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    <name>Article</name>
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          <name>Title</name>
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              <text>Developing the assessment questions automatically to determine the cognitive level of the e-learner using NLP techniques</text>
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          <name>Subject</name>
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              <text>Blooms Taxonomy; Learning Management System; Multiple Choice Questions; Named Entity Recognition; Natural Language Processing</text>
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              <text>The key objective of the teaching-learning process (TLP) is to impart the knowledge to the learner. In the digital world, the computer-based system emphasis teaching through online mode known as e-learning. The expertise level of the learner in learned subjects can be measured through e-assessment in which multiple choice questions (MCQ) is considered to be an effective one. The assessment questions play the vital role which decides the ability level of a learner. In manual preparation, covering all the topics is difficult and time consumable. Hence, this article proposes a system which automatically generates two different types of question helps to identify the skill level of a learner. First, the MCQ questions with the distractor set are created using named entity recognizer (NER). Further, based on blooms taxonomy the Subjective questions are generated using natural language processing (NLP). The objective of the proposed system is to generate the questions dynamically which helps to reduce the occupation of memory concept.  2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.</text>
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          <name>Creator</name>
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              <text>Deena G.; Raja K.; Nizar Banu P.K.; Kannan K.</text>
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              <text>International Journal of Service Science, Management, Engineering, and Technology, Vol-11, No. 2, pp. 95-110.</text>
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          <name>Publisher</name>
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              <text>IGI Global</text>
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          <name>Date</name>
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              <text>2020-01-01</text>
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              <text>&lt;a href="https://doi.org/10.4018/IJSSMET.2020040106" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/IJSSMET.2020040106&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083287039&amp;amp;doi=10.4018%2FIJSSMET.2020040106&amp;amp;partnerID=40&amp;amp;md5=8e04dafa401e18bd6f50186ae970b170" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083287039&amp;amp;doi=10.4018%2fIJSSMET.2020040106&amp;amp;partnerID=40&amp;amp;md5=8e04dafa401e18bd6f50186ae970b170&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 1947959X</text>
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          <name>Format</name>
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              <text>Online</text>
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          <name>Language</name>
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              <text>English</text>
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              <text>Deena G., Sathyabama University, Chennai, Tamil Nadu, India; Raja K., Dhaanish Ahmed College of Engineering, Chennai, India; Nizar Banu P.K., CHRIST (Deemed to be University), Bangalore, Karnataka, India; Kannan K., AudiSankara College of Engineering and Technology, Gudur, Nellore, India</text>
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