Farhan Ullah1,4,*, Abdullah Bajahzar2, Hamza Aldabbas3, Muhammad Farhan4, Hamad Naeem1, S. Sabahat H. Bukhari4,5, Kaleem Razzaq Malik6
Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 169-180, 2020, DOI:10.31209/2019.100000138
Abstract This research aims to an electronic assessment (e-assessment) of students’
replies in response to the standard answer of teacher’s question to automate
the assessment by WordNet semantic similarity. For this purpose, a new
methodology for Semantic Similarity through WordNet Semantic Similarity
Techniques (SS-WSST) has been proposed to calculate semantic similarity
among teacher’ query and student’s reply. In the pilot study-1 42 words’ pairs
extracted from 8 students’ replies, which marked by semantic similarity
measures and compared with manually assigned teacher’s marks. The teacher
is provided with 4 bins of the mark while our designed methodology provided
an exact measure of… More >
Login
Register
