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2021 - Volume 4 - Number 2

A Literature Review on Automatic Generation of Examinations

Peter Ndegwa Ndirangu * ndejanpeter@gmail.com * ORCID: 0000-0002-2305-930X
The Kenyatta University, Computing and Information Technology Department, Nairobi, KENYA

Elizaphan Maina Muuro * maina.elizaphan@ku.ac.ke * ORCID: 0000-0003-1917-9760
The Kenyatta University, Computing and Information Technology Department, Nairobi, KENYA

John M. Kihoro * kihoro.jm@cuk.ac.ke * ORCID: 0000-0002-8477-5588
The Kenyatta University, Computing and Information Technology Department, Nairobi, KENYA

Open Journal for Information Technology, 2021, 4(2), 77-84 * https://doi.org/10.32591/coas.ojit.0402.04077n
Received: 28 September 2021 ▪ Accepted: 3 December 2021 ▪ Published Online: 30 December 2021

LICENCE: Creative Commons Attribution 4.0 International License.

ARTICLE (Full Text - PDF)

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.

KEY WORDS: natural language processing, MLA – machine learning algorithm, AI – artificial intelligence.

CORRESPONDING AUTHOR:
Peter Ndegwa Ndirangu, The Kenyatta University, School of Engineering and Technology, Nairobi, KENYA. E-mail: ndejanpeter@gmail.com.

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