Online Examination System Using Artificial In...

Online Examination System Using Artificial Intelligence

Author Name : Rudresh Kale, Aniket Gaikwad, Prashant Gawali, Shivani Gunjal, Abhay R. Gaidhani

ABSTRACT Modern society places a high importance on online education because of how quickly technology is developing and how education must change to keep up. E-learning is the only option left following the COVID-19 pandemic to keep instruction going during lockdowns, though. Artificial intelligence plays an important role in it. The avoidance of unfair means occurring during online exams is one of the most challenging circumstances exam invigilators encounter. Some of the issues can need consulting nearby references or perhaps getting assistance from neighbours The evaluation of responses, particularly those of the subjective variety, is one of the main difficulties of online exams. Subjective responses gauge a student's capacity for information retention and verbal expression. Subjective questions, in contrast to objective questions, may have more than one valid response. These responses can state the same thing in a different language and grammatical structure. This research paper focuses with a particular emphasis on the randomization approach for ensuring fairness and integrity in assessments. The paper outlines a weighted value-based algorithm designed to generate unique yet equivalently challenging exams, taking into account specific parameters set by the exam creator. Through validation and testing, the system demonstrates its effectiveness in preventing cheating while maintaining exam quality and consistency. As a result, grading subjective questions manually takes a lot of time and is difficult to automate. This work uses machine learning (ML) and natural language processing (NLP) to automatically grade subjective questions. The objective response and the ideal response offered by the body that formulated the question were contrasted in the study