Affective Behaviour analysis of Students

Web mining of educational content to identify the affective behavior of students like the moods, feelings and participation levels. Some of the aspects which are used to measure have been listed below:

.Session statistics: basic statistics about sessions such as average session length in time or in number of requests.
· Session patterns: the determination of student learning processes extracted from navigation and request
behaviour.
· Time series of session data: the analysis of the development of session statistics and session patterns over a
period of time.

.Behaviour patterns data: to analyze the various expressions of the students depending upon the challenges given to them and their expressions capture by either physical recording or their digital abstraction of images, video.

Tools such as discussion forums, Search engines which collect a large volume of information can also be used to identify the affective behaviour patterns of students.

Use of LMS(Learning Management System) in Educational Data Mining

Learning management systems have made the life simpler by managing a centralized accessibility of all the requirements of an instructor, student and content management. Some of well known Learning Management System include Moodle, Sakai, WebCT, WhiteBoard, Brihaspati-3. The main aim of building a LMS is to achieve a collabrative learning atmosphere, where students can exchange there ideas, share resources and instructors can create content for the students and post at a centralized repository for the content to be available in a well organized way. some of basic qualities of a Learning Management System includes the following:

1. Course Management -course enrollment, course updates, curriculum design, types of Assignments.

2. Content Management- content design, type of content, wiki, discussion forum, groups, chats, hot potato, organize content repositories.

3. Student Management-student enrollments, profiles, student learning tools, blogs.

4. Grading and Evaluation Management- rubrics, assessment tools, grading reports, monitoring of student response, maintenance of student database repositories.

5. Institute and Administration Management- Institute authorization, institute administration, resource monitoring, database backups, recovery and restoration of content.

These are some of major functionalities most of the Learning Management system possess. So, rather than setting up individual systems for each and every functionality, all of them can be managed very well under a central repository through LMS.