Back to Search Start Over

Artificial Intelligence in Distance Education: A Systematic Literature Review of Brazilian Studies

Authors :
Durso, Samuel de Oliveira
Arruda, Eucidio Pimenta
Source :
Problems of Education in the 21st Century. 2022 80(5):679-692.
Publication Year :
2022

Abstract

Artificial Intelligence (AI) is changing the way people live in society. New technologies powered by AI have been applied in different sectors of the economy and the educational context is no different. AI has been considered a key to the development of learning strategies, especially in distance education. In this sense, this research aimed to identify the current state of Brazilian literature on AI applied to distance education. The Higher Education market in Brazil, which is the biggest in Latin America regarding the number of individuals able to enroll in a program, is still developing and distance education has grown rapidly. To reach the purpose of this paper, it was performed a Systematic Literature Review (SLR) to find the research conducted in graduate programs that investigate the subject of AI applied to distance education. The final analysis used a total of 63 studies -- 26 master's theses and 37 doctoral dissertations. The main results show that most of the research on AI in distance education in Brazil was conducted in Computer Science (56%) and Engineering (27%). Only 6% of the studies reviewed are from masters' or doctoral programs in Education. The result also shows that limited attention is paid to critical topics related to the growing introduction of AI in distance education, as such teachers' employability and technological training or the ethical implications of using AI for the educational process. As a result of this SLR, it was possible to suggest research opportunities considering the international agenda on AI.

Details

Language :
English
ISSN :
1822-7864 and 2538-7111
Volume :
80
Issue :
5
Database :
ERIC
Journal :
Problems of Education in the 21st Century
Publication Type :
Academic Journal
Accession number :
EJ1368971
Document Type :
Journal Articles<br />Information Analyses