The Use of Artificial Intelligence in Education: Applications, Challenges, and the Way Forward

The Use of Artificial Intelligence in Education: Applications, Challenges, and the Way Forward

Elisha Mupaikwa
Copyright: © 2023 |Pages: 25
DOI: 10.4018/978-1-6684-8671-9.ch002
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Abstract

Over the past few decades, there has been an increase in ongoing research into the use of artificial intelligence in education. The usage of artificial intelligence in educational institutions has grown during the past few years. This chapter examines how artificial intelligence is used in education. The establishment of inclusive learning environments, collaborative learning and research, social robots, student assessment, automated grading, recommender systems, and student performance prediction were identified to be the main applications of artificial intelligence in education. Lack of funding, lack of faith in the system, lack of portability of systems, infrastructure issues, ethical issues regarding data privacy and security, and a lack of experience were some of the difficulties noted. After that, the chapter included recommendations for infrastructure improvements, ICT policy changes at the national and institutional levels, curriculum revisions for teacher- and school-level preparation, and additional research.
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Background

In several sectors, AI usage and development have increased during the last few decades. A new area of study known as “AI in Education (AIED)” has emerged as a result of the usage and research of AI in the fields of education and training. According to Tan et al., (2022), AIED refers to the use of AI in educational environments to enhance teaching and learning by emulating human intelligence to infer, judge, and make decisions, among other activities of education and training as well as research. Three dimensions have developed in the field of artificial intelligence in education (AIED). These are AI-directed, learner-as-recipient; AI-supported, learner-as-collaborator; and AI-empowered, learner-as-leader Ouyang & Jiao (2021). For the first paradigm, the learner is reduced to a passive observer while the AI system assumes a leading and directing role in the educational process, imparting knowledge and setting the learning agenda. A collaborative relationship exists between the AI system and the user in the second paradigm. The third paradigm aims to provide the learner with more control over their education by personalizing the learning experience and assigning each student a specially designed learning assignment.

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