The Politics of E-Learning: A Game Theory Analysis

The Politics of E-Learning: A Game Theory Analysis

Celia Romm-Livermore, Mahesh S. Raisinghani, Pierlugi Rippa
Copyright: © 2016 |Pages: 14
DOI: 10.4018/IJOPCD.2016040101
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Abstract

The focus of this article is on how the negotiations between professors and students that are part of the eLearning political process can be interpreted through the prism of game theory. The source of data for the case was a series of in-depth interviews with the professor and an analysis of the e-mail messages exchanged between the professor, the students, and management. Each round of the game represents a different combination of positions, strategies and outcomes, yet, taken as a whole, the case events suggest underlying themes that, if been identified by the two sides, could have led to different outcomes. The discussion and conclusions section outlines the rules that governed the behaviour of the actors from a game theory perspective. This case is unique and, hence, the conclusions from it are not necessarily generalizable. Management's role in the games that people play in the eLearning area is crucial in the newly emerging corporatized university. Game theory analysis is applied in this paper to a four-round negotiation process between students and their professor in the context of an eLearning case study.
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The Politics Of E-Learning

Before we consider the role that politics may play in eLearning, it is important to define eLearning. Cross (2004) is considered the person who coined the term eLearning. Since then, a range of definitions have been offered for this term. The first type of definitions focus on the fact that eLearning is based on the Internet. For example, Rosenberg (2001) defines eLearning as: “the use of internet technologies to deliver a broad array of solutions that enhance knowledge and performance, Rossett amd Kendra (2001) defines eLearning as: “Web-based training (WBT)”, and Adrich (2004) defines eLearning as: “a broad combination of processes, content, and infrastructure to use computers and networks to scale and/or improve one or more significant parts of a learning value chain, including management and delivery”.

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