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1. The Use of the Graded Response Model in Computerized Adaptive Testing of the Attitudes to Science Scale.

Author

Foong, Yoke-Yeen and Lam, Tit-Loong

Abstract

The graded response model for two-stage testing was applied to an attitudes toward science scale using real-data simulation. The 48-item scale was administered to 920 students at a grade-8 equivalent in Singapore. A two-stage 16-item computerized adaptive test was developed. In two-stage testing an initial, or routing, test is followed by a second-stage testlet of greater or lesser difficulty based on performance. A conventional test of the same length as the adaptive two-stage test was selected from the 48-item pool. Responses to the conventional test, the routing test, and a testlet were simulated. The algorithm of E. Balas (1965) and the multidimensional knapsack problem of optimization theory were used in test development. The simulation showed the efficiency and accuracy of the two-stage test with the graded response model in estimating attitude trait levels, as evidenced by better results from the two-stage test than its conventional counterpart and the reduction to one-third of the length of the original measure. Six tables and three graphs are included. (SLD)

Published
1991

2. Simulation-based decision support framework for dynamic ambulance redeployment in Singapore.

Author

Lam, Sean Shao Wei, Ng, Clarence Boon Liang, Nguyen, Francis Ngoc Hoang Long, Ng, Yih Yng, and Ong, Marcus Eng Hock

Subjects
*EMERGENCY medical services, *AMBULANCE service, *DYNAMIC programming, *DECISION support systems, *COMPUTER simulation, *ALGORITHMS, *AMBULANCES, *MATHEMATICAL models, *QUALITY assurance, *RESOURCE allocation, *TIME, *THEORY, *STANDARDS
Abstract

Objective: Dynamic ambulance redeployment policies tend to introduce much more flexibilities in improving ambulance resource allocation by capitalizing on the definite geospatial-temporal variations in ambulance demand patterns over the time-of-the-day and day-of-the-week effects. A novel modelling framework based on the Approximate Dynamic Programming (ADP) approach leveraging on a Discrete Events Simulation (DES) model for dynamic ambulance redeployment in Singapore is proposed in this paper.Methods: The study was based on the Singapore's national Emergency Medical Services (EMS) system. Based on a dataset comprising 216,973 valid incidents over a continuous two-years study period from 1 January 2011-31 December 2012, a DES model for the EMS system was developed. An ADP model based on linear value function approximations was then evaluated using the DES model via the temporal difference (TD) learning family of algorithms. The objective of the ADP model is to derive approximate optimal dynamic redeployment policies based on the primary outcome of ambulance coverage.Results: Considering an 8min response time threshold, an estimated 5% reduction in the proportion of calls that cannot be reached within the threshold (equivalent to approximately 8000 dispatches) was observed from the computational experiments. The study also revealed that the redeployment policies which are restricted within the same operational division could potentially result in a more promising response time performance. Furthermore, the best policy involved the combination of redeploying ambulances whenever they are released from service and that of relocating ambulances that are idle in bases.Conclusion: This study demonstrated the successful application of an approximate modelling framework based on ADP that leverages upon a detailed DES model of the Singapore's EMS system to generate approximate optimal dynamic redeployment plans. Various policies and scenarios relevant to the Singapore EMS system were evaluated. [ABSTRACT FROM AUTHOR]

Published
2017
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