Utilização da inteligência artificial entre estudantes universitários no ensino superior

Uso de la inteligencia artificial entre estudiantes universitarios en la educación superior

Autores

Letty Carolina García-Zambrano Universidad Técnica de Manabí. Ecuador https://orcid.org/0009-0002-1051-2969
Rafael Tejeda-Díaz Universidad Técnica de Manabí. Ecuador https://orcid.org/0000-0001-8098-9661

DOI:

https://doi.org/10.33936/cognosis.v10iEE(1).7122

Resumo

A inteligência artificial (IA) consolidou-se como uma ferramenta fundamental no campo educacional, transformando a forma como os estudantes acessam e processam informações. Essa mudança despertou interesse em compreender como a IA é percebida e utilizada em contextos acadêmicos. O presente estudo analisa o uso e a percepção das ferramentas de IA entre estudantes da Faculdade de Ciências Humanísticas e Sociais da Universidade Técnica de Manabí. Adotou-se uma metodologia quantitativa com delineamento descritivo-correlacional, permitindo examinar a relação entre a percepção e o uso da IA no ensino superior. Para a coleta de dados, aplicou-se um questionário estruturado a uma amostra de 211 estudantes, cujas informações foram analisadas por meio de métodos estatísticos, seguindo rigorosamente as normas éticas. Os resultados, validados por análise fatorial (KMO = 0,862), indicam que os estudantes consideram a IA uma ferramenta útil para a aprendizagem. No entanto, observaram-se diferenças significativas relacionadas ao nível acadêmico e a preocupações éticas, especialmente entre aqueles que cursam níveis mais avançados. As análises de ANOVA e do teste HSD de Tukey revelam uma percepção mais favorável nos estudantes iniciantes, a qual tende a diminuir nos níveis superiores devido a uma exposição mais crítica. Conclui-se que há uma aceitação geral da IA como competência essencial, embora as diferenças de percepção evidenciem a necessidade de aprofundar pesquisas sobre seu impacto em diversos contextos acadêmicos, bem como explorar fatores como o apoio institucional e o nível de conhecimento técnico dos estudantes.

PALAVRAS-CHAVE: Inteligência artificial; ensino superior; percepção; análise fatorial; ética.

Downloads

Não há dados estatísticos.

Biografia do Autor

Letty Carolina García-Zambrano, Universidad Técnica de Manabí. Ecuador

Licenciada en Ciencias de la Educación, Mención Psicología Educativa y Orientación Vocacional.

Rafael Tejeda-Díaz, Universidad Técnica de Manabí. Ecuador

Doctor en Ciencias Pedagógicas. Posdoctorado en la Universidad Federal de Minas Gerais, Brasil en Formación de Competencias en la Educación Superior. Licenciado en Educación. Master en Pedagogía Profesional. Profesor titular No 1. Tiempo completo en la Universidad Técnica de Manabí, Ecuador. Director del Grupo de investigación PROINNOEDUCA y del Centro de Estudios sobre el desarrollo de la Educación Superior (CEDES).

Referências

Abulibdeh, A., Zaidan, E., & Abulibdeh, R. (2024). Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production, 437, 140527. https://doi.org/10.1016/j.jclepro.2023.140527

Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligence, 4, 100131. https://doi.org/10.1016/j.caeai.2023.100131

Alamri, H. A., Watson, S., & Watson, W. (2021). Learning Technology Models that Support Personalization within Blended Learning Environments in Higher Education. TechTrends, 65(1), 62–78. https://doi.org/10.1007/s11528-020-00530-3

Ala-Mutka, K. M. (2005). A Survey of Automated Assessment Approaches for Programming Assignments. Computer Science Education, 15(2), 83–102. https://doi.org/10.1080/08993400500150747

Ambrose, M. L., Arnaud, A., & Schminke, M. (2007). Individual Moral Development and Ethical Climate: The Influence of Person–Organization Fit on Job Attitudes. Journal of Business Ethics, 77(3), 323–333. https://doi.org/10.1007/s10551-007-9352-1

An, X., Chai, C. S., Li, Y., Zhou, Y., & Yang, B. (2023). Modeling students’ perceptions of artificial intelligence assisted language learning. Computer Assisted Language Learning, 1–22. https://doi.org/10.1080/09588221.2023.2246519

Baca, G., & Zhushi, G. (2024). Assessing attitudes and impact of AI integration in higher education. Higher Education, Skills and Work-Based Learning. https://doi.org/10.1108/HESWBL-02-2024-0065

Bao, L., Krause, N. M., Calice, M. N., Scheufele, D. A., Wirz, C. D., Brossard, D., Newman, T. P., & Xenos, M. A. (2022). Whose AI? How different publics think about AI and its social impacts. Computers in Human Behavior, 130, 107182. https://doi.org/10.1016/j.chb.2022.107182

Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/j.caeai.2022.100068

Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 38(4), 101520. https://doi.org/10.1016/j.giq.2020.101520

Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023). Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success. Information Systems Frontiers, 25(1), 161–182. https://doi.org/10.1007/s10796-022-10291-4

Chou, C.-M., Shen, T.-C., Shen, T.-C., & Shen, C.-H. (2022). Influencing factors on students’ learning effectiveness of AI-based technology application: Mediation variable of the human-computer interaction experience. Education and Information Technologies, 27(6), 8723–8750. https://doi.org/10.1007/s10639-021-10866-9

Crittenden, W. F., Biel, I. K., & Lovely, W. A. (2019). Embracing Digitalization: Student Learning and New Technologies. Journal of Marketing Education, 41(1), 5–14. https://doi.org/10.1177/0273475318820895

Dai, Y., Chai, C.-S., Lin, P.-Y., Jong, M. S.-Y., Guo, Y., & Qin, J. (2020). Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age. Sustainability, 12(16), 6597. https://doi.org/10.3390/su12166597

Davis, F. D., & Granić, A. (2024). The Technology Acceptance Model. Springer International Publishing. https://doi.org/10.1007/978-3-030-45274-2

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y

Fetzer, J. H. (1990). What is Artificial Intelligence? In Artificial Intelligence: Its Scope and Limits (pp. 3–27). https://doi.org/10.1007/978-94-009-1900-6_1

Guàrdia, L., Clougher, D., Anderson, T., & Maina, M. (2021). IDEAS for Transforming Higher Education: An Overview of Ongoing Trends and Challenges. The International Review of Research in Open and Distributed Learning, 22(2), 166–184. https://doi.org/10.19173/irrodl.v22i2.5206

Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1

Imran, A. A., & Lashari, A. A. (2023). Exploring the World of Artificial Intelligence: The Perception of the University Students about ChatGPT for Academic Purpose. Global Social Sciences Review, VIII(I), 375–384. https://doi.org/10.31703/gssr.2023(VIII-I).34

Kashive, N., Powale, L., & Kashive, K. (2020). Understanding user perception toward artificial intelligence (AI) enabled e-learning. The International Journal of Information and Learning Technology, 38(1), 1–19. https://doi.org/10.1108/IJILT-05-2020-0090

Kessler, G., & Bikowski, D. (2010). Developing collaborative autonomous learning abilities in computer mediated language learning: attention to meaning among students in wiki space. Computer Assisted Language Learning, 23(1), 41–58. https://doi.org/10.1080/09588220903467335

Kim, N. J., & Kim, M. K. (2022). Teacher’s Perceptions of Using an Artificial Intelligence-Based Educational Tool for Scientific Writing. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.755914

Kim, Y., Soyata, T., & Behnagh, R. F. (2018). Towards Emotionally Aware AI Smart Classroom: Current Issues and Directions for Engineering and Education. IEEE Access, 6, 5308–5331. https://doi.org/10.1109/ACCESS.2018.2791861

Kong, S.-C., Cheung, W. M.-Y., & Zhang, G. (2022). Evaluating artificial intelligence literacy courses for fostering conceptual learning, literacy and empowerment in university students: Refocusing to conceptual building. Computers in Human Behavior Reports, 7, 100223. https://doi.org/10.1016/j.chbr.2022.100223

Korteling, J. E. (Hans)., van de Boer-Visschedijk, G. C., Blankendaal, R. A. M., Boonekamp, R. C., & Eikelboom, A. R. (2021). Human- versus Artificial Intelligence. Frontiers in Artificial Intelligence, 4. https://doi.org/10.3389/frai.2021.622364

Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J. H., Ogata, H., Baltes, J., Guerra, R., Li, P., & Tsai, C.-C. (2020). Challenges and Future Directions of Big Data and Artificial Intelligence in Education. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.580820

Maghsudi, S., Lan, A., Xu, J., & van der Schaar, M. (2021). Personalized Education in the Artificial Intelligence Era: What to Expect Next. IEEE Signal Processing Magazine, 38(3), 37–50. https://doi.org/10.1109/MSP.2021.3055032

Mantello, P., Ho, M.-T., Nguyen, M.-H., & Vuong, Q.-H. (2023). Bosses without a heart: socio-demographic and cross-cultural determinants of attitude toward Emotional AI in the workplace. AI & SOCIETY, 38(1), 97–119. https://doi.org/10.1007/s00146-021-01290-1

Marangunić, N., & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81–95. https://doi.org/10.1007/s10209-014-0348-1

Martín-Gutiérrez, J., Fabiani, P., Benesova, W., Meneses, M. D., & Mora, C. E. (2015). Augmented reality to promote collaborative and autonomous learning in higher education. Computers in Human Behavior, 51, 752–761. https://doi.org/10.1016/j.chb.2014.11.093

Okunlaya, R. O., Syed Abdullah, N., & Alias, R. A. (2022). Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education. Library Hi Tech, 40(6), 1869–1892. https://doi.org/10.1108/LHT-07-2021-0242

Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(6), 7893–7925. https://doi.org/10.1007/s10639-022-10925-9

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0

Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, 2021(1). https://doi.org/10.1155/2021/8812542