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Estimation of Heterogeneous SubjectItem Parameters
k Optimization Procedure for an Adaptive Teaching System
Design of a Computer Controlled Learning Experiment
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adaptive optimization procedure adaptive teaching system algorithm Analysis of Variance AOP and RCP assumption average composite parameter Correct on Study Correct on Test correct response curves decision process denote difference between AOP differences between procedures Doctor of Philosophy dynamic programming E[Aq Efficiency Quotients error probability Figure given Groen and Atkinson instructional process item and subject item components item difficulty item parameter estimation iteration Kaupe late retention test learning process likelihood function linear model Low group Mathematical Psychology MIP-procedure Monte-Carlo experiments number of items OEM-procedure one-element model optimal policy optimization strategies parameter values presentation procedures Proportion Correct quasi-additive reinforcement response latency response sequence RTI-model selected selection algorithm Smallwood 1967 stage Stanford University student Study Sessions study-sessions subject and item subject components subject parameters sufficient history Swahili Table test days Test Sessions test-sessions trial TS-session updating utility function Variance of Latencies variation SS df