Una investigación de la mejora de la capacidad de evaluación mediante el uso de un modelo logit anidado para items de elección múltiple.

Autores/as

  • Tour Liu Collaborative Innovation Center of Assessment toward Basic Education Quality (CICA-BEQ), Bejing Normal University
  • Mengcheng Wang Center for Psychometric and Latent Variable Modeling, Guangzhou University, Guangzhou
  • Tao Xin School of Education Science, Tianjin Normal University, Tianjin
DOI: https://doi.org/10.6018/analesps.33.3.238621
Palabras clave: items de elección múltiple, modelo logit anidado, información distractora, capacidad de evaluación.

Resumen

Los items de elección múltiple se han usado ampliamente en tests psicológicos y educativos. Este estudio investiga si los items de elección múltiple tiene ventajas sobre los items dicotómicos o sobre la evaluación de rasgo latente. Un modelo de respuesta al item, con un modelo logit anidado, logístico 2-parámetros (2PL-NKM), fue usado para ajustar los datos de elección múltiple. Los estudios de simulación y empíricos indicaron que la precisión y la estabilidad de la estimación de capacidad mejoró usando el modelo de elección múltiple en contraposición al modelo dicotómico, debido a la mayor información incluida en los items distractores de la elección múltiple. Pero la precisión y la capacidad de estimación mostró pequeñas diferencias en items de cuatro elecciones, cinco y seis elecciones. Además, el modelo 2PL-NLM puede extraer más información respondientes de bajo nivel que de los de alto nivel, debido a que tienen conductas de elección con más distractores. En el estudio empírico, los respondientes en diferentes niveles de rasgo fueron atraídos por diferentes distractrores del Test de Vocabulario chino en el primer grado, usando trazos cambiantes en la probabilidad de distractor a partir de 2PL-NLM. Esto sugiere que las respuestas de los estudiantes a diferentes niveles puede reflejar un proceso evolutivo de vocabulario en los estudiantes.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Attali, Y., & Fraenkel, T. (2000). The Point-Biserial as a Discrimination Index for Distractors in Multiple-Choice Items:Deficiencies in Usage and an alternative. Journal of Educational Measurement, 37(1), 77-86. doi: 10.1111/j.1745-3984.2000.tb01077.x

Bock, R. D. (1972). Estimating item parameters and latent ability when responses are scored in two or more nominal categories. Psychometrika, 37, 29-51.doi: 10.1007/BF02291411

Bolt, D. M., Wollack, J. A., &Suh, Y. (2012). Application of a multidimensional nested logit model to multiple-choice test items. Psychometrika, 77, 339-357.doi: 10.1007/S11336-012-9257-5

Briggs, D. C., Alonzo, A. C., Schwab, C., & Wilson, M. (2006). Diagnostic assessment with ordered multiple-choice items. Educational Assessment, 11, 33-63.doi: 10.1207/s15326977ea1101_2

Cao, Y. W. (1999). Construction of vocabulary tests for junior school level. Acta Psychologica Sinica, 31, 460-467.

Davis, F. B., & Fifer, G. (1959). The effect on test reliability and validity of scoring aptitude and achievement tests with weights for every choice. Educational and Psychological Measurement, 19, 159-170.doi: 10.1177/001316445901900202

Divgi, D. R. (1986). Does the Rasch model really work for multiple choice items? Not if you look closely. Journal of Educational Measurement, 23, 283-298.doi: 10.1111/j.1745-3984.1986.tb00251.x

Drasgow, F., Levine, M. V., & Williams, E. A. (1985). Appropriateness Measurement with Polychotomous Item Response Models and Standardized Indices. British Journal of Mathematical and Statistical Psychology, 38, 67-86. doi: 10.1111/j.2044-8317.1985.tb00817.x

Embretson, S. E., & Reise, S. P. (2000). Item Response Theory for Psychologists. Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc.

Green, B. F., Crone, C. R., & Folk, V. G. (1989). A Method for Studying Differential Distractor Functioning. Journal of Educational Measurement, 26, 147-160.doi: 10.1111/j.1745-3984.1989.tb00325.x

Haladyna, T. M., & Downing, S. M. (1989). A Taxonomy of Multiple-Choice Item-Writing Rules. Applied Measurement in Education, 2, 37-50.doi: 10.1207/s15324818ame0201_3

Haladyna, T. M., & Downing, S. M. (1993). How Many Options is Enough for a Multiple-Choice Testing Item. Educational and Psychological Measurement, 53, 999-1010.doi: 10.1177/0013164493053004013

Haladyna, T. M., Downing, S. M., & Rodriguez, M. C. (2002). A Review of Multiple-Choice Item-Writing Guidelines for Classroom Assessment. Applied Measurement in Education, 15, 309-333.doi: 10.1207/S15324818AME1503_5

Henning, G. (1989). Does the Rasch model really work for multiple-choice items? Take another look: a response to Divgi. Journal of Educational Measurement, 26, 91-97.doi: 10.1111/j.1745-3984.1989.tb00321.x

Hofmann, K. P. (2007). Psychology of Decision Making in Economics, Business and Finance. Nova Publishers.

Jacobs, P. I., &Vandeventer, M. (1970). Information in wrong responses. Psychological Reports, 26, 311-315.doi: 10.2466/pr0.1970.26.1.311

Kim, J. (2006). Using the Distractor Categories of Multiple-Choice Items to Improve IRT Linking. Journal of Educational Measurement, 43, 193-213.doi: 10.1111/j.1745-3984.2006.00013.x

Levine, M. V., &Drasgow, F. (1983). The relation between incorrect option choice and estimated ability. Educational and Psychological Measurement, 43, 675-685.doi: 10.1177/001316448304300301

Liu, O. L., Lee, H., & Linn, M. C. (2011). An investigation of explanation multiple-choice items in science assessment. Educational Assessment, 16, 164-184.doi: 10.1080/10627197.2011.611702

Love, T. E. (1997). Distractor selection ratios. Psychometrika, 62, 51-62.doi: 10.1007/BF02294780

Luecht, R. M. (2007). Using information from multiple-choice distractors to enhance cognitive-diagnostic score reporting. In J. P. Leighton &M. J. Gierl (Eds.),Cognitive diagnostic assessment for education: Theory and practices(pp. 319–340). Cambridge University Press.doi: 10.1017/CBO9780511611186

Muraki, E. (1992). A Generalized Partial Credit Model:Application of an EM Algorithm. Applied Psychological Measurement, 16, 159-176.doi: 10.1002/j.2333-8504.1992.tb01436.x

Penfield, R. D. (2011). How are the Form and Magnitude of DIF Effects in Multiple-Choice Items Determined by Distractor-Level Invariance Effects?. Educational And Psychological Measurement, 71, 54-67.doi: 10.1177/0013164410387340

Roediger III, H. L., & Marsh, E. J. (2005). The positive and negative consequences of multiple-choice testing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31, 1155.doi: 10.1037/0278-7393.31.5.1155

Sadler, P. M. (1998). Psychometric models of student conceptions in science: Reconciling qualitative studies and distractor-driven assessment instruments. Journal of Research in science Teaching, 35, 265-296.doi: 10.1002/(SICI)1098-2736(199803)35:3<265::AID-TEA3>3.0.CO;2-P

Sigel, I. E. (1963). How intelligence tests limit understanding of intelligence. Merrill-Paker Quarterly,9, 39-56.

Suh, Y., & Bolt, D. M. (2010). Nested logit models for multiple-choice item response data. Psychometrika, 75, 454-473.doi: 10.1007/s11336-010-9163-7

Suh, Y., & Bolt, D. M. (2011). A Nested Logit Approach for Investigating Distractors as Cause of Different Item Functioning. Journal of Educational Measurement, 48, 188-205.doi: 10.1111/j.1745-3984.2011.00139.x

Suh, Y., & Talley, A. E. (2015). An Empirical Comparison of DDF Detection Methods for Understanding the Causes of DIF in Multiple-Choice Items. Applied Measurement in Education, 28, 48-67.doi: 10.1080/08957347.2014.973560

Tamir, P. (1971). An alternative approach to the construction of multiple choice test items. Journal of Biological Education, 5, 305-307.doi: 10.1080/00219266.1971.9653728

Tamir, P. (1989). Some issues related to the use of justifications to multiple-choice answers. Journal of Biological Education, 23, 285-292.doi: 10.1080/00219266.1989.9655083

Thissen, D. M. (1976). Information in wrong responses to the Raven Progressive Matrices. Journal of Educational Measurement, 13, 201-214.doi: 10.1111/j.1745-3984.1976.tb00011.x

Thissen, D., & Steinberg, L. (1984). A Response Model for Multiple Choice Items. Psychometrika, 49, 501-519.doi: 10.1007/BF02302588

Thissen, D., Steinberg, L., & Fitzpatrick, A. R. (1989). Multiple-Choice Models: The Distractors Are Also Part of the Item. Journal of Educational Measurement, 26, 161-176.doi: 10.1111/j.1745-3984.1989.tb00326.x

Walther B. A., & Moore J. L. (2005). The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography, 28, 815-829. doi: 10.1111/j.2005.0906-7590.04112.x

Wollack, J. A. (1997). A Nominal Response Model Approach for Detecting Answer Copying. Applied Psychological Measurement, 21, 307-320.doi: 10.1177/01466216970214002

Publicado
21-07-2017
Cómo citar
Liu, T., Wang, M., & Xin, T. (2017). Una investigación de la mejora de la capacidad de evaluación mediante el uso de un modelo logit anidado para items de elección múltiple. Anales de Psicología / Annals of Psychology, 33(3), 530–537. https://doi.org/10.6018/analesps.33.3.238621
Número
Sección
Multidisciplinar