HAWK EYE: Intelligent Analysis of Socio Inspired Cohorts for Plagiarism

Abstract

Plagiarism has become a major cause of concern that has even spread its root across academic area. Universities are becoming more concerned about it because of growing development of internet especially socio media and thereby increasing opportunity among students to copy and paste the electronic content. Students in today’s digital era follow the trend of exchange and copying of information in order to maintain their socio integrity among their circle without considering its long term negative social impact especially from their career perspective. ‘They feel The more you exchange, the more social you are’. To avoid this kind of plagiarism especially in Universities labs, Hawk Eye an innovative mobile plagiarism detection system was an initiative in this regard. Hawk Eye combination with Cohort Intelligence (CI) represents higher state of vision to see things even with more clarity in ordinary experiences, by using Hawk’s keen and observant eyesight, and CI self-supervising nature. This would also help to take appropriate preventive measures to avoid plagiarism from its root among students. ‘Hawk Eye for Cohort (HEC)’ based on comparative analysis of various algorithms like CI and Genetic Search GA can play an important role in formulation of behavioral distribution patterns of students. CI algorithm deploys its self-supervising mechanism to improvise an individual behavior in a cohort and by observing these behavioral patterns, decisions can be taken by teachers in regard of re-design of appropriate evaluation systems to check and stop plagiarism among students. The final outcome of HEC would be an incrementally learning evaluation systems which would iteratively grow with evolving cohort behavioral patterns with every upcoming batch of students. This evolving behavioral patterns search process can be optimized using GA. HEC really would be a concrete evaluation system for analyzing percentage of plagiarism among students, understanding real time reasons behind the growing percentage and coming up with suitable prevention measures in order to cure plagiarism. The concept of study of cohort behavioral distribution pattern using algorithms like GA and CI for plagiarism detection based on student’s socio thinking using different Cohort Analysis Tools is indeed an entirely new idea which is being discussed in this paper in detail.