IDEAS home Printed from https://ideas.repec.org/a/nos/voprob/2020i4p8-36.html

Checking the Possibility of an International Comparative Study of Reading Literacy Assessment for Children Starting School

Author

Abstract

Alina Ivanova - Research Fellow, Center for Psychometrics and Measurements in Education, Institute of Education, National Research University Higher School of Economics. E-mail: aeivanova@hse.ruElena Kardanova - Candidate of Sciences in Mathematical Physics, Associate Professor, Tenured Professor, Director of the Center for Psychometrics and Measurements in Education, Institute of Education, National Research University Higher School of Economics. E-mail: ekardanova@hse.ruAddress: Bld. 10, 16 Potapovsky Lane, 101000 Moscow, Russian Federation.The early years of school, when a child is only learning to read, are critically important for later development and learning. Cross-cultural comparative assessments of reading literacy provide a rich source of data for researchers, practitioners and politicians on the opportunities and prospects of early childhood development in different countries, circumstances and contexts. There are few publications of this sort available, and none of them has involved Russian-speaking children on entry to school so far.Data obtained using two language versions of the International Performance Indicators in Primary Schools (iPIPS) on representative samples of first-graders from the Republic of Tatarstan and Scotland is used to compare the early reading assessment results between children starting school in countries with linguistic, cultural, and school entry age differences.Two studies are conducted to analyze the possible methods of comparing assessment results of children from different countries in the absence of a common measurement scale. The first study uses the rank-ordering method to establish a correspondence between the levels of reading literacy among Russian- and English-speaking children by expert judgment. In the second study, the obtained model of literacy levels is used to establish the cut-off scores (benchmarks) of student assessment outcomes.

Suggested Citation

  • Alina Ivanova & Elena Kardanova, 2020. "Checking the Possibility of an International Comparative Study of Reading Literacy Assessment for Children Starting School," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 8-36.
    • Handle: RePEc:nos:voprob:2020:i:4:p:8-36
    as

    Download full text from publisher

    File URL: https://vo.hse.ru/data/2021/01/03/1344142810/Ivanova,%20Kardanova%20ENG.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. Liu, Ji & Steiner-Khamsi, Gita, 2020. "Human Capital Index and the hidden penalty for non-participation in ILSAs," International Journal of Educational Development, Elsevier, vol. 73(C).
    3. Elena Kardanova & Alina Ivanova & Pavel Sergomanov & Tatjana Kanonire & Inna Antipkina & Diana Kayky, 2018. "Patterns of First-Graders' Development at the Start of Schooling: Cluster Approach Based on the Results of iPIPS Project," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 1, pages 8-37.
    Full references (including those not matched with items on IDEAS)

    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. Иванова А. Е. & Карданова Е. Ю., 2020. "Изучение Возможности Проведения Межстранового Сравнительного Исследования Навыка Чтения У Учащихся На Входе В Школу," Вопросы образования // Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 8-36.
    2. César Merino-Soto & Gina Chávez-Ventura & Verónica López-Fernández & Guillermo M. Chans & Filiberto Toledano-Toledano, 2022. "Learning Self-Regulation Questionnaire (SRQ-L): Psychometric and Measurement Invariance Evidence in Peruvian Undergraduate Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    3. Roberto Burro & Riccardo Sartori & Giulio Vidotto, 2011. "The method of constant stimuli with three rating categories and the use of Rasch models," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(1), pages 43-58, January.
    4. Chang, Hsin-Li & Yang, Cheng-Hua, 2008. "Explore airlines’ brand niches through measuring passengers’ repurchase motivation—an application of Rasch measurement," Journal of Air Transport Management, Elsevier, vol. 14(3), pages 105-112.
    5. Luo, Nanyu & Ji, Feng & Han, Yuting & He, Jinbo & Zhang, Xiaoya, 2024. "Fitting item response theory models using deep learning computational frameworks," OSF Preprints tjxab, Center for Open Science.
    6. Ivana Bassi & Matteo Carzedda & Enrico Gori & Luca Iseppi, 2022. "Rasch analysis of consumer attitudes towards the mountain product label," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-25, December.
    7. Hua-Hua Chang, 1996. "The asymptotic posterior normality of the latent trait for polytomous IRT models," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 445-463, September.
    8. Curt Hagquist & Raili Välimaa & Nina Simonsen & Sakari Suominen, 2017. "Differential Item Functioning in Trend Analyses of Adolescent Mental Health – Illustrative Examples Using HBSC-Data from Finland," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 10(3), pages 673-691, September.
    9. Hoben, Matthias & Kilmen, Sevilay & Keefe, Janice & O'Rourke, Hannah M. & Banerjee, Sube & Estabrooks, Carole A., 2025. "Measurement invariance and differential item functioning of a care staff proxy measure of nursing home resident dementia-specific quality of life (DEMQOL-CH): do care aides' first language, and care aides' and residents’ ethno-cultural background mat," Social Science & Medicine, Elsevier, vol. 375(C).
    10. Thilo J. Ketschau & Janne Kleinhans, 2019. "Concept and Implementation of a Two-Stage Coding Scheme for the Development of Computer-Based Testing (CBT)-Items in Traditional Test Software," J, MDPI, vol. 2(1), pages 1-9, January.
    11. David J. Hessen, 2023. "Fitting and Testing Log-Linear Subpopulation Models with Known Support," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 917-939, September.
    12. Chang, Hsin-Li & Wu, Shun-Cheng, 2008. "Exploring the vehicle dependence behind mode choice: Evidence of motorcycle dependence in Taipei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(2), pages 307-320, February.
    13. C. Glas & Anna Dagohoy, 2007. "A Person Fit Test For Irt Models For Polytomous Items," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 159-180, June.
    14. Stephen Reder, 2023. "Adults’ reading engagement and wellbeing in Aotearoa New Zealand," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-20, September.
    15. repec:plo:pone00:0155895 is not listed on IDEAS
    16. Jesper Tijmstra & Maria Bolsinova, 2019. "Bayes Factors for Evaluating Latent Monotonicity in Polytomous Item Response Theory Models," Psychometrika, Springer;The Psychometric Society, vol. 84(3), pages 846-869, September.
    17. Salzberger, Thomas & Koller, Monika, 2013. "Towards a new paradigm of measurement in marketing," Journal of Business Research, Elsevier, vol. 66(9), pages 1307-1317.
    18. Joakim Wallmark & James O. Ramsay & Juan Li & Marie Wiberg, 2024. "Analyzing Polytomous Test Data: A Comparison Between an Information-Based IRT Model and the Generalized Partial Credit Model," Journal of Educational and Behavioral Statistics, , vol. 49(5), pages 753-779, October.
    19. Fumiko Samejima, 1995. "Acceleration model in the heterogeneous case of the general graded response model," Psychometrika, Springer;The Psychometric Society, vol. 60(4), pages 549-572, December.
    20. Richard N McNeely & Salissou Moutari & Samuel Arba-Mosquera & Shwetabh Verma & Jonathan E Moore, 2018. "An alternative application of Rasch analysis to assess data from ophthalmic patient-reported outcome instruments," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-32, June.
    21. Efstratopoulou, Maria & Opoku, Maxwell Peprah & Tsingilis, Nikolaos & Nur, Shakila & Gyimah, Ebenezer Mensah & Moustafa, Ashraf, 2025. "Validating a parental trauma informed approaches scale in Low-Income countries using the Rasch model," Children and Youth Services Review, Elsevier, vol. 179(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:nos:voprob:2020:i:4:p:8-36. 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: Marta Morozova (email available below). General contact details of provider: http://vo.hse.ru/en/ .

    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.