e-learning; learning technology; web-based courses; adaptive hypermedia; AHA!; statistical evaluation; data analysis

Mining knowledge from logs of adaptive system is one of methods, how to obtain information, which can be used to verify used adaptation scheme and to determinate possible modifications of learning materials. This paper is focusing on statistic methods, which can show differences between several groups of users and determine knowledge cohesion of users in progress and at the end of the course. To determine difficult or simple questions in tests level of relevancy can be used. For log processing can be used methods of data analysis, such as clustering or decision trees. These methods are useful for detection of navigation in course and for determination, which parts of offered learning material is necessary to know for particular final mark.

Mining knowledge from logs of adaptive system is one of methods, how to obtain information, which can be used to verify used adaptation scheme and to determinate possible modifications of learning materials. This paper is focusing on statistic methods, which can show differences between several groups of users and determine knowledge cohesion of users in progress and at the end of the course. To determine difficult or simple questions in tests level of relevancy can be used. For log processing can be used methods of data analysis, such as clustering or decision trees. These methods are useful for detection of navigation in course and for determination, which parts of offered learning material is necessary to know for particular final mark.