Available via license: CC BY 4.0
Content may be subject to copyright.
Rev. Gest. Soc. Ambient. | Miami | v.18.n.10 | p.1-19 | e09522 | 2024.
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RGSA – Revista de Gestão Social e Ambiental
ISSN: 1981-982X
Submission date: 07/19/2024
Acceptance date: 09/20/2024
DOI: https://doi.org/10.24857/rgsa.v18n10-326
Organization: Interinstitutional Scientific Committee
Chief Editor: Ana Carolina Messias de Souza Ferreira da Costa
Assessment: Double Blind Review pelo SEER/OJS
CHALLENGES AND OPPORTUNITIES OF ARTIFICIAL INTELLIGENCE IN
PUBLIC EDUCATION: A CASE STUDY IN BARÃO DOS COCAIS - MG
Érika Márcia Assis de Souza
1
Erika Silva Fabri
2
Wagner dos Reis Marques Araújo
3
Wagner Cavalare de Souza
4
Sara Isabel de Melo Resende
5
Hélio Augusto Goulart Diniz
6
ABSTRACT
Objective: Considering the use of Artificial Intelligence (AI) by teachers in public high schools in Barão de Cocais
faces challenges, such as the lack of specific training and inadequate infrastructure, along with concerns about
pedagogical autonomy, the objective is to investigate the impacts of these technological tools on the teaching-
learning process.
Theoretical Framework: This research presents the main concepts and theories that underlie the work. The use
of artificial intelligence in public education, the ethical and pedagogical challenges of using artificial intelligence
in teaching and the infrastructure and public policies for artificial intelligence in education stand out, providing a
solid basis for understanding the context of the investigation.
Method: A qualitative methodology is applied, based on semi-structured interviews with teachers, aiming to
capture their experiences and perceptions regarding the use of AI in their pedagogical practices.
Results and Discussion: The results obtained revealed that it is essential to incorporate digital skills development
into teacher training curricula, in addition to promoting public policies that encourage the conscious and
appropriate use of AI in the educational context.
Research Implications: Content analysis allows the identification of patterns and recurring themes, providing a
broad understanding of the implications of this technology in education. It is observed that AI is seen by teachers
as a promising tool, particularly for automating tasks and personalizing learning. However, there is a significant
gap in teacher training and in the schools’ infrastructure, hindering more efficient adoption.
Originality/Value: This study contributes to the emerging literature on the implementation of AI in Brazilian
public education, offering valuable insights into the challenges and opportunities surrounding the adoption of these
technologies in educational institutions in specific regions, such as Barão de Cocais.
Keywords: Artificial Intelligence, Public education, Teacher training, Teaching-learning, Educational
technologies.
1
Universidade do Estado de Minas Gerais (UEMG), João Monlevade, Minas Gerais, Brazil.
E-mail: erikamarcia.souza@gmail.com Orcid: https://orcid.org/0000-0002-9355-1914
2 Universidade do Estado de Minas Gerais (UEMG), João Monlevade, Minas Gerais, Brazil.
E-mail: erika.fabri@uemg.br Orcid: https://orcid.org/0009-0002-9186-6530
3 Universidade do Estado de Minas Gerais (UEMG), Carangola, Minas Gerais, Brazil.
E-mail: marquesreis@hotmail.com Orcid: https://orcid.org/0000-0003-0793-0043
4 Universidade do Estado de Minas Gerais (UEMG), João Monlevade, Minas Gerais, Brazil.
Rede de Ensino Doctum, João Monlevade, Minas Gerais, Brazil. E-mail: wcavalare2005@yahoo.com.br
Orcid: https://orcid.org/0000-0001-6253-1067
5 Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil.
E-mail: sara_sidmr@yahoo.com.br Orcid: https://orcid.org/0009-0005-3604-1044
6 Universidade do Estado de Minas Gerais (UEMG), João Monlevade, Minas Gerais, Brazil.
Centro Universitário Estácio de Belo Horizonte (Bolsista do Programa Pesquisa Produtividade), Belo Horizonte,
Minas Gerais, Brazil. E-mail: helioufmg@gmail.com Orcid: https://orcid.org/0000-0002-5614-1561
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DESAFIOS E OPORTUNIDADES DA INTELIGÊNCIA ARTIFICIAL NO ENSINO PÚBLICO: UM
ESTUDO DE CASO EM BARÃO DOS COCAIS – MG
RESUMO
Objetivo: Considerando que o uso de Inteligência Artificial (IA) por professores nas escolas públicas de ensino
médio de Barão de Cocais enfrenta desafios, como a falta de formação específica e infraestrutura inadequada, além
de preocupações com a autonomia pedagógica, o objetivo deste estudo é investigar os impactos dessas ferramentas
tecnológicas no processo de ensino-aprendizagem.
Referencial Teórico: Esta pesquisa apresenta os principais conceitos e teorias que fundamentam o trabalho.
Destacam-se o uso da inteligência artificial na educação pública, os desafios éticos e pedagógicos do uso da
inteligência artificial no ensino e a infraestrutura e políticas públicas para a inteligência artificial na educação,
fornecendo uma base sólida para a compreensão do contexto da investigação.
Método: Aplica-se uma metodologia qualitativa, baseada em entrevistas semiestruturadas com professores,
buscando capturar suas experiências e percepções sobre a utilização da IA em suas práticas pedagógicas.
Resultados e Discussão: Os resultados obtidos revelaram que é essencial incorporar o desenvolvimento de
habilidades digitais ao currículo de formação de professores, além de promover políticas públicas que incentivem
o uso consciente e adequado da IA no contexto educacional.
Implicações da Pesquisa: A análise de conteúdo permite identificar padrões e temas recorrentes, proporcionando
uma visão ampla das implicações dessa tecnologia no ensino. Desse modo, observa-se que a IA é vista pelos
professores como uma ferramenta promissora, especialmente para automação de tarefas e personalização do
aprendizado. No entanto, há uma lacuna significativa na formação docente e na infraestrutura das escolas,
dificultando uma adoção mais eficiente.
Originalidade/Valor: O estudo contribui para a literatura emergente sobre a implementação de IA no ensino
público brasileiro, fornecendo insights valiosos sobre os desafios e oportunidades que envolvem a adoção dessas
tecnologias em instituições de ensino de regiões específicas como Barão de Cocais.
Palavras-chave: Inteligência Artificial, Educação pública, Formação de professores, Ensino-aprendizagem,
Tecnologias educacionais.
DESAFÍOS Y OPORTUNIDADES DE LA INTELIGENCIA ARTIFICIAL EN LA EDUCACIÓN
PÚBLICA: UN ESTUDIO DE CASO EN EL BARRIO DOS COCAIS - MG
RESUMEN
Objetivo: Considerando que el uso de Inteligencia Artificial (IA) por parte de los profesores en las escuelas
públicas de educación secundaria en Barão de Cocais enfrenta desafíos, como la falta de formación específica y la
infraestructura inadecuada, además de preocupaciones sobre la autonomía pedagógica, el objetivo es investigar los
impactos de estas herramientas tecnológicas en el proceso de enseñanza-aprendizaje.
Marco Teórico: Esta investigación presenta los principales conceptos y teorías que subyacen al trabajo. Se
destacan el uso de la inteligencia artificial en la educación pública, los desafíos éticos y pedagógicos del uso de la
inteligencia artificial en la enseñanza y la infraestructura y políticas públicas para la inteligencia artificial en la
educación, brindando una base sólida para comprender el contexto de la investigación.
Método: La metodología adoptada para esta investigación es una metodología cualitativa basada en entrevistas
semiestructuradas con los profesores, con el fin de captar sus experiencias y percepciones sobre el uso de la IA en
sus prácticas pedagógicas.
Resultados y Discusión: Los resultados obtenidos llevan a la conclusión de que es esencial incorporar el desarrollo
de habilidades digitales en los programas de formación de profesores, además de promover políticas públicas que
fomenten el uso consciente y adecuado de la IA en el contexto educativo.
Implicaciones de la investigación: El análisis de contenido permite identificar patrones y temas recurrentes,
proporcionando una comprensión amplia de las implicaciones de esta tecnología en la educación. Se observa que
Challenges and Opportunities of Artificial Intelligence in Public Education: A Case Study in Barão Dos Cocais –
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los profesores ven la IA como una herramienta prometedora, especialmente para la automatización de tareas y la
personalización del aprendizaje. Sin embargo, existe una brecha significativa en la formación docente y en la
infraestructura de las escuelas, lo que dificulta una adopción más eficiente.
Originalidad/Valor: Este estudio contribuye a la literatura emergente sobre la implementación de IA en la
educación pública brasileña, ofreciendo valiosas ideas sobre los desafíos y oportunidades relacionados con la
adopción de estas tecnologías en instituciones educativas en regiones específicas como Barão de Cocais.
Palabras clave: Inteligencia Artificial, Educación pública, Formación docente, Enseñanza-aprendizaje,
Tecnologías educativas.
RGSA adota a Licença de Atribuição CC BY do Creative Commons (https://creativecommons.org/licenses/by/4.0/).
1 INTRODUCTION
The incorporation of Artificial Intelligence (AI) into the educational environment has
been a global trend, promoting debates about its impact on the personalization of teaching and
the automation of pedagogical tasks. However, in the context of Brazilian public schools, this
adoption faces significant barriers, mainly related to the lack of specific public policies and
inadequate infrastructure.
According to Selwyn (2019), while AI has the potential to transform education by
offering new forms of engagement and learning, its application is still limited by the resilience
of some teachers and the absence of ongoing training. In many public schools, such as those of
Barão de Cocais, this reality is reflected in the difficulty teachers have in integrating these
technologies into their daily practices.
To Holmes et al. (2019), lack of institutional preparation and support is one of the main
barriers to effective AI uptake in education, as teachers often lack the resources to adapt to
technological innovations. Furthermore, Rogers (2003), in his model of diffusion of
innovations, points out that the adoption of new technologies by teachers tends to be a gradual
process and influenced by factors such as the available infrastructure and the support offered
by the institution.
The research of Reyes-Villalba et al. (2024) aimed to examine current educational
practices related to the understanding and use of artificial intelligence in the educational field.
The authors concluded that while there is a variety of educational practices involving AI,
challenges such as lack of resources, teacher training, and ethical issues still persist. Lengua-
Cantero et al. (2024) explored the relationship between autonomous learning, artificial
intelligence and 21st century skills. The researchers concluded that, while artificial intelligence
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is still in development, it is strongly related to autonomous learning and skills such as critical
thinking, collaborative work and problem solving.
Faced with these challenges, this study seeks to investigate the use of AI by teachers in
public secondary schools in Barão de Cocais, analyzing both the perceived benefits and the
obstacles faced in the process of implementing these tools. The research aims to provide
valuable insights into how AI can be effectively integrated into the Brazilian educational
context, with a focus on the insights and experiences of local teachers. Understanding these
dynamics is essential for the development of public policies that encourage the conscious and
efficient adoption of AI in schools, promoting more inclusive and personalized teaching.
2 THEORETICAL FRAME
2.1 ARTIFICIAL INTELLIGENCE IN EDUCATION
According to Selwyn (2019), Artificial Intelligence (AI) has played an increasingly
important role in a number of sectors, including education. The use of AI in the educational
environment is expanding the possibilities of teaching personalization, automation of
pedagogical processes and predictive analysis of student performance. With the help of
advanced technologies, AI can provide education more tailored to students’ individual needs,
optimizing teacher time and promoting more efficient management of administrative tasks.
According to Luckin (2018), AI has the potential to profoundly transform education by
creating systems that can adjust content according to the learner's pace of learning, identifying
knowledge gaps, and suggesting resources to meet those needs.
One of the main applications of AI in the educational environment is the implementation
of intelligent tutoring systems. These systems, as pointed out by Holmes et al. (2019), are able
to offer personalized support to students, adapting the content according to their needs and
difficulties, promoting a more autonomous and efficient learning. Intelligent tutoring systems
use machine learning algorithms to analyze student performance in real time, identifying
learning patterns and adjusting the pedagogical approach according to the data collected
(Zawacki-Richter et al., 2019). In addition to helping to personalize teaching, these tools also
help reduce the workload for teachers, who can focus their efforts on more complex and
strategic activities.
Another relevant aspect of AI use in education is predictive analysis of student
performance. This technology, as discussed by Williamson (2017), allows teachers and
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educational managers to early identify students at risk of avoidance or poor performance,
enabling more effective preventative interventions. From large volumes of data on student
behavior, AI algorithms can predict which students are struggling and suggest strategies to
improve their performance. According to Holmes et al. (2019), this ability to predict and
anticipate problems can revolutionize educational management by allowing interventions to be
more targeted and evidence-based.
In addition, the automation of administrative tasks is another significant potential of AI
in the school context. AI-based systems can automate activities such as test correction,
frequency records, and the organization of teaching materials, freeing teachers to focus on
activities that require greater human interaction and creativity (Luckin, 2018). Automation can
also improve the efficiency of school management by making it easier to monitor students’
academic performance and make data-driven decisions.
While the potential of AI in education is promising, it is important to recognize the
challenges that this technology presents. Integrating AI in schools requires a robust technology
infrastructure and public policies that support its implementation. In addition, as discussed by
Selwyn (2019), there are significant ethical concerns surrounding the use of AI in education,
particularly regarding the privacy of students' data and the possibility of dehumanizing
pedagogical relationships. If AI is to be fully integrated positively into the educational
environment, a balance must be struck between the use of technology and respect for traditional
pedagogical principles, which value the teacher's role as a knowledge mediator.
As pointed out by Dias and Moraes (2023), AI offers a range of tools and resources that
can transform education, from personalizing teaching to automating tasks and predictive
analysis of student performance.
However, Dias e Moraes (2023) points out that for these technologies to be effectively
incorporated, it is essential that teachers receive adequate training and that schools have
sufficient infrastructure to support these innovations. Only in this way will it be possible to
make full use of the potential of AI in the educational environment, promoting a more inclusive
teaching and adapted to the needs of each student.
2.2 ADOPTION OF EDUCATIONAL TECHNOLOGIES BY TEACHERS
The adoption of educational technologies by teachers is a complex process, influenced
by a number of factors ranging from structural issues to cultural and individual aspects. Rogers's
diffusion model of innovations (2003) provides a robust theoretical framework for
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understanding how new technologies, such as Artificial Intelligence (AI), are incorporated into
pedagogical practices. According to Rogers (2003), the process of adopting innovations follows
five stages: knowledge, persuasion, decision, implementation and confirmation. These steps
help explain why some teachers quickly adopt new technologies, while others face resistance
or delay.
The first stage, knowledge, refers to the moment when teachers become aware of a new
technology, such as AI, and begin to form an initial understanding of its functioning and
potential. This phase is crucial, as access to information and training on AI use directly
influences the level of interest and acceptance by teachers (Selwyn, 2019). The absence of
specific training programs for the integration of AI into pedagogical practices may slow this
process, as many teachers do not have adequate knowledge about how these tools can be applied
in teaching.
The persuasion phase involves the formation of a positive or negative attitude towards
innovation. At this point, perceptions about the benefits and challenges of using AI in education
play a key role. Holmes et al (2019) points out that teachers tend to adopt new technologies
more easily when they realize clear benefits for student learning, such as personalizing teaching
and automating administrative tasks. However, worries about overwork, lack of technical
support, and loss of pedagogical autonomy can lead to negative attitudes, making it difficult to
adopt AI.
At the decision stage, the professor chooses to adopt or to reject the innovation. Rogers
(2003) argues that this decision is often influenced by the school context and available
resources. In schools where there is adequate infrastructure and supporting policies for the
implementation of new technologies, the decision to adopt AI tends to be easier. On the other
hand, in environments where technological equipment and specific training are lacking, the
tendency is for teachers to choose not to use AI in their pedagogical practices.
According to Fullan (2015), the adoption of innovations is most effective when there is
an institutional commitment to change, which includes providing resources and ongoing
support.
The implementation stage refers to the practical use of innovation in the educational
context. In this respect, the integration of AI into pedagogical practices depends not only on
technical knowledge, but also on the adaptation of teaching methodologies to include new tools.
As Selwyn (2019) points out, the success of AI implementation is strongly linked to teachers’
continued education and their ability to tailor technologies to the specific needs of their students
and classes.
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Finally, the confirmation phase occurs when the teacher reflects on the use of the
technology and decides to continue using it or abandon it. At this stage, student feedback,
institutional support, and results observed in academic performance influence the decision to
maintain AI use. As pointed out by Ertmer and Ottenbreit-Leftwich (2010), teachers are more
likely to continue using technology when they notice tangible improvements in student learning
and have access to ongoing technical support.
The adoption of educational technologies, such as AI, does not occur in an isolated
manner. Rogers (2003) emphasizes that factors such as social context, teacher characteristics,
and school infrastructure play a significant role in the adoption process. Teachers working in
schools with a culture of innovation and robust technological support are more likely to adopt
new technologies quickly. On the other hand, in schools with poor infrastructure and lack of
incentive policies, adoption tends to be slow and uneven. This is especially relevant in the case
of AI, which requires not only access to technological equipment, but also an institutional
environment that favors experimentation and continuous learning (Williamson, 2017).
In addition, resilience to change is a common challenge in adopting educational
technologies. As Rogers (2003) points out, many teachers are reluctant to adopt innovations
that significantly change their routines or that require major adaptation efforts. To overcome
this resistance, schools must provide ongoing support, such as teacher training programs,
adequate infrastructure, and opportunities for teachers to experience and share their experiences
with the new technology (Fullan, 2015). Creating a community of practice where teachers can
collaborate and learn from each other can also facilitate the adoption of technological
innovations.
2.3 ARTIFICIAL INTELLIGENCE IN PUBLIC EDUCATION
The insertion of Artificial Intelligence (AI) in the context of Brazilian public schools
faces a series of challenges, both for educators and for students. One of the main obstacles is
the lack of public policies that encourage the dissemination of this technology, especially in
areas without adequate internet coverage and with poor physical infrastructure. The lack of
technological support in educational institutions limits the implementation of innovative digital
projects, essential for the development of more dynamic pedagogical practices adapted to the
needs of contemporary society.
The resistance of education professionals themselves to the use of new information and
communication technologies (ICTs) aggravates the scenario. Many teachers, due to lack of
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knowledge or specific training, encounter difficulties in handling digital tools, which creates a
mismatch between the rapid technological evolution and the reality of public schools. As
Tardelli and Paula (2011) point out, students born in the digital age deal with these innovations
in a natural way, while many teachers still see the act of teaching in a traditional way, which
generates insecurity in relation to the use of AI and other technologies.
In this sense, globalization and the scientific-technological revolution have significantly
altered social relations and the labor market, which demands a reconfiguration not only of
educational policies, but also of the role of the teacher and the school structure itself (Tardelli
and Paula, 2011).
However, many educational systems are still based on outdated practices, which
contribute little to the training of students able to face the challenges of modern society.
According to Morin (2009), it is necessary to abandon a fragmented education that separates
knowledge into disconnected blocks and adopt a more holistic approach, capable of
understanding the complexity of the world and preparing young people to interact critically
with new technologies.
This reflection leads to the need to rethink the school curriculum. Children and young
people already master many of the available technologies outside the school environment,
including AI, without any pedagogical guidance. As Tedesco (2015) points out, the creation of
a just society in the future depends on the ability to design an education that values the conscious
and critical use of these technologies, preventing them from being used inadequately, as is often
observed in digital media.
2.4 CUSTOMIZATION OF EDUCATION WITH AI
Teaching personalization is one of the main promises of Artificial Intelligence (AI) in
the educational field, offering the possibility to adapt the content to the rhythm and individual
needs of each student.
According to Martins and Rocha (2023), AI allows learning platforms to analyze real-
time data about student performance, automatically adjusting content and activities to optimize
understanding and retention of information.
This type of personalization, as pointed out by Ferreira and Gonçalves (2023), goes
beyond traditional differentiation, creating a highly adapted learning experience that enhances
each student's abilities.
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In addition, AI can automate repetitive tasks such as exercise correction and progress
monitoring, freeing teachers to focus on activities that require more creativity and human
interaction (Garcia and Santos, 2023).
However, as noted by Selwyn (2019) and Holmes et al. (2019), that approach is not
without limitations. Dependence on algorithms can reduce the complexity of the teaching
process, since pedagogical decisions are in part transferred to automated systems, which can
lead to superficiality in teaching more complex skills such as critical thinking and creativity.
In short, AI has the potential to transform teaching by adapting content accurately and
quickly to each student's needs. However, it is crucial that educators play an active role in
integrating these technologies to ensure that personalization does not replace human interaction,
which is essential in the educational process.
2.5 ETHICAL AND EDUCATIONAL CHALLENGES OF AI IN EDUCATION
The implementation of AI in education raises a number of ethical and pedagogical
challenges, which need to be carefully considered. One of the main challenges concerns the
privacy of student data. As Braga and Costa (2023) state, AI platforms collect and analyze large
volumes of personal data, which can expose sensitive student information. The lack of clear
regulation on the use of such data increases the risk of privacy violations, making it necessary
to develop strict policies that ensure the protection of information.
Another important ethical aspect is the issue of equal access to technology. In many
contexts, technological infrastructure is inadequate, which hinders widespread adoption of AI
in public schools, especially in more vulnerable regions (Tardelli and Paula, 2011). Lima and
Souza (2023) highlight that this technological inequality may exacerbate educational
disparities, leaving behind students who do not have access to suitable devices or the internet.
Finally, there is the concern that the adoption of AI devalues the role of the teacher in
the teaching-learning process. While AI can be a valuable tool to support teaching work, it is
critical that the teacher remains the primary mediator in the educational process.
As Morin (2009) emphasizes, education should not be fragmented or reduced to
algorithms; it should promote an integral and complex understanding of the world. In this sense,
AI should be seen as a resource to enhance the work of the teacher, and not as a replacement.
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2.6 INFRASTRUCTURE AND PUBLIC POLICIES FOR AI IN EDUCATION
Technological infrastructure in public schools is one of the main factors limiting the
effective adoption of AI in education. Lack of adequate equipment, quality internet connection
and technical support are barriers that make it difficult to implement these technologies in a
comprehensive and equitable manner.
According to Vicari (2018), most Brazilian schools still lack basic resources to integrate
technological innovations, which makes full adoption of AI unfeasible.
In this context, public policies play a crucial role in creating an enabling environment
for the implementation of AI in schools. As Almeida e Silva (2023) argues, it is necessary for
the government to invest in technological infrastructure, ensuring that all schools, regardless of
their geographic location or socioeconomic condition, have access to the tools necessary to
incorporate AI into the teaching-learning process. In addition, public policies should promote
teacher training so that teachers are able to use these technologies effectively and ethically
(Barros et al., 2024).
2.7 CONTINUED TEACHER TRAINING FOR AI
Continued teacher training is an essential element for the successful integration of AI
into education. Most teachers, especially in public schools, have not yet received adequate
training to use emerging technologies in their pedagogical practices (Carvalho, 2023). This
creates a significant gap between the potential of AI and its practical application in the
classroom.
To overcome this challenge, it is necessary to redesign the teacher training curricula,
incorporating digital and technological skills as an integral part of future teacher education
(Tedesco, 2015). Braga and Costa (2023) argue that training programs should go beyond simple
technical training and also address the pedagogical and ethical implications of AI use,
promoting a critical reflection on how these tools can be used in a balanced way.
Continued training, as Dias and Moraes (2023) point out, should be an ongoing process,
accompanying technological innovations and offering constant support to teachers. This
includes not only the development of technological skills, but also the creation of spaces for
dialog and exchange of experiences among teachers, so that they can share challenges and
solutions in the use of AI.
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3 METHODOLOGY
This research follows a qualitative approach, carried out in three public elementary and
high schools located in the municipality of Barão de Cocais, Minas Gerais. The main objective
was to investigate the use of Artificial Intelligence (AI) by teachers at these institutions,
examining the impact of these tools on the teaching-learning process, as well as identifying the
main challenges and benefits perceived by incorporating these technologies into pedagogical
practices. The choice of a qualitative approach, as advocated by Creswell (2014), allows for a
deep and detailed understanding of social phenomena in specific contexts, offering valuable
insights into participants' experiences and perceptions.
The data collection was carried out through semi-structured interviews with the teachers
of the three selected schools. According to Flick (2009), this type of interview makes it possible
to explore in depth the experiences and perceptions of the participants, maintaining flexibility
so that new emerging issues are addressed throughout the conversation. The participants were
intentionally selected, as suggested by Patton (2002), considering their direct involvement with
high school education and the use of technological tools, in order to ensure a sample aligned
with the research objectives.
Data analysis followed the content analysis technique, which, according to Bardin
(2011), allows one to identify patterns and recurring themes from the systematic organization
of the data. The interviews were transcribed and categorized based on previously established
topics such as the level of AI adoption, infrastructure challenges, teacher training, and perceived
impacts on student learning. This approach facilitates the identification of structural barriers
and opportunities provided by AI in the educational context.
In addition to the interviews, field observations were conducted in the three schools, as
recommended by Lüdke and André (2013), to understand the daily use of technologies in the
school environment and how teachers integrate these resources into their pedagogical practices.
The observations served to contextualize the lecturers' talks and to offer a broader vision of the
technological reality of the institutions investigated.
Finally, the triangulation of data - derived from interviews, observations and
documentary analysis - followed the principles described by Denzin (2006), guaranteeing
methodological rigor and greater reliability of the results. This procedure allowed to verify the
consistency between the data sources and to identify divergences in the teachers' responses,
providing a more comprehensive and detailed understanding of the dynamics and challenges
associated with the implementation of AI in public education in Barão de Cocais.
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4 RESULTS AND DISCUSSIONS
The results of this research, carried out with 54 teachers in three public high schools of
Barão de Cocais, revealed mixed perceptions about the use of Artificial Intelligence (AI) in the
school environment. The interviews and observations conducted indicated four main themes:
adaptation and use of AI in pedagogical practices, infrastructure challenges, teacher training
and perception of impacts on learning.
4.1 ADAPTATION AND USE OF AI IN PEDAGOGICAL PRACTICES
Figure 1 illustrates the percentage of AI use in schools. Most of the teachers interviewed,
41 out of 54 (76%), professors, recognized that Artificial Intelligence has great potential,
especially when applied to the personalization of teaching and the automation of administrative
tasks, such as automatic correction of exercises and the continuous monitoring of students'
progress. Of the 54 interviewees, 33 (61%) realized that AI could facilitate the adaptation of
activities to each student's level of learning, which would increase the engagement and
efficiency of the teaching process. However, only 16 teachers (30%) reported systematically
using these tools in their school day-to-day.
Figure 1
Use of AI in Pedagogical Practices.
Challenges and Opportunities of Artificial Intelligence in Public Education: A Case Study in Barão Dos Cocais –
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Among the 16 teachers who use AI, the most cited application was the use of digital
platforms with automatic learning algorithms for planning classes and creating personalized
activities for different profiles of students. They reported that AI helps monitor students’
performance and identify their difficulties faster and more accurately. However, despite these
advances, 38 teachers (70%) are still in the early stages of adopting these technologies and face
challenges in integrating them into their traditional methodologies. The main obstacle identified
by 18 teachers (86%) was the lack of adequate resources, in addition to the complexity involved
in learning and integrating new technological tools into school life.
4.2 INFRASTRUCTURE CHALLENGES
Figure 2 presents the answers on infrastructure conditions in schools. All 54 teachers
interviewed (100%) pointed to inadequate technological infrastructure as a critical barrier to the
implementation of AI in the public schools of Barão de Cocais. The lack of high-quality internet
connection and the scarcity of equipment such as computers, tablets and smartphones have been
identified as factors hindering the full adoption of AI tools. In some schools, 36 teachers (67%)
reported that the internet connection is so unstable that it does not allow continued use of AI-
based educational platforms. This severely restricts both students' and teachers' access to these
innovative technological resources.
Figure 2
Infrastructure conditions in schools.
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In addition, 47 teachers (87%) stated that the equipment available in schools is obsolete
or insufficient to meet the needs of the entire school community. Teachers reported that they
need to improvise using their own personal devices or adapting traditional methods due to the
technological limitation available. These structural challenges result in a significant disparity
in opportunities for students from different backgrounds, widening educational inequalities.
4.3 TEACHER TRAINING
Figure 3 presents the answers on teacher training and training. Another limiting fatora
highlighted by 41 teachers (76%) was the absence of continuous and specific training for the
use of emerging technologies, such as AI. These faculty members have reported that they feel
unprepared to use these tools effectively, resulting in limited or superficial adoption of AI
technologies. Only 13 teachers (24%) reported having participated in some type of training
aimed at the use of AI in pedagogical contexts, while the other 41 teachers (76%) never received
guidance on how to integrate these tools efficiently into traditional teaching practices.
Figure 3
Teacher Training and Training.
Without this training, 31 faculty members (57%) were reluctant to adopt AI more
broadly, and those trying to integrate AI into their practices reported difficulties in developing
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a cohesive pedagogical approach that harnesses the full potential of technology. This lack of
training also contributes to a widespread feeling of insecurity, cited by 36 teachers (62%), which
directly affects their confidence in the use of AI in the educational environment.
4.4 PERCEIVED IMPACTS ON LEARNING
Figure 4 presents the responses on the impacts of AI. The 16 teachers already using AI-
based tools (29%) noted a positive impact on student engagement, especially among those with
learning difficulties. All 6 reported that AI's ability to customize activities and adapt the pace
of teaching to students' specific needs was one of the main benefits observed. According to
these professors, this personalization not only improves the performance of students with
difficulties, but also increases their interest and participation in educational activities.
Figure 4
Perceptions of the Impacts of AI.
However, 23 teachers (43%) expressed concerns about the impacts of AI on the
pedagogical process. The main concern, reported by 36 professors (62%), is that the excessive
dependence on technology may devalue the role of the professor, jeopardizing the development
of socio-emotional skills and critical thinking in the students. In addition, 16 teachers (29%)
mentioned that AI, by automating certain tasks, could lead teachers to focus excessively on
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technical and bureaucratic aspects, to the detriment of promoting creativity and social
interaction.
Another point highlighted by 26 professors (48%) was the concern with equity. While
AI can personalize teaching, they fear that students with limited access to technology will be
even further away from their peers who have better infrastructure. Such inequality in access to
technology could exacerbate existing educational disparities, especially among schools in more
vulnerable regions.
The results presented confirm the existing literature on the challenges of adopting AI in
the educational context, especially in areas with limited infrastructure. According to Selwyn
(2019), the lack of resources and teacher training are frequent barriers to technological
implementation, which corroborates the perceptions of Baron de Cocais' teachers. Although AI
is recognized for its potential in personalizing teaching (Holmes et al., 2019), the low level of
teacher training limits its effective adoption, as also noted by Rogers (2003) in his theory of
diffusion of innovations.
Discussion of the results further highlights that while AI can improve the quality of
teaching by allowing a personalized approach, its implementation cannot occur without
significant investments in technology infrastructure and ongoing teacher training, as suggested
by Williamson (2017). The limitations identified in this study, such as the lack of stable internet
and technological devices, are consistent with the challenges pointed out by Vicari (2018) in
the context of Brazilian public schools.
Among the limitations of this research, the fact that the study was conducted in only
three public schools in a specific region of Minas Gerais, which may limit the generalization of
the results to other regions of Brazil, is noteworthy. In addition, the focus on teacher perceptions
leaves gaps on the vision of students and school managers, who are also important actors in the
adoption of new educational technologies.
For future research, it is recommended to expand the study to include different regions
and types of schools, as well as to explore more deeply the experiences of students and
managers. It would also be relevant to investigate how different models of continuing education
can influence the adoption of AI and other emerging technologies in Brazilian public education.
5 CONCLUSION
This study sought to investigate the impact of the use of Artificial Intelligence (AI) in
the public high schools of Barão de Cocais, focusing on the perception of teachers and the
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barriers faced. The results showed that although AI is seen as a promising tool, mainly for the
personalization of teaching and task automation, its implementation faces serious challenges,
such as a lack of specific training for teachers and inadequate infrastructure in schools.
The findings confirm that although 61% of teachers recognize the potential of AI to
adapt teaching to students' individual needs, only a small proportion (30%) use it systematically.
The lack of technological resources, reported by all interviewees, as well as the absence of
continuous and specific training, were limiting factors for the wider adoption of these tools.
In practical terms, the research highlighted the importance of public policies that
promote access to adequate infrastructure and the training of teachers for the effective use of
AI in pedagogical practices. This will not only allow for greater digital inclusion in public
schools, but will also favor the creation of a more adaptable teaching environment responsive
to students' needs.
Therefore, the study contributes to the field of research by providing a detailed analysis
on the opportunities and limitations of AI in Brazilian public education. Furthermore, it
suggests that for AI to reach its full potential in education, it is essential that investments in
technology are accompanied by teacher training initiatives that can ensure that these tools are
used consciously and efficiently in the teaching-learning process.
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