scholarly journals The Automatic Question Generation System for CET

2021 ◽  
Vol 09 (09) ◽  
pp. 161-168
Author(s):  
Xinya Zhang ◽  
Xiaodong Yan ◽  
Zhou Yao
Keyword(s):  
Generation System ◽  
Question Generation ◽  
Automatic Question Generation

scholarly journals Weak Supervision Enhanced Generative Network for Question Generation

2019 ◽  
Author(s):  
Yutong Wang ◽  
Jiyuan Zheng ◽  
Qijiong Liu ◽  
Zhou Zhao ◽  
Jun Xiao ◽  
...  
Keyword(s):  
Question Answering ◽  
Interaction Mechanism ◽  
Generation System ◽  
Dialogue System ◽  
Question Generation ◽  
Weak Supervision ◽  
Weakly Supervised ◽  
The Given ◽  
Automatic Question Generation

Automatic question generation according to an answer within the given passage is useful for many applications, such as question answering system, dialogue system, etc. Current neural-based methods mostly take two steps which extract several important sentences based on the candidate answer through manual rules or supervised neural networks and then use an encoder-decoder framework to generate questions about these sentences. These approaches still acquire two steps and neglect the semantic relations between the answer and the context of the whole passage which is sometimes necessary for answering the question. To address this problem, we propose the Weakly Supervision Enhanced Generative Network (WeGen) which automatically discovers relevant features of the passage given the answer span in a weakly supervised manner to improve the quality of generated questions. More specifically, we devise a discriminator, Relation Guider, to capture the relations between the passage and the associated answer and then the Multi-Interaction mechanism is deployed to transfer the knowledge dynamically for our question generation system. Experiments show the effectiveness of our method in both automatic evaluations and human evaluations.

Automatic Question Generation system

2014 ◽  
Author(s):  
P Pabitha ◽  
M. Mohana ◽  
S. Suganthi ◽  
B. Sivanandhini
Keyword(s):  
Generation System ◽  
Question Generation ◽  
Automatic Question Generation

The Development of an Automatic Question Generation System on Facebook Using an Artificial Bee Colony Algorithm

2013 ◽  
Vol 311 ◽  
pp. 141-146
Author(s):  
Hsin Chin Chen ◽  
Chia Cheng Hsu ◽  
Hung Chang Li ◽  
Chih Chin Huang ◽  
Yueh Min Huang
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Learning Ability ◽  
Generation System ◽  
Question Generation ◽  
Bee Colony ◽  
Learning Platform ◽  
Need To Evaluate ◽  
E Learning ◽  
Automatic Question Generation

Facebook is currently one of the world's most popular social networking services, and has been widely used in the field of e-learning. In general, learners in e-learning environments need to evaluate their learning ability through taking tests to present the learning achievement. In order to evaluate their ability on e-learning platform with social network services, this study proposes an automatic question generation system for individual learning status. The proposed system uses the artificial bee colony algorithm to find suitable questions for each learner according to the learner's profile, reading experience, professional ability, and the e-learning records in the system. The experimental results indicate that the proposed method improves the accuracy of the automatic question generation system and that it outperforms the random method.

An Automatic Question Generation System using Rule-Based Approach in Bloom’s Taxonomy

2019 ◽  
Vol 13 ◽  
Author(s):  
G Deena ◽  
K Raja ◽  
K Kannan
Keyword(s):  
Language Processing ◽  
Learning Process ◽  
Question Generation ◽  
Test Question ◽  
Rule Based ◽  
Part Of Speech ◽  
Core Idea ◽  
Rule Based Approach ◽  
Teaching Learning ◽  
Automatic Question Generation

: In this competing world, education has become part of everyday life. The process of imparting the knowledge to the learner through education is the core idea in the Teaching-Learning Process (TLP). An assessment is one way to identify the learner’s weak spot of the area under discussion. An assessment question has higher preferences in judging the learner's skill. In manual preparation, the questions are not assured in excellence and fairness to assess the learner’s cognitive skill. Question generation is the most important part of the teaching-learning process. It is clearly understood that generating the test question is the toughest part. Methods: Proposed an Automatic Question Generation (AQG) system which automatically generates the assessment questions dynamically from the input file. Objective: The Proposed system is to generate the test questions that are mapped with blooms taxonomy to determine the learner’s cognitive level. The cloze type questions are generated using the tag part-of-speech and random function. Rule-based approaches and Natural Language Processing (NLP) techniques are implemented to generate the procedural question of the lowest blooms cognitive levels. Analysis: The outputs are dynamic in nature to create a different set of questions at each execution. Here, input paragraph is selected from computer science domain and their output efficiency are measured using the precision and recall.

Improving Learning Outcomes with Gaze Tracking and Automatic Question Generation

2020 ◽  
Author(s):  
Rohail Syed ◽  
Kevyn Collins-Thompson ◽  
Paul N. Bennett ◽  
Mengqiu Teng ◽  
Shane Williams ◽  
...  
Keyword(s):  
Learning Outcomes ◽  
Question Generation ◽  
Gaze Tracking ◽  
Automatic Question Generation
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