Game Theory for Best Results in Academics
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Game Theory (GT) is a technique or tool for analyzing the problems for studying and evolving the strategies, for reaching out towards the rational decision processes of individual persons and their interactions in an environment of a group. Game Theory focuses on studying the different approaches, in which strategic interactions among different economic agents evolve outcomes with respect to the choices (or utility) of the agents, irrespective of whether the results of their efforts were intended. Thus, mostly GT is used for a study of different mathematical models of variations, uncertainties, conflicts and interactions among intelligent; rationally deciding subjects i.e. human beings.
In teaching learning process large number of students, faculties are involved. This results in large number of variables. Large number of students with unpredictable behaviors, number of faculties with different methods of teaching, makes it difficult to achieve the best academic results. So a study is undertaken and a game theory (GT) is adapted to evolve an academic system so that academic process becomes interesting for the participants that are the students and faculty.
The basic reason of choosing a GT is as it allows users to consider the different variations in the chosen model. The objective of this study is to evolve a composite optimum strategy for the faculty member in-order to achieve the best possible result for any fragmented group of students. The analysis is carried out at the level of some subject in which maximum use of mathematics is observed, such as economics and financial analysis and management.
Keywords
- Osborne, M. J., (2004), An Introduction to Game Theory, Oxford University Press.
- Ross, D.: Game Theory: Stanford Encyclopedy of Philosophy. http://plato.stanford.edu/entries/game–theory/, Part 1: Philosophical and Historical Motivation
- Binmore, K., (2007), Game Theory: A Very Short Introduction. Oxford University Press
- Myerson, R.B., (1991), Game Theory: Analysis of Conflict. Harvard University Press, Chapt. 1: Decision - theoretic foundation, 1 - 9.
- D'Agostini, G., (1999), Teaching statistics in the physics curriculum: Unifying and clarifying role of subjective probability, American Journal of Physics, vol. 67, 1260–1268.
- Armstrong, S. A., (2004), A Meta-Analysis of Randomness in Human Behavioral Research, MSc Thesis, Department of Mathematics, Louisiana State University.
- Aleksić-Maslać, K., Sinković, B. and Vranešić, P, (2018), “The role of competition and reward regarding student motivation in the gamification process of different age groups, 10th annual International Conference on Education and New Learning Technologies, Palma de Mallorca, Spain.
- Erenli K., (2013), “The Impact of Gamification - Recommending Education Scenarios.” International Journal of Emerging Technologies in Learning, vol. 8. pp. 15-21,.
- Kulkarni Ankur A. and Abraham Mathew P., (2018), An Approach Based on Generalized Nash Games and Shared Constraints for Discrete Time Dynamic Games, Dynamic Games and Applications, vol. 8, issue 4, 641-670
- Abraham Mathew P & Kulkarni Ankur A., (2017), New results on the existence of open loop Nash equilibria in discrete time dynamic games via generalized Nash games, Under review with Mathematical Methods of Operations Research
- Graţiela G., & Carmen J. G., (2014) Applications of games theory in analyzing teaching process, WCES 2013Procedia - Social and Behavioral Sciences 116, 3588 – 3592
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