How to Make an Assessment More Informative and Interpretable Using the Ordered Partition Model
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As an extension of the partial credit model (PCM), the ordered partition model (Wilson, 1992; OPM) is designed for the measurement context in which different strategies might lead to the same score on an assessment. In the diagnostic context, the data would neither be nominal nor completely ordered, and so it may not be suitable for other polytomous item responses models. The OPM, however, does deal with this type of data (Wilson, 1992). This paper demonstrates how the OPM can help make assessments more informative. To help readers understand the OPM, the PCM and its relationship with the OPM is first described, then, the interpretation of OPM parameters is explained by showing the OPM results with two illustrative data sets: the ‘Using Evidence’ data and the ‘PISA 2003 science assessment’ data.
Abstract
As an extension of the partial credit model (PCM), the ordered partition model (Wilson, 1992; OPM) is designed for the measurement context in which different strategies might lead to the same score on an assessment. In the diagnostic context, the data would neither be nominal nor completely ordered, and so it may not be suitable for other polytomous item responses models. The OPM, however, does deal with this type of data (Wilson, 1992). This paper demonstrates how the OPM can help make assessments more informative. To help readers understand the OPM, the PCM and its relationship with the OPM is first described, then, the interpretation of OPM parameters is explained by showing the OPM results with two illustrative data sets: the ‘Using Evidence’ data and the ‘PISA 2003 science assessment’ data.
참고문헌 (21)
- Quest. Melbourne, "Adams, R. J.", Australian Council for Educational Research., ~ (1996)
- Andersen, E. B, "A general latent structure model for contingency table data, in Principals of modern psychological measurement", pp.117~138 (1983), Erlbaum
- Andrich, D, "A rating formulation for ordered response categories", Psychometirka, 43(4), pp.561~578 (1978)
- Bell, B., "The Characteristics of Formative Assessment in Science Education", Assessment in Education, 6, pp.101~115 (2000)
- Black, P, "Formative assessment and the improvement of learning", Journal of Special Education, 23(2), pp.51~56 (1996)
- Black, P, "Assessment and classroom learning", Assessment in Education, 5(1), pp.7~74 (1998)
- Brookhart, S. M, "Classroom assessment: Tensions and intersections in theory and practice", Teachers College Record, 106(3), pp.429~458 (2004)
- Interpreting ordered partition model parameters from ConQuest, "Brown, N. J. S", Berkeley Evaluation & Assessment Research Center, ~ (2004)
- Proposal for Using Evidence project: An Analysis of US and German Science Teaching and Learning, "Brown, N. J. S", ~ (2004)
- Embretson, S. E., "Item Response Theory for Psychologists" (2000), Lawrence Erlbaum Associates
- The nature and impact of teachers’ formative assessment practices, "Herman, J. L.", CSE, ~, pp.CSE Technical report 703. (2006)
- Masters, G. N, "A Rasch model for partial credit scoring", Psychometrika, 47(2), pp.149~174 (1982)
- Messick, S, "The psychology of educational measurement", Journal of Educational Measurement, 21(3), pp.215~237 (1984)
- Mislevy, R. J., "Modeling item responses when different subjects employ different solution strategies", Psychometrika, 55(2), pp.195~215 (1990)
- Sadler, D. R, "Formative assessment and the design of instructional systems", Instructional Science, 18(2), pp.119~144 (1989)
- Sadler, D. R, "Formative assessment: revisiting the territory", Assessment in Education, 5(1), pp.77~84 (1989)
- Tierney, R., "Stocks and prospects: Research on formative assessment in secondary classrooms", presented in the annual meeting of AERA (2007)
- William, D, "Keeping learning on track: Classroom assessment and the regulation of learning, in Second Handbook of Research on Mathematics Teaching and Learning", pp.1051~1098 (2007), National Council of Teachers of Mathematics
- Wilson, M, "The ordered partition model: An extension of the partial credit model", Applied Psychological Measurement, 16(4), pp.309~325 (1992)
- Wilson, M., "Marginal maximum likelihood estimation for the ordered partition model", Journal of Education Statistics, 18(1), pp.69~90 (1993)
- Wu, M. L., "ACER ConQuest user guide" (1998), ACER Press