Teaching Profiles And Artificial Intelligence In Higher Education In The State Of Paraná, Brazil.

Ayrosa, P.P.S & Moreira, J.A. (2025). Teaching Profiles And Artificial Intelligence In Higher Education In The State Of Paraná, Brazil [Video]. AcademyOn. https://academy-on.com/videos/vjhsr-v4i2-1148

This video aims to briefly explore and address three fundamental questions regarding the topic “Faculty and Artificial Intelligence in Higher Education in the State of Paraná, Brazil.” The three questions are: Is there interest in the topic of AI in higher education? What do we know about it? How can we profile those interested in order to design continuing education tailored to a specific audience? The methodological procedures adopted are presented and justified, and the results obtained are analyzed and discussed. Finally, the video is expected to contribute to the production of socially relevant knowledge about the digital competencies of faculty members in Paraná, with a view to informing proposals and professional development programs.

This article presents an exploratory data analysis conducted with a sample of 611 faculty members from seven public state universities in Paraná, Brazil. By applying artificial intelligence (AI) and data science techniques, participants were classified into three groups (clusters) based on four analytical dimensions: perceived AI competence, recognition of the urgency of the topic across teaching, research, outreach, and management areas, ethical stance toward AI use, and interest in continuing education. Principal Component Analysis (PCA) and clustering using the K-Means algorithm were employed. The analysis identified three distinct profiles: cautious veterans (or traditionalists), open realists (potential institutional articulators), and new enthusiasts (potential multipliers). The findings highlight the need for segmented and flexible training policies, with learning pathways tailored to the identified profiles.

The author acknowledges the support of the Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Estado do Paraná, within the scope of the activities funded by the project “Assessing and Training Higher Education Faculty in Artificial Intelligence: A Proposal Inspired by the DigCompEdu Framework.” He also extends his gratitude to the Center for Global Studies of the Universidade Aberta de Portugal (CEG-UAb) for hosting him in its postdoctoral program, which contributed to the development of this research.

Associate Professor at the Universidade Estadual de Londrina, affiliated with the Department of Computer Science. He holds a Ph.D. in Systems Engineering and Computer Science from the Universidade Federal do Rio de Janeiro (2001), a Master’s degree in the same field from UFRJ/COPPE (1992), and a Bachelor’s degree in Mathematics from the Universidade Federal Fluminense (1988). He has taught at the undergraduate, graduate specialization, and master’s levels in Computer Science. He served as a member of the Editorial Board of the publishing house of the Universidade Estadual de Londrina (Eduel). He is an institutional, program, and Distance Education (DE) evaluator for INEP, and also serves as an ad hoc expert in Distance Education for the Secretariat of Science and Technology of the State of Paraná. He currently serves as General Coordinator of the Center for Distance Education at UEL (NEAD-UEL), Local Coordinator of the Open University of Brazil (UAB), and Director of the Educational Technology Laboratory (LABTED). He is a member of the Management Group of the Virtual University of Paraná (UVPR) and acts as the institutional representative in the Talento Tech/PR Program. He is a researcher with NAPI Educação do Futuro and a member of the Teaching Practice Study Group (GEPE/UEL). His work focuses on Distance Education and Computer Science, with an emphasis on Artificial Intelligence research.