Artificial intelligence applications in Latin American higher education: a systematic review

• Published in: International Journal of Educational Technology in Higher Education 2022-04, Vol.19 (1), p.1-20, Article 21
• Main Authors: Salas-Pilco, Sdenka Zobeida, Yang, Yuqin
• Format: Article
• Language: English
• Subjects: Administration; Algorithms; Artificial Intelligence; Artificial intelligence (AI); Assistive Technology; At Risk Students; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Content Analysis; Deep learning; Dropout Characteristics; Educational Innovation; Educational Quality; Educational Technology; Foreign Countries; Higher Education; Higher education institutions; Humanities; Identification; Information Systems Applications (incl.Internet); Instruction; Latin America; Law; Learning; Learning Analytics; Learning Processes; Literature reviews; Machine learning; Mathematics; Natural Language Processing; Prediction; Prediction models; Review Article; Statistics for Social Sciences; Systematic review; Technology Uses in Education; Technology-mediated educational innovations in Latin American higher education institutions
• ISSN: 2365-9440; 2365-9440
• DOI: 10.1186/s41239-022-00326-w

Over the last decade, there has been great research interest in the application of artificial intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has been a research focus on the application of AI in education, where it has great potential. Therefore, a systematic review of the literature on AI in education is therefore necessary. This article considers its usage and applications in Latin American higher education institutions. After identifying the studies dedicated to educational innovations brought about by the application of AI techniques, this review examines AI applications in three educational processes: learning, teaching, and administration. Each study is analyzed for the AI techniques used, such as machine learning, deep learning, and natural language processing, the AI tools and algorithms that are applied, and the main education topic. The results reveal that the main AI applications in education are: predictive modelling, intelligent analytics, assistive technology, automatic content analysis, and image analytics. It is further demonstrated that AI applications help to address important education issues (e.g., detecting students at risk of dropping out) and thereby contribute to ensuring quality education. Finally, the article presents the lessons learned from the review concerning the application of AI technologies in higher education in the Latin American context.