Towards a pragmatic visionof measument in education
Hacia una visión pragmática de la medición en Educación
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Ovalle Ramírez , C. P. (2025). Towards a pragmatic visionof measument in education. Tempus Psicológico, 8(1). https://doi.org/10.30554/tempuspsi.8.1.5161.2025
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How to Cite
Ovalle Ramírez , C. P. (2025). Towards a pragmatic visionof measument in education. Tempus Psicológico, 8(1). https://doi.org/10.30554/tempuspsi.8.1.5161.2025
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This article introduces the reader to the pragmatic perspective of measurement that goes beyond the traditional view of measurement as assigning numbers (Stevens, 1958). The educator has to consider the measurement process and the assumptions (theoretical and psychometric) that he or she has regarding that process in order for the measurement to be valid and actionable. In addition, measurement should shift from focusing on normally distributed continuous variables to the use of measures such as ordinals and nominal that allow us to address other phenomena of interest such as levels of progression and improvement. Finally, an example is presented with the pragmatic measurement of 21st century skills.
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- Birnbaum, A. (1957). Efficient design and use of tests of a mental ability for various decision-making problems. USAF School of Aviation Medicine.
- Bock, R. D. (1972). Estimating item parameters and latent ability when responses are scored in two or more nominal categories. Psychometrika, 37, 29-51. https://doi.org/10.1007/BF02291411
- Box, G. (1979). Robustness in the strategy of scientific model building. En Launer, R. L.; Wilkinson, G. N. (Eds.), Robustness in Statistics. Academic Press.
- Briggs, D. (2021). Book review: A pragmatic perspective of measurement by David Torres Irribarra. Integrative Psychological and Behavioral Science, 56(1), 1-10. https://doi.org/10.1007/s12124-021-09635-7
- Diakow, R., Torres-Irribarra, D. & Wilson, M. (2014). Some Comments on Representing Construct Levels in Psychometric Models. En: Millsap R.E., van der Ark L.A., Bolt D.M., Woods C.M. (Eds). New Developments in Quantitative Psychology. Springer Proceedings in Mathematics & Statistics. Springer.
- Duncan, R. & Suppes, P. (2002). Representational Measurement Theory. En H. Pashler & J. Wixted (Eds.), Stevens’ Handbook of Experimental Psychology (pp. 1-41). John Wiley & Sons, Inc.
- Formann, A. (1995). Linear logistic latent class analysis. En G. H. Fischer & I. W. Molenaar. Rasch models: Foundations, recent developments, and applications (pp. 239–256). New York: Springer.
- Franz, D. (2021). Are psychological attributes quantitative? is not an empirical question: Conceptual confusions in the measurement debate. Theory & Psychology, 1(1), 1–20. https://doi.org/10.1177/09593543211045340
- Green, C. (2001). Operationism again: What did Bridgman say? What did Bridgman need?. Theory & Psychology, 11(1), 45–51 https://doi.org/10.1177/0959354301111003
- Griffin, P. & Care, E. (2015). Assessment and teaching of XXI century skills. Springer. Hontagas, P., Ponsoda, V., Olea, J. & Revuelta, J. (1998). Representación de funciones características de ítems dicotómicos y politómicos. Psicothema, 10(2), 475-479. https://www.psicothema.com/contenido?num=19981002
- Lindsay, B, Clogg, C. & Grego, J. (1991). Semiparametric estimation in the Rasch model and related exponential response models, including a simple latent class model for item analysis. Journal of the
- American Statistical Association, 86(413), 96–107 https://www.tandfonline.com/doi/abs/10.1080/01621459.1991.10475008
- López-Pina, J. (2005). Ítems politómicos vs. dicotómicos: un estudio metodológico. Anales de Psicología, 21(2), 339-344. https://revistas.um.es/analesps/article/view/26941
- Mari, L., Maul, A., Torres-Irribarra, D. & Wilson, M. (2017). Quantities, Quantification, and the Necessary and Sufficient Conditions for Measurement. Measurement, 100, 115-121. http://dx.doi.org/10.1016/j.measurement.2016.12.050
- Masters, G. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149-174. https://doi.org/10.1007/BF02296272
- Maul, A., Mari, L., Torres Irribarra, D. & Wilson, M. (2018). The quality of measurement results in terms of the structural features of the measurement process. Measurement, 116, 611-620. https://doi.org/10.1016/j.measurement.2017.08.046
- Michell, J. (1997). Quantitative science and the definition of measurement in psychology. British Journal of Psychology, 88(3), 355–383. https://doi.org/10.1111/j.2044-8295.1997.tb02641.x
- Michell, J. (2003). The quantitative imperative: Positivism, naïve realism and the place of qualitative methods in psychology. Theory & Psychology, 13(1), 5–31. https://doi.org/10.1177/0959354303013001758
- National Research Council [NRC]. (2001). Knowing what students know: the science and design of educational assessment. National Academy Press. https://nap.nationalacademies.org/catalog/10019/knowing-what-students-know-the-science-and designof-educational#toc
- Rasch, G. (1960). Studies in mathematical psychology: I. Probabilistic models for some intelligence and attainment tests. Nielsen & Lydiche.
- Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monographs, 17, 1-169 https://onlinelibrary.wiley.com/doi/pdf/10.1002/j.2333-8504.1968.tb00153.x
- Spearman, C. (1904). The proof and measurement of association between two things. The American Journal of Psychology, 15(1), 72–101. https://pubmed.ncbi.nlm.nih.gov/3322052/
- Stevens, S. (1958). Measurement and man. Science, 127(3295), 383–389. https://doi.org/10.1126/science.127.3295.383
- Tafreshi, D., Slaney, K. & Neufeld, S. (2016). Quantification in psychology: Critical analysis of an unreflective practice. Journal of Theoretical and Philosophical Psychology, 36(4), 233-249. https://doi.org/10.1037/teo0000048
- Torres-Irribarra, D. (2020). A pragmatic perspective on measurement. Springer Briefs in Psychology.
- Trendler, G. (2009). Measurement theory, psychology and the revolution that cannot happen. Theory & Psychology, 19(5), 579–599. https://doi.org/10.1177/0959354309341926
- Trendler, G. (2013). Measurement in psychology: A case of ignoramus et ignorabimus? A rejoinder. Theory & Psychology, 23(5), 591–615. https://doi.org/10.1177/0959354313490451
- Uher, J. (2020). Measurement in metrology psychology and social sciences: data generation traceability and numerical traceability as basic methodological principles applicable across sciences. Quality and Quantity, 54(3), 975–1004. https://doi.org/10.1007/s11135-020-00970-2
- Valsiner, J. (2012). La dialéctica en el estudio del desarrollo. En M. Carretero & J. A. Castorina, (Eds.). Desarrollo cognitivo y educación. Los inicios del conocimiento (pp. 137-157). Buenos Aires: Paidós.
- Wang, W. C. & Wilson, M. (2005). The Rasch testlet model. Applied Psychological Measurement 29(2), 126–149. https://doi.org/10.1177/0146621604271053
- Wilson, M., Bejar, I., Scalise, K., Templin, J., Dylan, W. & Torres-Irribarra, D. (2012). Perspectives on Methodological issues. En Griffin P. & Care E. (Eds.). Assessment and Teaching of 21st Century Skills. Springer.
- Wilson, M. & Sloane, K. (2000). From Principles to Practice: An Embedded Assessment System. Applied Measurement in Education, 13(2), 181-208. https://doi.org/10.1207/S15324818AME1302_4
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