**1. Introduction**

34 Security Enhanced Applications for Information Systems

Wright, John D., "Air Force Cyberspace Strategic Planning Factors", *High Frontier*, v 7 #3,

http://en.wikipedia.org/wiki/Timeline\_of\_events\_involving\_Anonymous.

Wikipedia, "Timeline of events involving Anonymous",

YouTube, http://www.youtube.com/watch?v=h2br2\_twHfw, 2010

May 2011.

The field of e-learning and self-learning has rapidly evolved during the past decade mainly because of major advances in telecommunications and information technologies, in particular the widespread use of web and mobile applications. Furthermore, the work environment conditions in most industries have become extremely demanding and competitive; therefore various forms of life-long learning appear to play an important role for employees' career development, as well as for companies' productivity improvement and human resources' efficiency. The flexibility, and cost effectiveness that e-learning offers is very significant, in most cases.

In an environment with abundant educational and training institutions the development of efficient new procedures to better guide students or trainees for selecting suitable learning materials is a challenging and open issue. In particular, the development of efficient elearning recommender systems, such as an electronic training advisor who will help individuals in choosing the appropriate e-learning courses matching their particular characteristics, preferences and needs and based on their expected professional and personal development, is an open and promising research and development area (Adomavicius & Tuzhilin, 2005; Brusilovsky, 2002; Kim et al, 2009; Ricci & Werthner, 2006; Zanker & Jessenitschnig, 2006;).

An e-learning recommender system can help trainees overcome basic constraints that elearning users increasingly face:


Development of an e-Learning Recommender System

Fig. 1. Stakeholders in an e-learning Environment

negotiation skills)

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crewmembers may have

Using Discrete Choice Models and Bayesian Theory: A Pilot Case in the Shipping Industry 37

 There is need to offer to the seafarers additional knowledge-skills as well the motivation to improve their soft skills, in particular (team work, leadership, communication,

There is need for applications that help the diffusion of tacit knowledge that

To address these needs in a systematic and valid manner we firstly developed a tool for accumulating the basic knowledge regarding the seafaring profession and training environment, registered the information of the interviewed sample population during the data collection phase, and used statistical analysis to support the choices of each individual

This chapter presents an innovative methodology for the development of a training advisor for e-learning environments. We consider e-learning personalization issues and present an e-learning recommender framework based on discrete choice models and Bayesian theory (Chaptini, 2005; Greene, 1993).
