Examination System Automation Using Natural Language Processing

Numerous examination portals have been created and distributed over several servers for a number of objectives, including the administration of tests in connection withadmission exams, Olympic competitions at national and worldwide levels, and the administration of placement tests. It turns out that practically all portals are set up for multiple-choice examinations, as we found. Our goal here is not to work on current technology, but rather to work on technology that is very uncommon. The descriptive online examination method is discussed here. Simple to use, multiple choice questions are composed of a question, many possible answers to the same question as well as a field to record the correct response in the database. Descriptive queries, on the other hand, do not fall within this category. To award marks to replies, it incorporates or employs Natural Language Processing (NLP) ideas. The model's responsibility is to lead procedure on the response string so it can give the right stamps to the examinee's responses. The data is generally assembled utilizing an enlightening web-based appraisal procedure. It is likewise inspected, and the made model honors right stamps to the inquiry's answers. With respect to the front-end, HTML 5, CS S 3, Bootstrap, and JavaS cript are utilized. The back-end was created in Python using Django, NLTK for Natural Language Processing, and SQLite version 3 as the database.