Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts: A Comprehensive Investigation

Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts: A Comprehensive Investigation

Mandana Farzaneh (University of Tehran, Iran), Iman Raeesi Vanani (University of Tehran, Iran) and Babak Sohrabi (University of Tehran, Iran)
Copyright: © 2012 |Volume: 3 |Issue: 1 |Article: 4 |Pages: 14
ISSN: 1947-8518|EISSN: 1947-8526|DOI: 10.4018/ijvple.2012010104
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MLA

Farzaneh, Mandana, Iman Raeesi Vanani and Babak Sohrabi. "Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts: A Comprehensive Investigation." IJVPLE 3.1 (2012): 55-68. Web. 1 Jan. 2019. doi:10.4018/ijvple.2012010104

APA

Farzaneh, M., Vanani, I. R., & Sohrabi, B. (2012). Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts: A Comprehensive Investigation. International Journal of Virtual and Personal Learning Environments (IJVPLE), 3(1), 55-68. doi:10.4018/ijvple.2012010104

Chicago

Farzaneh, Mandana, Iman Raeesi Vanani and Babak Sohrabi. "Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts: A Comprehensive Investigation," International Journal of Virtual and Personal Learning Environments (IJVPLE) 3 (2012): 1, accessed (January 01, 2019), doi:10.4018/ijvple.2012010104

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Abstract

E-learning is one of the most important learning approaches within which intelligent software agents can be efficiently used so as to automate and facilitate the process of learning. The aim of this paper is to illustrate a comprehensive categorization of intelligent software agent features, which is valuable for being deployed in the virtual world of learning and training. The characteristics of agents make them worthwhile for being used in the implementation and improvement of e-learning information systems, especially the web-based or web-enabled e-learning mechanisms. An extensive exploration of agent-related international papers has been conducted so as to cover a wide range of internationally accepted features as well as the classification of agents and their correspondent references. These agent characteristics enable the online learning mechanisms to act on behalf of the user in electronic learning and to respond to specific requirements in a more efficient and effective manner than the traditional learning systems. The implementation of agents according to the most useful features helps teachers transfer the related knowledge easier, faster, and more directed towards the targeted audience of the e-learning system for a better and deeper learning quality.

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