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EDUCATIONAL ASSESSMENT & EVALUATION

A Rasch and factor analysis of an Indonesian version of the Student Perception of Opportunity Competence Development (SPOCD) questionnaire

, , , & | (Reviewing editor)
Article: 1721633 | Received 25 Apr 2019, Accepted 18 Jan 2020, Published online: 31 Jan 2020

References

  • Allison, C., Baron-Cohen, S., Stone, M. H., & Muncer, S. J. (2015). Rasch modeling and confirmatory factor analysis of the Systemizing Quotient-Revised (SQ-R) Scale. Spanish Journal of Psychology, 18, 1–18. doi:10.1017/sjp.2015.19
  • Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43, 561–573. doi:10.1007/BF02293814
  • Andrich, D., & Marais, I. (2019). A course in rasch measurement theory: Measuring in the educational, social and health sciences. Singapore: Springer Nature Singapore Pte Ltd.
  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246. doi:10.1037/0033-2909.107.2.238
  • Bond, T., & Fox, C. (2015). Applying the Rasch model: Fundamental measurement in the human sciences (3rd ed.). Mahwah, NJ: Lawrence Erblaum & Associates.
  • Bonne, L., & Lawes, E. (2016). Assessing students’ maths self-efficacy and achievement. Assessment News, 2, 60–63.
  • Brown, A., & Croudace, T. J. (2015). Scoring and estimating score precision using multidimensional IRT models. In S. P. Reise & D. A. Revicki (Eds.), Handbook of item response modeling: Applications to typical performance assessment (pp. 307–333). New York, NY: Routledge.
  • Brown, T., McNamara, O., Hanley, U., & Jones, L. (1999). Primary student teachers’ understanding of mathematics and its teaching. British Educational Research Journal, 25, 299–322. doi:10.1080/0141192990250303
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York, NY: Guilford Press.
  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.
  • Chou, Y.-T., & Wang, W.-C. (2010). Checking dimensionality in item response models with principal component analysis on standardized residuals. Educational and Psychological Measurement, 70, 717–731. doi:10.1177/0013164410379322
  • Christensen, K. B., Makransky, G., & Horton, M. (2017). Critical values for Yen’s Q3: Identification of local dependence in the Rasch model using residual correlations. Applied Psychological Measurement, 41, 178–194. doi:10.1177/0146621616677520
  • Cobb, P., Stephan, M., McClain, K., & Gravemeijer, K. (2001). Participating in classroom mathematical practices. The Journal of Learning Sciences, 10, 113–163. doi:10.1207/S15327809JLS10-1-2_6
  • Das Nair, R., Moreton, B. J., & Lincoln, N. B. (2011). Rasch analysis of the Nottingham extended activities of daily living scale. Journal of Rehabilitation Medicine, 43, 944–950. doi:10.2340/16501977-0858
  • de Ayala, R. J. (2009). The theory and practice of item response theory. New York, NY: Guilford Press.
  • DiStefano, C., & Morgan, G. B. (2010). Evaluation of the BESS TRS-CA using the Rasch rating scale model. School Psychology Quarterly, 25, 202–212. doi:10.1037/a0021509
  • Doran, H. C. (2005). The information function for the one parameter logistic model: Is it reliability? Educational & Psychological Measurement, 65, 665–675. doi:10.1177/0013164404272500
  • Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9, 466–491. doi:10.1037/1082-989X.9.4.466
  • Flora, D. B., & Flake, J. K. (2017). The purpose and practice of exploratory and confirmatory factor analysis in psychological research: Decisions for scale development and validation. Canadian Journal of Behavioural Science, 49, 78–88. doi:10.1037/cbs0000069
  • Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25, 186–192. doi:10.1177/002224378802500207
  • Hiebert, J. (1988). A theory of developing competence with written mathematical symbols. Educational Studies in Mathematics, 19, 333–355. doi:10.1007/BF00312451
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. doi:10.1080/10705519909540118
  • Hudson, B., Henderson, S., & Hudson, A. (2014). Developing mathematical thinking in the primary classroom: Liberating students and teachers as learners of mathematics. Journal of Curriculum Studies, 47, 374–398. doi:10.1080/00220272.2014.979233
  • International Test Commision. (2018)ITC guidelines for translating and adapting tests second edition. International Journal of Testing, 18, 101–134. DOI:10.1080/15305058.2017.1398166
  • Kean, J., Brodke, D. S., Biber, J., & Gross, P. (2018). An introduction to item response theory and Rasch analysis of the Eating Assessment Tool (EAT-10). Brain Impairment, 19, 91–102. doi:10.1017/BrImp.2017.31
  • Kim, S., & Kyllonen, P. C. (2006). Rasch rating scale modeling of data from the standardized letter of recommendation (ETS Research Report RR-06-33). Princeton, NJ: Educational Testing Service.
  • Linacre, J. M. (1998). Detecting multidimensionality: Which residual data-type works best? Journal of Outcome Measurement, 2, 266–283.
  • Linacre, J. M. (2008). WINSTEPS Rasch measurement computer program [Version 3.65.0]. Chicago, IL: Winsteps.com.
  • Linacre, J. M. (2010). Predicting responses from Rasch measures. Journal of Applied Measurement, 11, 1–10.
  • Luo, X., Cappelleri, J. C., Cella, D., Li, J. Z., Charbonneau, C., Kim, S. T., … Motzer, R. J. (2009). Using the Rasch model to validate and enhance the interpretation of the functional assessment of cancer therapy–kidney symptom index—disease-related symptoms scale. Value In Health, 12, 580–586. doi:10.1111/j.1524-4733.2008.00473.x
  • Mair, P. (2018). Modern psychometrics with R. Cham, Switzerland: Springer International Publishing AG.
  • Masters, G. N., & Wright, B. D. (1984). The essential process in a family of measurement models. Psychometrika, 49, 529–544. doi:10.1007/BF02302590
  • Maydeu-Olivares, A., & Joe, H. (2014). Assessing approximate fit in categorical data analysis. Multivariate Behavioral Research, 49, 305–328. doi:10.1080/00273171.2014.911075
  • Ministry of Education of New Zealand. (2007). The New Zealand curriculum. Wellington, NZ: Ministry of Education by Learning Media Limited.
  • Ministry of Education of New Zealand. (2015). Capable kids: Working with the key competencies. Retrieved from https://nzcurriculum.tki.org.nz/Key-competencies/Capable-kids-Working-with-the-key-competencies#collapsible5
  • Mitchell-Parker, K., Medvedev, O. N., Krageloh, C. U., & Siegert, R. J. (2018). Rasch analysis of the frost multidimensional perfectionism scale. Australian Journal of Psychology, 70, 258–268. doi:10.1111/ajpy.2018.70.issue-3
  • Muthén, L. K., & Muthén, B. O. (1998/2017). Mplus user’s guide: Statistical analysis with latent variables ((8th ed.). Los Angeles, CA: Muthén & Muthén.
  • Nasoetion, N., Djalil, A., Musa, I., Soelistyo, S., Choppin, B. H., & Postlethwaithe, T. N. (1976). The development of educational evaluation models in Indonesia. Paris, France: International Institute for Educational Planning.
  • Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen, Denmark: Danish Institute for Educational Research.
  • Smith, E. (2002). Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. Journal of Applied Measurement, 3, 205–231.
  • Swaragita, G. (2018). Indonesian exams ‘too hard’, students ‘want to die’. Retrieved from https://www.thejakartapost.com/news/2018/04/14/indonesian-exams-too-hard-students-want-to-die.html
  • Tait-McCutcheon, S. L. (2014). Teacher practice in primary mathematics classroom: A story of positioning. Doctoral dissertation, Victoria University of Wellington
  • Tennant, A., & Conaghan, P. (2007). The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied, and what should one look for in a Rasch paper? Arthritis Care and Research, 5, 1358–1362. doi:10.1002/art.23108
  • Wihardini, D. (2016). An investigation of the relationship of student performance to their opportunity-to-learn in PISA 2012 mathematics: The case of Indonesia. Doctoral dissertation, University of California: Berkeley
  • Wilson, M., & Draney, K. (2002). A technique for setting standards and maintaining them over time. In S. Nishisato, Y. Baba, H. Bozdogan, & K. Kanefugi (Eds.), Measurement and multivariate analysis (pp. 325–332). Tokyo, Japan: Springer-Verlag.
  • Worldometers. (2019). Indonesia population. Retrieved from https://www.worldometers.info/world-population/indonesia-population/
  • Wright, B. D. (1968). Sample-free test calibration and person measurement. Proceedings of the 1967 Invitational Conference on Testing Problems, (pp. 85–101). Princeton, NJ: Educational Testing Service.
  • Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. Chicago, IL: MESA Press.
  • Yen, W. M. (1984). Effects of local item dependence on the fit and equating performance of the three-parameter logistic model. Applied Psychological Measurement, 8, 125–145. doi:10.1177/014662168400800201
  • Zulkardi, Z., Putri, R. I. I., & Wijaya, A. (2019). Two decades of realistic mathematics education in Indonesia. In M. van den Heuvel-panhuizen (Ed.), International reflections on the Netherlands didactics of mathematics (pp. 325–340). Cham, Switzerland: Springer Nature Switzerland AG.