Exams System Website
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Since technology has a great impact on all aspects of life, the methods used to write examination questions using paper and pencil have become very traditional methods. Keeping up with this technological development, there are many websites that offer exams forms which often composed of multiple choice questions, that are performed, resolved and submitted online, or provide prepared templates for examinations and ask the teacher to fill the questions that he want, other websites offering various exams in known areas such as the TOEFL exam and global intelligence tests such as IQ exam and others. The idea of this website is to provide exams and homework from questions that are already entered by the teacher, which is easier than writing new questions each time in the traditional methods, where the teacher enters materials names, IDs, credit hours and departmant name, then he can enter large set of questions with related keywords and select the material that it belongs to, which is stored in the database, and when he wants to write an exam, he determines certain specifications such as the weight of the exam from the total mark of the course, exam duration, exam type (firt, second …etc.) and date, after that he can search for already stord questions and select ones that he want, then enter the mark for each question, and he can request to change or delete a question. There are two types of exams that are normal or online exam, for normal exam teacher can determine the shape of the exam by specifying the empty space after each question and the order of questions, then he can generate PDF file for the exam under these conditions to be ready for printing or preservation, the teacher can also choose to take the exam online, in which case he will determine the exam time and the students who will take the exam Students can access the website to solve the online exams, and get their results. The technique that will be used in this project is Natural Language Processing (data mining). Where the principle of this technique is to convert keywords and entered a query to the form of vectors, then find maximum cosine similarity between them.