IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE TOOLS IN EDUCATION: A SCOPE REVIEW
Abstract
The use of Artificial Intelligence (AI) tools in education has become increasingly prevalent in recent years, especially following the advancement of generative models. Teachers have begun to adopt these technologies to automate tasks, create instructional materials, personalize activities, analyze open-ended responses, and monitor the learning process with greater precision. Despite this growth, there are still uncertainties and challenges related to how these tools are implemented in teaching practice. This paper presents a scoping review that brings together and analyzes recent studies on the use of AI by teachers, aiming to understand how these technologies are being applied, what benefits are perceived, and which difficulties persist. In this context, eith relevant studies were analyzed, and it was observed that AI contributes to the personalization of learning, optimizes teachers’ working time, and enhances understanding of students’ thinking processes. However, significant limitations were also identified, such as lack of training, ethical concerns, insufficient infrastructure, and difficulties in pedagogical integration. The present study points to possible pathways for the critical and responsible use of AI, while also highlighting the importance of teacher mediation to ensure that these tools contribute meaningfully to education. These findings reinforce the need for aligned and continuous educational policies.
Author Biographies
Undergraduate student in Computer Science at Universidade Federal da Paraíba and PIBIC scholarship holder, with research experience in artificial intelligence, automation, and computational systems. Works in laboratories at Universidade Federal da Paraíba developing interdisciplinary studies involving applied AI, neuroscience, and neurotechnology techniques.
Undergraduate student in Computer Engineering at Universidade Federal da Paraíba and PIBIC scholarship holder, working in research and development of web applications, IoT systems, and artificial intelligence. Participates in projects at the Systems Engineering and Robotics Laboratory (L.A.S.E.R) of Universidade Federal da Paraíba.
Ph.D. from the Graduate Program of the Department of Electrical Engineering at Universidade Federal de Campina Grande (2019). Professor of higher education at Universidade Federal da Paraíba in the area of Digital Systems and Embedded Systems.
Ph.D. in Computer Science from Universidade Federal do Ceará and Assistant Professor at Universidade Federal Rural do Semi-Árido (UFERSA). Leads the Software Innovations Laboratory (LIS), with research interests in Databases, Big Data, Data Streams, NoSQL, Data Warehousing, and data management.
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