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Title |
Web-Based Question Bank System using Artificial Intelligence and Natural Language Processing |
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Author |
Ahd Aljarf, Eman Noor Al-Islam, Kawther Al-shamrani,Nada Al-Sufyini, Shatha Tariq Bugis, Aisha Sharif |
| Citation |
Vol. 22 No. 12 pp. 132-138 |
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Abstract |
Due to the impacts of the current pandemic COVID-19 and the continuation of studying online. There is an urgent need for an effective and efficient education platform to help with the continuity of studying online. Therefore, the question bank system (QB) is introduced. The QB system is designed as a website to create a single platform used by faculty members in universities to generate questions and store them in a bank of questions. In addition to allowing them to add two types of questions, to help the lecturer create exams and present the results of the students to them. For the implementation, two languages were combined which are PHP and Python to generate questions by using Artificial Intelligence (AI). These questions are stored in a single database, and then these questions could be viewed and included in exams smoothly and without complexity. This paper aims to help the faculty members to reduce time and efforts by using the Question Bank System by using AI and Natural Language Processing (NLP) to extract and generate questions from given text. In addition to the tools used to create this function such as NLTK and TextBlob. |
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Keywords |
Question Bank, Artificial Intelligence, Natural Language Processing, E-learning. |
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