Modeling item responses when different subjects employ different solution strategies

A model is presented for item responses when different subjects employ different strategies, but only responses, not choice of strategy, can be observed. Using substantive theory to differentiate the likelihoods of response vectors under a fixed set of strategies, we model response probabilities in terms of item parameters for each strategy, proportions of subjects employing each strategy, and distributions of subject proficiency within strategies. The probabilities that an individual subject employed the various strategies can then be obtained, along with a conditional estimate of proficiency under each. A conceptual example discusses response strategies for spatial rotation tasks, and a numerican example resolves a population of subjects into subpopulations of valid responders and random guessers.

[1]  Robert J. Mislevy,et al.  BILOG 3 : item analysis and test scoring with binary logistic models , 1990 .

[2]  Mark Wilson Saltus: A psychometric model of discontinuity in cognitive development. , 1989 .

[3]  Robert K. Tsutakawa,et al.  Approximation for Bayesian Ability Estimation , 1988 .

[4]  A. F. Smith,et al.  Statistical analysis of finite mixture distributions , 1986 .

[5]  Norman Verhelst,et al.  Maximum Likelihood Estimation in Generalized Rasch Models , 1986 .

[6]  Robert J. Mislevy,et al.  Bayes modal estimation in item response models , 1986 .

[7]  James A. Paulson Latent Class Representation of Systematic Patterns in Test Responses , 1986 .

[8]  M. Just,et al.  Cognitive coordinate systems: accounts of mental rotation and individual differences in spatial ability. , 1985, Psychological review.

[9]  Randall J. Mumaw,et al.  3 – Analyses of Spatial Aptitude and Expertise , 1985 .

[10]  Samuel Messick,et al.  The Psychology of Educational Measurement. , 1984 .

[11]  Patrick C. Kyllonen,et al.  Effects of Aptitudes, Strategy Training, and Task Facets on Spatial Task Performance. , 1984 .

[12]  K. Tatsuoka RULE SPACE: AN APPROACH FOR DEALING WITH MISCONCEPTIONS BASED ON ITEM RESPONSE THEORY , 1983 .

[13]  R. Kail,et al.  Algorithms for processing spatial information. , 1983, Journal of experimental child psychology.

[14]  F. Samejima A Latent Trait Model for Differential Strategies in Cognitive Processes. , 1983 .

[15]  Fritz Drasgow,et al.  Item response theory : application to psychological measurement , 1983 .

[16]  S. Embretson,et al.  Component Latent Trait Models for Test Design. , 1982 .

[17]  D. Gentner,et al.  Flowing waters or teeming crowds: Mental models of electricity , 1982 .

[18]  T. Louis Finding the Observed Information Matrix When Using the EM Algorithm , 1982 .

[19]  R. Siegler Developmental Sequences within and between Concepts. , 1981 .

[20]  D. Lohman Spatial Ability: A Review and Reanalysis of the Correlational Literature. , 1979 .

[21]  M. Bryden,et al.  An investigation of sex differences in spatial ability: mental rotation of three-dimensional objects. , 1977, Canadian journal of psychology.

[22]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[23]  James O. Ramsay,et al.  Solving implicit equations in psychometric data analysis , 1975 .

[24]  Ledyard R Tucker,et al.  The distribution of chance congruence coefficients from simulated data , 1975 .

[25]  G. H. Fischer,et al.  The linear logistic test model as an instrument in educational research , 1973 .

[26]  M. Powell Lawton,et al.  The psychology of adult development and aging , 1973 .

[27]  R. Shepard,et al.  CHRONOMETRIC STUDIES OF THE ROTATION OF MENTAL IMAGES , 1973 .

[28]  John W. French,et al.  The Relationship of Problem-Solving Styles to the Factor Composition of Tests1 , 1965 .

[29]  John W. French,et al.  THE RELATIONSHIP OF PROBLEM-SOLVING STYLES TO THE FACTOR COMPOSITION OF TESTS , 1963 .

[30]  P. Mussen The psychological development of the child , 1963 .

[31]  B. Inhelder,et al.  Discussions on Child Development , 1961 .