis Gaya & Denise Ruschel Bandeira, 2021. "Subjective Well-Being and Psychopathology Symptoms: Mental Health Profiles and their Relations with Academic Achievement in Brazilian Children," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(3), pages 1121-1137, June.
    8. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    9. Angela Bruns, 2015. "Stability and Change: Income Packaging among Partners of Incarcerated Men," Working Papers wp15-04-ff, Princeton University, School of Public and International Affairs, Center for Research on Child Wellbeing..
    10. Jun Xie & Wataru Nozawa & Shunsuke Managi, 2020. "The role of women on boards in corporate environmental strategy and financial performance: A global outlook," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(5), pages 2044-2059, September.
    11. Martin Lukac & Nadja Doerflinger & Valeria Pulignano, 2019. "Developing a Cross-National Comparative Framework for Studying Labour Market Segmentation: Measurement Equivalence with Latent Class Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(1), pages 233-255, August.
    12. Wang, Meng-Cheng & Gong, Jie & Gao, Yu & Zhang, Xintong & Yang, Wengdeng & Luo, Jie, 2020. "Variants of psychopathy in Chinese male offenders: A latent profile analysis in a large prison sample," Journal of Criminal Justice, Elsevier, vol. 69(C).
    13. Collart, Alba J. & Palma, Marco A., 2014. "What Motivates Individuals to Participate in Economic Experiments? A Latent Class Analysis with Unobserved Heterogeneity," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170401, Agricultural and Applied Economics Association.
    14. Ribeiro da Silva, Diana & Salekin, Randall T. & Rijo, Daniel, 2019. "Psychopathic severity profiles: A latent profile analysis in youth samples with implications for the diagnosis of conduct disorder," Journal of Criminal Justice, Elsevier, vol. 60(C), pages 74-83.
    15. Palma, Marco A. & Ness, Meghan L. & Anderson, David P., 2015. "Buying More than Taste? A Latent Class Analysis of Health and Prestige Determinants of Healthy Food," 2015 Conference (59th), February 10-13, 2015, Rotorua, New Zealand 202566, Australian Agricultural and Resource Economics Society.
    16. Clara H. Mulder & Michael Wagner, 2001. "The Connections between Family Formation and First-time Home Ownership in the Context of West Germany and the Netherlands," European Journal of Population, Springer;European Association for Population Studies, vol. 17(2), pages 137-164, June.
    17. Krause, Werner & Giebler, Heiko, 2020. "Shifting Welfare Policy Positions: The Impact of Radical Right Populist Party Success Beyond Migration Politics," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 56(3), pages 331-348.
    18. Adrian O’Hagan & Arthur White, 2019. "Improved model-based clustering performance using Bayesian initialization averaging," Computational Statistics, Springer, vol. 34(1), pages 201-231, March.
    19. Shelley H. Liu & Yitong Chen & Jordan R. Kuiper & Emily Ho & Jessie P. Buckley & Leah Feuerstahler, 2024. "Applying Latent Variable Models to Estimate Cumulative Exposure Burden to Chemical Mixtures and Identify Latent Exposure Subgroups: A Critical Review and Future Directions," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 482-502, July.
    20. Gerben ter Riet & Paula Chesley & Alan G Gross & Lara Siebeling & Patrick Muggensturm & Nadine Heller & Martin Umbehr & Daniela Vollenweider & Tsung Yu & Elie A Akl & Lizzy Brewster & Olaf M Dekkers &, 2013. "All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-6, 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:zbw:espost:140878. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .

    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.