Embedding Information Retrieval and Nearest-Neighbour Algorithm into Automated Essay Grading System

One of the research interests in educational technology has been in the automating the text assessment of the students’ answer. The main reason for such interest is due to an overwhelming of marking scripts need to be graded within a time limit. Among many forms of answering format, an essay-type answer is the most difficult format for an automated system to assess. In this paper, we describe the architecture of our system which assigns a grade to an essay prepared by the students for the history subject. The system is built on modules that perform preprocessing of the document and query, prepare model answers and assign grades to the students’ answer. We show the output of the system as the results of applying this system on the samples of data which are the students’ answer for high school syllabus.