This paper describes a possible application of swarm intelligence techniques in e-learning: an auditing tool for pedagogical planning. Swarm intelligence techniques can be applied to a web system thanks to the fact that the available online material can be organized in a graph by means of hyperlinks. In this case, the swarm that moves on the graph is composed of students who unconsciously leave pheromones in the environment depending on their success or failure. The paper presents the system and shows its capacity to serve as an auditing tool for courses designed by a pedagogical team.

This paper describes experiments aimed at adapting Ant Colony Optimization (ACO) techniques to an e-learning environment, thanks to the fact that the available on-line material can be organized in a graph by means of hyperlinks between educational topics. The structure of this graph is to be optimized in order to facilitate the learning process for students.ACO is based on an ant-hill metaphor. In this case, however, the agents that move on the graph are students who unconsciously leave pheromones in the environment depending on their success or failure. In the paper, the whole process is therefore referred to as a "man-hill."Compared to the [13,14] papers that were providing guidelines for this problem, real-size tests have been performed, showing that man-hills behave differently from ant-hills. The notion of pheromone erosion (rather than evaporation) is introduced.

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In a previous SAC-COMPAHEC paper[1], a method was presented using an interactive evolutionary algorithm for cochlear implants fitting.The method has recently been put to test, with very unexpected and encouraging results: in a few words, it seems that the algorithm is capable to obtain much better results than an expert practitioner in many cases.The solutions proposed by the algorithm are counter-intuitive, yet they improve speech recognition drastically. If these preliminary results are confirmed by many more cases, it could mean that experts have been deterministically tuning cochlear implants the wrong way for many years.However, it seems that the very good results obtained by the algorithm depend a lot on the acoustic environment in which the fitting is performed. A broader fitting scheme has therefore been implemented that should overcome this problem, by allowing the patient to sample typical background noises for which the prosthesis should be specifically tuned.In the future, a piece of software will be added to the cochlear implant signal processor that will automatically choose the best setting depending on the kind of sound environment picked up by the microphone.

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