The notion of communities has been widely studied and recognized as an increasingly important social structure for creating, sharing and applying knowledge in organizational and educational settings. With the advent of Web 2.0 a wide range of community driven technologies has greatly enhanced the development of online communities. In this paper we present CRICOS, a web-based environment which enhances knowledge discovery and sharing within interconnected communities by integrating several community-driven technologies such as collaborative filtering, social navigation and social tagging. The communities are evolved in the system as their members create and improve both the content and the structure of their information spaces. The paper describes the facilities provided to the users by CRICOS and presents an empirical study of the use of the web-based environment in a university course. The results from the empirical study are encouraging regarding the usefulness and the usability of the provided facilities and revealed the students’ positive attitude to the CRICOS web-based environment.This paper refers to a student evaluation enhancement fuzzy logic system in the context of lab–based examinations. In such examinations, the evaluation is traditionally based on the solution the students submit at the end of the exams. While the correctness of the solution has been the most important (and easy to apply) evaluation criterion, sometimes it appears that it is not adequate for a judge evaluation. Many times it is interesting to diagnose both the capability, on behalf of the student, of using the laboratory tool as well as his/her sound comprehending of the theoretical principles (which he/she is expected to apply using the lab tool). This separation is feasible only when the intermediate steps to the solution are taken into account. On the other hand, other characteristics such as the total time that has been needed in order to solve the problem, the number of commands executed and the route the student has followed are usually ignored or in the best case only qualitatively considered. In this paper we present the solution we have applied in order to confront these limitations. Specifically we have evaluated and established further evaluation criteria, in parallel with the correctness of the final result. To this end it has been necessary to develop enhanced logging functionality, which monitors and afterwards analyzes the complete life cycle of the solution process. The fuzzy model represents expert’s knowledge in linguistic form and infers student’s characteristics, combining fuzzy facts, each one contributing to some degree to a fuzzy relation and to the final decision. The system has been applied in the Energy Technology Department of TEI (Technological Educational Institute) of Athens and the results have been interesting, in terms of the evaluation efficiency and the students performance.