An automatic grading system based on dynamic corpora

Assessment is a key component of the teaching and learning process. In most Algerian Universities, assessing a student’s answer to an open ended question, even if it is a short answer question, is a difficult and time-consuming activity. In order to enhance the learning process quality and the global student evaluation process and to highly reduce the assessment time and difficulties, most Algerian Universities were provided with an e-learning environment as a result of a government initiative. Unfortunately, such environment seems to be rarely used in the student’s assessment process mainly due to the inefficiency of its Automatic Grading Subsystem (AGS) and the underlying corpora. A corpora used in the grading process contains a great number of miscellaneous answers, each one graded by more than two experts. Building efficient corpora for a course is actually a challenge. The underlying subjectivity in grading answers may have a serious impact in the corpus quality . The specific course context defined by a teacher and the time dependent grading strategy may make very difficult the construction of traditional course corpora. This paper presents a short answer AGS which has the capacity to dynamically build an up to date corpus related to each correct reference short answer. The automatically generated corpus is mainly based on a variety of indications specified by the teacher for each reference short answer. The early experiment of the presented AGS has shown its high efficiency for the automatic answers grading in some computer science courses.