Usage of advanced E-leaming methods for faster newcomer adaptation in IT production environment

Modern IT companies are experiencing high employee fluctuations during last years which cause lots of financial costs due to an initial adaptation periods for new employees. Considering mainly fresh graduate employees and employees which don't have enough initial knowledge to perform according various internal rules, causes their disorientation in the company processes and thus slower their professional grow to become a profitable employee. This paper compile solutions which have been used effectively in E-learning environment and next generation education practices into a proposal of concept for the newcomer training system for better self-study, employee ability analysis, mentor intervention alerting and many more features which will ease load on mentors and in parallel create better usage of internal knowledge bases and other tools by utilizing machine learning techniques. However majority of current systems focus on user learning behavior model, demands and habits, few of them encompass the problem difficulty and user profile or his abilities, which can be derived directly from his CV or from various forms of skill databases which are used widely by IT companies. This system should create a less stressful environment for a newcomer and thus he can become valuable part of workforce team.