A Literature Review on Automatic Generation of Examinations
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Date
2021
Authors
Ndirangu, Peter Ndegwa
Muuro, Elizaphan Maina
Journal Title
Journal ISSN
Volume Title
Publisher
COAS
Abstract
The examination is a key activity in determining what the learner has gained from the study.
Institutions of higher learning (IHL) perform this activity through various assessment methods
(test/examination, practical, etc.). The world today is focused on automation of exam generation
which is ongoing with dire need during this period of the COVID-19 pandemic when education is
greatly affected, leading to embracing online learning and examination. A text/exam comprises
questions and answers that focus on evaluation to determine the student’s conversant level in the
area of study. Each question has a cognitive level as described by (Armstrong, 2016) in the revised
Bloom’s taxonomy. Questions chosen have cognitive levels based on the level of study and
standardization of the exam. There is, therefore, a need to consider the question’s cognitive level
along with other factors when generating an examination by incorporating deep learning
algorithms.
Description
Article
Keywords
natural language processing, MLA – machine learning algorithm, AI – artificial intelligence
Citation
Ndirangu, P. N., Muuro, E. M., & Kihoro, J. M. A Literature Review on Automatic Generation of Examinations. Open Journal for, 77.