Hybrid Intelligence in the support to the distance higher education: conditions, possibilities and restrictions in an University

Authors

  • Jenifer Ferraz Calvi Universidade Cesumar (UniCesumar), Programa de Mestrado em Gestão do conhecimento, Maringá, PR, Brasil. jeniferferraz94@gmail.com https://orcid.org/0000-0003-0935-4529
  • Hilka Pelizza Vier Machado Universidade Cesumar (UniCesumar), Programa de Mestrado em Gestão do conhecimento, Maringá, PR, Brasil. hilkavier@yahoo.com https://orcid.org/0000-0002-2554-0025
  • Marcio Pascoal Cassandre Universidade Estadual de Maringá (UEM), Programa de Pós-Graduação em Administração, Maringá, PR, Brasil. mpcassandre@uem.br https://orcid.org/0000-0001-9415-4315
  • Igor da Penha Natal Universidade Federal de Uberlândia (UFU), Faculdade de Computação, Monte Carmelo, MG, Brasil. igor.natal@ufu.br https://orcid.org/0000-0001-5911-2048

DOI:

https://doi.org/10.21573/vol42n12026.145719

Keywords:

hybrid intelligence, Artificial intelligence, Organizations, Learning, Education

Abstract

The research aims to analyze the possibilities and limitations of using hybrid intelligence to support distance learning. The research is qualitative and uses the case study method, drawing on data from interviews and focus groups, as well as secondary sources. Content analysis resulted in three categories: conditions for the use of hybrid intelligence, possibilities for learning with hybrid intelligence, and restrictions on the use of hybrid intelligence. The results address the implementation, possibilities, and constraints of hybrid intelligence applications in the context analyzed.

Downloads

Download data is not yet available.

Author Biographies

Jenifer Ferraz Calvi, Universidade Cesumar (UniCesumar), Programa de Mestrado em Gestão do conhecimento, Maringá, PR, Brasil. jeniferferraz94@gmail.com

Master's degree in Knowledge Management in Organizations, specialization in Business Communication and Digital Marketing, Executive Education, Data Science and Bachelor's degree in Administration. For 11 years in the educational sector, working on several fronts, from CPD (data processing center), teaching, educational processes, management and consultancy. He is currently part of the innovation area at Vitru Educação, where he works with initiatives focused on a culture of innovation and the practical application of artificial intelligence.

Hilka Pelizza Vier Machado, Universidade Cesumar (UniCesumar), Programa de Mestrado em Gestão do conhecimento, Maringá, PR, Brasil. hilkavier@yahoo.com

PhD in Production Engineering from the Federal University of Santa Catarina (2002), Sandwich PhD from the École des Hautes Études Commerciales de Montreal (200-2001). Post-Doctorate from the Federal University of Natal and Visiting Researcher at the University of Bremen (UNIBREMEN, 2018). Retired professor at the State University of Maringá. Full Professor at UniCesumar University. Collaborating professor in the Doctorate Program in Administration at the Federal University of Paraná. Associate Editor of Brazilian Business Review. Leader of the International Entrepreneurship theme of the National Meeting of Postgraduate Programs in Administration - EnanPAD for the period 2025. Member of the Advisory Board of the National Association of Studies in Entrepreneurship and Small Business Management ANEGEPE. She is a researcher at the National Council for Scientific and Technological Development - CNPq and at the Cesumar Institute of Science, Technology and Innovation - ICETI. Peer Review College of the British Academy of Management (BAM) 2022-2023. Member of the National Committee for Gender Equality-2009-2010. Member and founding partner of the National Association for Studies in Entrepreneurship and Small Business Management - ANEGEPE. Author of several articles and reviewer for National and International Scientific Journals.

Marcio Pascoal Cassandre, Universidade Estadual de Maringá (UEM), Programa de Pós-Graduação em Administração, Maringá, PR, Brasil. mpcassandre@uem.br

Postdoctoral degree from the Danish School of Education at Aarhus University (Copenhagen), Learning, Innovation and Sustainability in Organizations (LISO) Program. PhD in Administration from Positivo University with sandwich period from the University of Helsinki at the Center for Research on Activity, Development and Learning (CRADLE). Holds a master's degree from the State University of Maringá (2008),  specialization in Marketing from the Institute of Social Sciences of Paraná (2002), specialization in Social Responsibility and Third Sector Organizations through  State Faculty of Economic Sciences of Apucarana (2004), degree in Administration  from the State Faculty of Economic Sciences of Apucarana (1998) and a degree in Psychology from Universidade Cesumar (2023). Worked as a state public servant since 2004 as a teacher. He is an associate professor in the department of Administration of the State University of Maringá,  teaching discipline in the area of ​​People Management, and in the Postgraduate Program in Administration of the same department, being in charge of the Practices disciplines Didactics in Administration, Organization Theory and  Organizational Learning. Director of the Office of International Cooperation from the State University of Maringá and editor of the journal Caderno of Administration at this university. Linked to the group
CRADLE researchers at the University of Helsinki. Coordinates the MEDIATA research group - Methodologies Interventionists and Transformative Learning. Experience in the area of ​​People Management, Strategic Planning, Organizational Learning, Qualitative Research Methodologies in
Administration, in addition to developing theoretical-empirical studies on the Interventionist research methodologies in organizations.

Igor da Penha Natal, Universidade Federal de Uberlândia (UFU), Faculdade de Computação, Monte Carmelo, MG, Brasil. igor.natal@ufu.br

Bachelor in Computer Science from Centro Universitário do Estado do Pará (CESUPA, 2011), Master in Computer Science from the Federal University of Pará (UFPA, 2015) and PhD in Computing from Universidade Federal Fluminense (UFF, 2020). He has experience in the area of ​​Computer Science, working mainly on the following topics: Computer Networks, Machine Learning, Data Mining, Deep Learning, Computer Programming, Human Activity Recognition and Artificial Intelligence.

References

ALPAYDIN, Ethem. Introduction to machine learning. MIT Press, 2020.

BRADY, Henry E. The Challenge of Big Data and Data Science. Annual Review of Political Science, v. 22, p. 297-323, 2019. https://doi.org/10.1146/annurev-polisci-090216-023229. Acesso em: 12 dez. 2024.

BUDHWAR, Pawan et al. Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, v. 33, n. 3, p. 606-659, 2023. Disponível em: https://doi.org/10.1111/1748-8583.12524 . Acesso em: 12 dez. 2024.

CARVALHO, André Carlos Ponce de Leon Ferreira de. Inteligência Artificial: riscos, benefícios e uso responsável. Estudos Avançados, v. 35, n. 101, p. 21-35, 2021. Disponível em: https://doi.org/10.1590/s0103-4014.2021.35101.003 . Acesso em: 15 jan. 2025.

CAVALCANTI, Wênio Marcelo; TAVARES, Elaine Jordan; PEREIRA JÚNIOR, José Lúcio. Aplicação da Inteligência Artificial no Ensino Superior: Áreas e Características. Revista ADM.MADE, v. 25, n. 2, p. 40-61, 2021. Disponível em: https://revistaadmmade.estacio.br/index.php/admmade/article/view/9201 . Acesso em: 22 jan. 2025.

DA SILVA, Lucas Ferreira. Dados Abertos Governamentais conectados em Big Data: framework conceitual. São Paulo: Editora Dialética, 2021.

DE FREITAS, Nikenge. Inteligência de negócios e análise de dados. São Paulo: Editora Senac, 2023.

DELLERMANN, Dominik; EBEL, Philipp; SÖLLNER, Matthias; LEIMEISTER, Jan Marco. Hybrid intelligence. Business & Information Systems Engineering, v. 61, n. 5, p. 637-643, 2019. Disponível em: https://doi.org/10.1007/s12599-019-00595-2 . Acesso em: 22 jan. 2025.

ELKJAER, Bente; BRANDI, Ulrik. Organizational Learning viewed from a social learning perspective. In: EASTERBY-SMITH, Mark; LYLES, Marjorie (Orgs.). Handbook of organizational learning and knowledge management. 2. ed. Chichester: John Wiley & Sons, 2011. p. 23-41.

FURR, Nathan; OZCAN, Pinar; EISENHARDT, Kathleen. O Que é a Transformação Digital? Tensões Fundamentais enfrentadas pelas Empresas estabelecidas no Cenário Mundial. Revista Inteligência Competitiva, v. 12, p. 4-10, 2022. Disponível em: https://doi.org/10.24883/eaglesustainable.v12i.443 . Acesso em: 12 dez. 2024.

GAWALI, Mahendra Bhatu; GAWALI, Swapnali Sunil. Optimized skill knowledge transfer model using hybrid Chicken Swarm plus Deer Hunting Optimization for human to robot interaction. Knowledge-Based Systems, v. 220, p. 106945, 2021. Disponível em: https://doi.org/10.1016/j.knosys.2021.106945 . Acesso em: 15 jan. 2025.

GUBAREVA, Regina; LOPES, Rui Pedro. Virtual Assistants for Learning: A Systematic Literature Review. CSEDU, v. 1, p. 97-103, 2020. Disponível em: https://doi.org/10.5220/0009417600970103 . Acesso em: 22 jan. 2025.

HADJIMICHAEL, Demetris; RIBEIRO, Rodrigo; TSOUKAS, Haridimos. How does embodiment enable the acquisition of tacit knowledge in organizations? From Polanyi to Merleau-Ponty. Organization Studies, v. 45, n. 4, p. 545-570, 2024. Disponível em: https://doi.org/10.1177/01708406241228374 . Acesso em: 12 dez. 2024.

HOLMES, Wayne; TUOMI, Ilkka. State of the art and practice in AI in education. European Journal of Education, v. 57, n. 4, p. 542-570, 2022. Disponível em: https://doi.org/10.1111/ejed.12533 . Acesso em: 15 jan. 2025.

IGUAL, Laura; SEGUÍ, Santi. Introduction to Data Science. In: Introduction to Data Science. Undergraduate Topics in Computer Science. Cham: Springer, 2024. Disponível em: https://doi.org/10.1007/978-3-031-48956-3_1 . Acesso em: 12 dez. 2024.

INEP. Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira. Ensino a distância cresce 47,4% em uma década. 2022. Disponível em: https://www.gov.br/inep/pt-br/assuntos/noticias/censo-da-educacao-superior/ensino-a-distancia-cresce-474-em-uma-decada . Acesso em: 12 dez. 2024.

JARRAHI, Mohammad Hossein et al. Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, v. 66, n. 1, p. 87-99, 2023. Disponível em: https://doi.org/10.1016/j.bushor.2022.03.002. Acesso em: 22 jan. 2025.

JÄRVELÄ, Sanna; ZHAO, Guoying; NGUYEN, Andy; CHEN, Hanxiang. Hybrid intelligence: Human–AI coevolution and learning. British Journal of Educational Technology, 2024. Disponível em: https://bera-journals.onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13560 . Acesso em: 15 jan. 2025.

LATOUR, Bruno. On Recalling ANT. The Sociological Review, v. 47, n. 1_suppl, p. 15-25, 1999. Disponível em: https://doi.org/10.1111/j.1467-954X.1999.tb03480.x . Acesso em: 15 jan. 2025.

LATOUR, Bruno. Is Re-modernization Occurring - And If So, How to Prove It? A Commentary on Ulrich Beck. Theory, Culture & Society, v. 20, n. 2, p. 35-48, 2003. Disponível em: https://doi.org/10.1177/0263276403020002002 . Acesso em: 22 jan. 2025.

LATOUR, Bruno; MILSTEIN, Denise; MARRERO-GUILLAMÓN, Isaac; RODRÍGUEZ-GIRALT, Israel. Down to earth social movements: an interview with Bruno Latour. Social Movement Studies, v. 17, p. 1-9, 2018. Disponível em: https://doi.org/10.1080/14742837.2018.1459298 . Acesso em: 15 jan. 2025.

LECUN, Yann; BENGIO, Yoshua; HINTON, Geoffrey. Deep learning. Nature, v. 521, n. 7553, p. 436-444, 2015. Disponível em: https://doi.org/10.1038/nature14539 . Acesso em: 12 dez. 2024.

LEE, Kai-Fu. Inteligência artificial. Rio de Janeiro: Globo, 2019.

LEE, Kai-Fu; QIUFAN, Chen. 2041: Como a inteligência artificial vai mudar sua vida nas próximas décadas. Rio de Janeiro: Alta Books, 2022.

LEODOLTER, Werner. Digital Transformation shaping the Subconscious Minds of Organizations. Cham: Springer, 2017.

LIM, Jongchan; HWANG, Junseok. Exploring trends and topics in hybrid intelligence using keyword co-occurrence networks and topic modelling. Futures, v. 167, 2025. Disponível em: https://doi.org/10.1016/j.futures.2025.103550 . Acesso em: 22 jan. 2025.

LIU, Yu; XU, Yi; ZHOU, Shuhua. Enhancing User Experience through Machine Learning-Based Personalized Recommendation Systems: Behavior Data-Driven UI Design. TechRxiv, 2024. Disponível em: https://doi.org/10.36227/techrxiv.173337559.97825928/v1 . Acesso em: 12 dez. 2024.

LUDERMIR, Teresa Bernarda. Inteligência Artificial e Aprendizado de Máquina: estado atual e tendências. Estudos Avançados, v. 35, n. 101, p. 85-94, 2021. Disponível em: https://doi.org/10.1590/s0103-4014.2021.35101.007 . Acesso em: 12 dez. 2024.

MALLIK, Sruti; GANGOPADHYAY, Ahana. Proactive and reactive engagement of artificial intelligence methods for education: A review. Frontiers in Artificial Intelligence, v. 6, p. 1151391, 2023. Disponível em: https://doi.org/10.3389/frai.2023.1151391 . Acesso em: 15 jan. 2025.

MELO, Marlene de Fátima Andrade de Queiroz. Discutindo a aprendizagem sob a perspectiva da teoria ator-rede. Educar Em Revista, n. 39, p. 177-190, 2011. Disponível em: https://www.scielo.br/j/er/a/MpwYCqWm3SMv5vJvJcgD9wx/ . Acesso em: 22 jan. 2025.

MITTELSTADT, Brent Daniel; ALLO, Patrick; TADDEO, Mariarosaria; WACHTER, Sandra; FLORIDI, Luciano. The ethics of algorithms: Mapping the debate. Big Data & Society, v. 3, n. 2, 2016. Disponível em: https://doi.org/10.1177/2053951716679679 . Acesso em: 12 dez. 2024.

MOSCOSO-ZEA, Oswaldo; CASTRO, Joel; PAREDES-GUALTOR, Jorge; LUJÁN-MORA, Sergio. A hybrid infrastructure of enterprise architecture and business intelligence & analytics for knowledge management in education. IEEE Access, v. 7, p. 38778-38788, 2019. Disponível em: https://doi.org/10.1109/ACCESS.2019.2906343 . Acesso em: 15 jan. 2025.

OLIVEIRA, Fábio et al. Inteligência artificial na educação: uma revisão sistemática e abrangente dos benefícios e desafios. Revista Caderno Pedagógico, v. 10, n. 3, p. 234-249, 2020. Disponível em: https://ojs.studiespublicacoes.com.br/ojs/index.php/cadped/article/view/13611 . Acesso em: 22 jan. 2025.

PEETERS, Marieke M. M.; VAN DIGGELEN, Jurriaan; VAN DEN BOSCH, Karel; BRONKHORST, Adelbert; NEERINCX, Mark A.; SCHRAAGEN, Jan Maarten; RAAIJMAKERS, Stephan. Hybrid collective intelligence in a human–AI society. AI & Society, v. 36, n. 1, p. 217-238, 2021. Disponível em: https://doi.org/10.1007/s00146-020-01005-y . Acesso em: 12 dez. 2024.

PRATER, Ryan; LAURENZI, Emanuele. A Hybrid Intelligent Approach for the Support of Higher Education Students in Literature Discovery. CEUR Workshop Proceedings, v. 3121, 2022. Disponível em: https://ceur-ws.org/Vol-3121/paper13.pdf . Acesso em: 22 jan. 2025.

RAUTENBERG, Sandro; DO CARMO, Paulo Roberto Vasconcelos. Big data e ciência de dados: complementariedade conceitual no processo de tomada de decisão. Brazilian Journal of Information Science: research trends, v. 13, n. 4, p. 56-67, 2019. Disponível em: https://doi.org/10.36311/1981-1640.2019.v13n4.06.p56 . Acesso em: 15 jan. 2025.

RUSSELL, Stuart; NORVIG, Peter. Inteligência Artificial. Rio de Janeiro: Elsevier, 2013.

SANTOS, Jucimara et al. Ética na aplicação de sistemas de inteligência artificial na educação. Revista Brasileira de Informática na Educação, v. 28, n. 1, p. 134-150, 2020. Disponível em: https://doi.org/10.5753/rbie.2020.28.0.134 . Acesso em: 22 jan. 2025.

SICHMAN, Jaime Simão. Inteligência Artificial e sociedade: avanços e riscos. Estudos Avançados, v. 35, n. 101, p. 37-50, 2021. Disponível em: https://doi.org/10.1590/s0103-4014.2021.35101.004 . Acesso em: 12 dez. 2024.

SOUZA MOURA, Francisco Luan de; DA SILVA RIBEIRO, Maria Edgleuma. Produção científica sobre o modelo de gestão das universidades públicas brasileiras. Revista Brasileira de Política e Administração da Educação, v. 40, n. 1, 2024. Disponível em: https://doi.org/10.21573/vol40n12024.131944 . Acesso em: 15 jan. 2025.

TEIXEIRA, João de Fernandes. Mentes e máquinas: Uma introdução à ciência cognitiva. Porto Alegre: Artes Médicas, 1998.

TEIXEIRA, João de Fernandes; GUIMARÃES, André Sathler. Inteligência Híbrida: parcerias cognitivas entre mentes e máquinas. Informática na Educação: teoria & prática, v. 9, n. 2, 2006. Disponível em: https://doi.org/10.22456/1982-1654.3171 . Acesso em: 12 dez. 2024.

TUCZYŃSKI, Krzysztof. The use of Artificial Intelligence in Distance Education. Journal of Modern Science, v. 6, n. 60, 2024. Disponível em: https://doi.org/10.13166/jms/197010 . Acesso em: 22 jan. 2025.

VICARI, Rosa Maria. Influências das Tecnologias da Inteligência Artificial no ensino. Estudos Avançados, v. 35, n. 101, p. 73-84, 2021. Disponível em: https://doi.org/10.1590/s0103-4014.2021.35101.006 . Acesso em: 15 jan. 2025.

VILLELA MAFRA DA SILVA, Alessandra; VALADÃO, Suzane. Educação a distância no Brasil: um panorama histórico sobre os últimos cinco anos da modalidade no país. Revista Brasileira de Política e Administração da Educação, v. 40, n. 1, 2024. Disponível em: https://doi.org/10.21573/vol40n12024.131088 . Acesso em: 12 dez. 2024.

WANG, Weitian; LI, Rui; CHEN, Yi; DIEKEL, Z. Max; JIA, Yunyi. Facilitating Human-Robot Collaborative Tasks by Teaching-Learning-Collaboration from Human Demonstrations. IEEE Transactions on Automation Science and Engineering, v. 16, n. 2, p. 640-653, 2019. Disponível em: https://doi.org/10.1109/TASE.2018.2840345 . Acesso em: 15 jan. 2025.

YIN, Robert K. Estudo de Caso: Planejamento e Métodos. 5. ed. Porto Alegre: Bookman, 2015.

Published

2026-07-21

How to Cite

Ferraz Calvi, J., Pelizza Vier Machado, H., Pascoal Cassandre, M., & da Penha Natal, I. (2026). Hybrid Intelligence in the support to the distance higher education: conditions, possibilities and restrictions in an University. REVISTA BRASILEIRA DE POLÍTICA E ADMINISTRAÇÃO DA EDUCAÇÃO, 42(1). https://doi.org/10.21573/vol42n12026.145719