Student testing and monitoring system (STMS) using Nlp
Автор: Muhammad Saad, Shanzah Aslam, Warda Yousaf, Moeed Sehnan, Sidra Anwar, Danish Rehman
Журнал: International Journal of Modern Education and Computer Science @ijmecs
Статья в выпуске: 9 vol.11, 2019 года.
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In the domain of knowledge, there is a rising demand for such a System to provide learning support via a platform which can generate any sort of questions automatically from provided source either (PDF) books or simply any keyword against a user needs to perform a test where STMS serves the purpose. Regarding Keyword operation, the System scraps all the text from Wikipedia and converts it into multiple choice questions. Moreover, it summarizes raw text from Wikipedia and parse the text from provided content to generate Multiple-Choice Questions(MCQs). The System also finds all the Named Entities and POS (Parts of speech tags) in the content to create relevant questions. The questions include Multiple-Choice Questions(MCQs), Cloze based questions and WH- questions (why, where, when etc.). In addition, when users score standard points in the test then they qualify for earning zone where they can earn money ($ Dollars) for scoring points in each test. The Income comes from AdSense applied on the website and other Local ads, Affiliating marketing and advertisements. All in all, the System would help in educational learning by providing helping material in the lacking knowledge areas after analyzing the tests users have performed while the Web-Traffic is the key to Success for monetary benefits.
Web based Student Testing and Monitoring System (STMS), Natural Language Processing, Artificial Intelligence, Semantic Role Labelling, Machine Learning, Wikipedia Scraping, Text Mining
Короткий адрес: https://sciup.org/15016877
IDR: 15016877 | DOI: 10.5815/ijmecs.2019.09.03
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