Developing the Assessment Questions Automatically to Determine the Cognitive Level of the E-Learner Using NLP Techniques

Abstract

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.

Demystifying the Role of Natural Language Processing (NLP) in Smart City Applications: Background, Motivation, Recent Advances, and Future Research Directions

“…• Generating a question bank for online assessment of students manually can be a weary task especially when a broad range of topics are to be covered. To automate this process Deena et al [201] proposed a system to generate Multiple Choice Questions (MCQ) using NER and subjective questions using Bloom's taxonomy and NLP. • Maxwell-Smith et al [44] introduced a method to formulate bilingual corpora by processing the Indonesian-English speech of teachers in an Indonesian classroom using automated speech recognition.…”

Automatic question generation and answer assessment: a survey

“…Dhokrat et al (2012) proposed an automatic system for subjective online examination using a taxonomy that coded earlier into the system. Deena et al (2020) suggested a question generation method using NLP and bloom's taxonomy that generated subjective questions dynamically and reduced the occupation of memory.…”

Predicting Marathi News Class Using Semantic Entity-Driven Clustering Approach

“…Using n blooms taxonomy questions having descriptive answers (subjective) are prepared using NLP techniques The system could dynamically generate the questions and reduces memory the occupation concept. (Deena et al, 2020) The most important research topics are searched using different text mining approaches. Topic modeling using LDA and co-word analysis is used on more than 1000 published research papers.…”