No abstract

No abstract

E-learning plays a significant role in educating large number of students. In the delivery of e-learning material, automatic e-assessment has been applied only to some extent in the case of free response answers in highly technical diagrams in domains like software engineering, electronics, etc., where there is a great scope of imagination and wide variations in answers. Therefore, the automatic assessment of diagrammatic answers is a challenging task. In this article, algorithms that compute the syntactic and semantic similarities of nodes to fulfill the objective of automatic assessment of use-case diagrams are described. To illustrate the performance of these algorithms, students' use-case diagrams are matched with model use-case diagram. Results from 13,749 labels of 445 student answers based on 14 different scenarios are analyzed to provide quantitative and qualitative feedback. No comparable study has been reported by any other label matching algorithms before in the research literature.

Establishment of institutions of higher learning requires massive amount of different resources which are always in short supply. The delivery of learning material and tests to the students has become very easy with the facility of uploading the same on the web irrespective of the number of students. The assessment part could be a deterrent as far as willingness of learned faculty members to participate in the whole process is concerned. If assessment will become automated then it will be easier for any teachers to evaluate any number of students. This paper presents a proposed architecture of automated assessment of Use -Case Diagram. The essence of this architecture is to assess large number of students very easily in short duration. This proposed work is going to be very useful for the needy students by assisting in evaluation of their performance.

No abstract