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Title:
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DEVELOPING A DECISION-THEORETIC MODEL BASED ON A STATE AND TRANSITION MODEL FOR IMPROVING STUDENT PERFORMANCE |
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Author(s):
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Wichian Premchaiswadi, Nipat Jongsawat, Nucharee Premchaiswadi |
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ISBN:
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978-972-8939-71-7 |
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Editors:
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Miguel Baptista Nunes and Pedro Isaías |
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Year:
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2012 |
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Edition:
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Single |
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Keywords:
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Bayesian Network, State and Transition Model, Decision-Theoretic Model, Diagnosis, GeNIe, Evidences. |
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Type:
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Full Paper |
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First Page:
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153 |
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Last Page:
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160 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper describes a decision-theoretic model- a Bayesian Network model- to diagnose the causes-effect of student performance in higher education. The aim of the paper is to build tools to assist policymakers in higher education to evaluate various scenarios, consider through a policy, and select among competing policy options. The tools can also provide a cause-effect relationship between the academic performance of students and other academic factors for policymakers. First, we build the State and Transition Model that is used to provide a simple framework for integrating knowledge about a specific level of student performance and various academic factors affecting student performance. Second, we convert the State and Transition Model into a Bayesian Network model. Third, the probabilities for the BN model are determined through the knowledge of university professors and literature studies. Last, we observe the interactions among the variables and allow for prediction of effects of external manipulation. We believe that both STM and BN models can be used as very practical tools for educating policymakers at the higher education level. |
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