Leveraging Ethics in Artificial Intelligence Technologies and Applications: E-Learning Management Systems in Namibia

Leveraging Ethics in Artificial Intelligence Technologies and Applications: E-Learning Management Systems in Namibia

Gabriel N. Uunona, Leila Goosen
DOI: 10.4018/979-8-3693-1487-6.ch008
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The purpose of the study reported on is to establish ways in which ethics in artificial intelligence (AI) technologies and applications can be leveraged towards improved, standardized and safe e-learning management systems (eLMSs) at higher education institutions (HEIs) in Namibia, against the background of semantic web technologies and applications in artificial intelligence, the internet of things (IoT), and artificial intelligence of things (AIoT).
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This section will describe the general perspective of the chapter and end by specifically stating the objectives.

Semantic Web Technologies and Applications in Artificial Intelligence of Things

The value that Artificial Intelligence (AI), the Internet of Things (IoT), Artificial Intelligence of Things (AIoT) and the Semantic Web had contributed to the development of industry, research, and society, in general, is relevant for a future society. As part of this book, the chapter could serve as a reference for the development of Semantic Web technologies in Industry 4.0 and the AIoT.

Leveraging Ethics in Artificial Intelligence Technologies and Applications at Higher Education Institutions: E-Learning Management Systems in Namibia

According to a previous chapter by Uunona and Goosen (2023, p. 310) on leveraging ethical standards in artificial intelligence technologies as a guideline for responsible teaching and learning applications in the Handbook of Research on Instructional Technologies in Health Education and Allied Disciplines, AI “is revolutionizing the field of education by providing new opportunities for online learning. However, as with any technology, there are ethical” implications that must be considered. With the commencement of the conversation on AI, the awareness of such ethical considerations needed to be kept in mind. Such a conversation should trigger the possibility of considering a logical culturally-sensitive framework that will be used to provide guidelines for national policy development on AI.

From the recommended topics for the book, this chapter will cover the following (although it is not limited to these):

• Usability and user experience in Semantic Web and AIoT application environments

• AIoT-based Semantic Web applications and public services

• Use of model and learning algorithms and machine learning in AIoT and Semantic Web

Target Audience

As part of this book, the chapter is aimed at academics, students, and industry, around topics such as the manufacturing industry, health and sciences, as well as e-government.


The objective of this quality chapter is to contribute to the book on topics related to cutting-edge technologies and serve as a knowledge base in terms of future research directions. Some of the objectives of the study reported on in this chapter include to:

• Explore current and future-projected developments in AI autonomy and how these could impact education, and

• Establish the extent to which the Namibian government had considered AI implications in its strategic plans and associated policies.



This section of the chapter will provide broad definitions and discussions of the topic on Leveraging Ethics in AI Technologies and Applications at Higher Education Institutions (HEIs) via e-Learning Management Systems (e-LMSs) in Namibia and incorporate the views of others (in the form of a literature review) into the discussion to support, refute, or demonstrate the authors’ position on the topic.

“Marginalias are the reading marks found in different types of documents” (Hernández-Quintana & Trinquete, 2022, p. 111). The way in which the latter are approached by “research in different fields of science is a growing phenomenon and therefore” required a proposal from the digital humanities regarding TAXChe, an online taxonomy for Che’s marginalias, which was described in the chapter by the latter authors in a book on knowledge organization across disciplines, domains, services and technologies.

Citizen information “is treated in the local media” (press) as being “of upmost importance for the” decision making of “citizens, and it is also relevant because of its impact” (Madruga, Roche, & Hernández Quintana, 2017, p. 11). The journal article by the latter authors therefore provided a content analysis of the Tribuna de La Habanas newspaper for the period 2008-2014

Key Terms in this Chapter

E-Learning: The use of digital media and information communication technologies for the development, management and delivery of educational content and processes.

LMS Plugin: Applications that enhance the ability of the LMS to create, innovate, host and manage online learning.

Ethics: Standards of right and wrong, which serve as a yardstick of human actions and behaviors in consideration of rights, fairness, and societal benefits.

Big Data: Data, where the volume and variety are relatively high such that these exert pressure on cost and innovation for storage and processing.

Artificial Intelligence in Education (AIEd): The understanding and application of AI in education for the improvement of teaching and learning, as well as developing expertise in AI.

Autonomous Artificial Intelligence (AI): The ability of machines, systems, or computer applications to take actions independently, without the influence of human guidance.

Learning Management System (LMS): The computerized web-based applications designed for administering and managing teaching, learning and assessment.

Educational Technology (Edtech): The use of technological resources for the enhancement of teaching and learning processes.

Delphi Technique: A systematic qualitative research method used to centrifuge diverse opinions into a converged opinion.

Machine Learning (ML): Computer algorithms that mimic human intelligence capable of learning from the patterns of events happening in the surrounding environment.

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