BIG DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE IN PROFESSIONAL AND TECHNOLOGICAL EDUCATION: ADVANCED STRATEGIES FOR DEVELOPING BNCC COMPETENCIES IN SECONDARY AND TECHNICAL EDUCATION
Álaze Gabriel do
Breviário
Master
of Theology.
Master
of Psychology.
Ivy
Enber Christian University (IECU).
Orlando,
Florida, United States.
Email:
alaze_p7sd8sin5@yahoo.com.br.
URL
Lattes: http://lattes.cnpq.br/9973998907456283.
ORCID: https://orcid.org/0000-0002-9480-6325.
Jaine Marques de Souza
Specialist
in Special Education. Portuguese Language Teacher.
ICM
School.
Email:
sousajaine9@gmail.com.
URL
Lattes: http://lattes.cnpq.br/2760508798931944.
João Batista Lucena
Master's student in Education.
Federal Institute of Education, Science and Technology of Rio
Grande do Norte, IFRN.
Natal, Rio Grande do Norte, Brazil.
Email: joao.batista.lucena@gmail.com.
URL Lattes: http://lattes.cnpq.br/2822567703207399.
Logan Faedda Rago
Master of Science in Education and Christian Ethics.
Ivy Enber Christian University, IECU.
Orlando, Florida, United States.
Email: loganfaedda@hotmail.com.
URL Lattes: https://lattes.cnpq.br/2516880221903287.
Marcelo D’Ávilla
Teixeira Gomes
Master in
Social Management, Education and Regional Development.
Vale do Cricaré
University Center (UNIVC). São Mateus, ES, Brazil.
Professor at
the Municipal Department of Education of São Mateus (ES).
E-mail: cpldavilla@gmail.com.
URL Lattes: https://lattes.cnpq.br/3740114889508259.
ORCID: https://orcid.org/0009-0003-3471-225X.
Deusirene Sousa da Silva
Fróes
PhD candidate in Education Sciences and Christian Ethics.
Ivy Enber Christian University, IECU.
Orlando, Florida, United States.
Email: deusirenesousasilvafroes@gmail.com.
URL Lattes: https://lattes.cnpq.br/0218139923264576.
ABSTRACT
This research addresses the integration of
Big Data Analytics and Artificial Intelligence (AI) in professional and
technological education, highlighting their potential to meet the competencies
of the National Common Curricular Base (BNCC). Contextualized in the need to
modernize technical education in Brazil, the problem investigated how these
technologies can be implemented to personalize learning, reduce educational
inequalities, and train teachers. The general objective was to analyze the
applicability of these tools in the development of technical and pedagogical
competencies aligned with the BNCC. Methodologically, the research adopted the
Gifted neoperspectivist paradigm and the theories of Complexity, Meaningful
Learning, Big Data, and Inclusive Education. The hypothetical-deductive method
guided the investigation, complemented by a Narrative Bibliographic and
Documentary Review that consulted databases such as Scopus, Web of Science and
SciELO, analyzing 47 selected works. The main findings include the
effectiveness of technologies in personalizing teaching, promoting student engagement
and reducing inequalities, although barriers such as insufficient
infrastructure and limitations in teacher training were identified. The
contributions cover theoretical and methodological advances, as well as
practical recommendations for the application of technologies in technical
education. Limitations include the absence of experimental studies and the
reliance on secondary data. This research adds value by expanding the
possibilities of inclusive pedagogical practices and strengthening the debate
on digital transformation in education.
Keywords: Educational Personalization. Technological Inclusion. Pedagogical Competencies. Digital Transformation. Teacher Training.