IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v49y2024i1p3-31.html
   My bibliography  Save this article

Finding the Right Grain-Size for Measurement in the Classroom

Author

Listed:
  • Mark Wilson

    (University of California, Berkeley)

Abstract

This article introduces a new framework for articulating how educational assessments can be related to teacher uses in the classroom. It articulates three levels of assessment: macro (use of standardized tests), meso (externally developed items), and micro (on-the-fly in the classroom). The first level is the usual context for educational measurement, but one of the contributions of this article is that it mainly focuses on the latter two levels. Co-ordination of the content across these two levels can be achieved using the concept of a construct map , which articulates the substantive target property at levels of detail that are appropriate for both teacher planning and within-classroom use. This article then describes a statistical model designed to span these two levels and discusses how best to relate this to the macrolevel. Results from a curriculum and instruction development project on the topic of measurement in the elementary school are demonstrated, showing how they are empirically related.

Suggested Citation

  • Mark Wilson, 2024. "Finding the Right Grain-Size for Measurement in the Classroom," Journal of Educational and Behavioral Statistics, , vol. 49(1), pages 3-31, February.
  • Handle: RePEc:sae:jedbes:v:49:y:2024:i:1:p:3-31
    DOI: 10.3102/10769986231159006
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/10769986231159006
    Download Restriction: no

    File URL: https://libkey.io/10.3102/10769986231159006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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.
    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. 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.
    2. Anja C. Rohenkohl & Monika Bullinger & Andreas M. Pleil & Levente Kriston & Julia H. Quitmann, 2016. "A Brief Version of the Quality of Life in Short Stature Youth Questionnaire - the QoLISSY-Brief," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 9(4), pages 971-984, December.
    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. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.
    5. 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.
    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. Antonio Caronni & Marina Ramella & Pietro Arcuri & Claudia Salatino & Lucia Pigini & Maurizio Saruggia & Chiara Folini & Stefano Scarano & Rosa Maria Converti, 2023. "The Rasch Analysis Shows Poor Construct Validity and Low Reliability of the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 (QUEST 2.0) Questionnaire," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    8. 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.
    9. 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.
    10. Edward Ip & Yuchung Wang & Paul Boeck & Michel Meulders, 2004. "Locally dependent latent trait model for polytomous responses with application to inventory of hostility," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 191-216, June.
    11. Chen-Wei Liu & R Philip Chalmers, 2018. "Fitting item response unfolding models to Likert-scale data using mirt in R," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-22, May.
    12. Janna Niens & Lisa Richter-Beuschel & Tobias C. Stubbe & Susanne Bögeholz, 2021. "Procedural Knowledge of Primary School Teachers in Madagascar for Teaching and Learning towards Land-Use- and Health-Related Sustainable Development Goals," Sustainability, MDPI, vol. 13(16), pages 1-36, August.
    13. 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.
    14. Marko Böhm & Jan Barkmann & Sabina Eggert & Claus H. Carstensen & Susanne Bögeholz, 2020. "Quantitative Modelling and Perspective Taking: Two Competencies of Decision Making for Sustainable Development," Sustainability, MDPI, vol. 12(17), pages 1-32, August.
    15. Salzberger, Thomas & Newton, Fiona J. & Ewing, Michael T., 2014. "Detecting gender item bias and differential manifest response behavior: A Rasch-based solution," Journal of Business Research, Elsevier, vol. 67(4), pages 598-607.
    16. Rasmus A. X. Persson, 2023. "Theoretical evaluation of partial credit scoring of the multiple-choice test item," METRON, Springer;Sapienza Università di Roma, vol. 81(2), pages 143-161, August.
    17. 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.
    18. 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.
    19. 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.
    20. Maren M. Michaelsen, 2012. "Mental Health and Labour Supply: Evidence from Mexico’s Ongoing Violent Conflicts," HiCN Working Papers 117, Households in Conflict Network.

    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:sae:jedbes:v:49:y:2024:i:1:p:3-31. 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: SAGE Publications (email available below). General contact details of provider: .

    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.