Title: Stigmergic agent-based adaptive content sequencing in an e-learning environment

Authors: Richa Sharma; Punam Bedi; Hema Banati

Addresses: Department of Computer Science, Faculty of Mathematical Sciences, University of Delhi, 1st Floor, New Academic Block, Delhi – 110007, India ' Department of Computer Science, Faculty of Mathematical Sciences, University of Delhi, 1st Floor, New Academic Block, Delhi – 110007, India ' Department of Computer Science, Dyal Singh College, University of Delhi, Lodhi Road, New Delhi – 110003, India

Abstract: Stigmergic agents (SA) gather their strength from the ant colony metaphor and multi-agent systems (MAS). Ant-based systems provide a means of picking up information through indirect communication by exhibiting stigmergic ant behaviour and MAS lends the benefits of direct interaction among the agents. This paper presents a stigmergic agent framework for adaptive content sequencing (ACS) in e-learning using SA (ACSeLSA). Each learner enrolled in the designed e-course has a personalised stigmergic agent (PSA) that employs an ant-based adaptive content sequencing algorithm, ACSeLAnt, to generate customised content sequence for him/her. By implementing ACSeLAnt, each PSA: 1) exhibits stigmergic behaviour of producing its own pheromone trails and sensing those of other learners to generate the content sequence; 2) elicits recommendations of other similar learners through direct communication with their PSAs and incorporates them into the content sequencing process. The merger is beneficial for knowledge sharing in e-learning systems where there is a dearth of active dialogue among learners.

Keywords: personalised e-learning; adaptive content sequencing; ACS; personalised stigmergic agents; stigmergy; ant colony optimisation; ACO; multi-agent systems; MAS; agent-based systems; personalisation; electronic learning; online learning; knowledge sharing.

DOI: 10.1504/IJAIP.2013.054673

International Journal of Advanced Intelligence Paradigms, 2013 Vol.5 No.1/2, pp.59 - 82

Received: 27 Jun 2012
Accepted: 30 Dec 2012
Published online: 30 Jul 2014 *

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