Artificial Intelligence at the university of Namibe: uncovering faculty perceptions and readiness
DOI:
https://doi.org/10.51247/pdlc.v5i2.482Keywords:
artificial intelligence, higher education, faculty perceptions, training, institutional support, Angola.Abstract
This study investigated the perceptions and readiness of faculty members at the University of Namibe (UNINBE) regarding the adoption of Artificial Intelligence (AI) in academic activities. The objectives were to assess the faculty's familiarity with AI, explore their perceptions of its importance in the university context, identify benefits and concerns, and analyze the need for training programs and existing institutional support. Using a quantitative approach, surveys were conducted with 25 doctoral faculty members at UNINBE. The results show that although 56% of the faculty are familiar with AI, a significant portion (36%) exhibits limited familiarity or neutrality. Despite this, 60% of the faculty already use AI in teaching and research activities. Most (92%) consider AI important for higher education, with particular emphasis on its potential impact on scientific research and teaching. The main concerns are related to ethical issues (48%) and security (28%). Finally, almost all faculty members (96%) recognize the need for AI training programs, while institutional support was deemed insufficient by the majority, reflecting the need for further investment in infrastructure and support policies. This study suggests the implementation of strategies to improve AI training and support in higher education, particularly in developing country contexts.
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References
Babbie, E. (2016). The practice of social research (14th ed.). Cengage Learning.
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-023-00392-8.
Decreto Presidencial nº 285/20, de 29 de outubro. (2020). Reorganização da rede de Instituições Públicas de Ensino Superior. Disponível em /mnt/data/DP-285-_-20-de-29-de-Outubro-reorganizacao-da-rede-de-IPES.pdf.
Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method (4th ed.). John Wiley & Sons.
Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications.
Fink, A. (2013). How to conduct surveys: A step-by-step guide (5th ed.). SAGE Publications.
Huang, R., Spector, J. M., & Yang, J. (2023). Educational technology integration: An analysis of teacher adoption and use of new innovations. Journal of Educational Technology & Society, 26(1), 89-103.
Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22(140), 1–55.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. London: Pearson Education.
Resnik, D. B. (2015). Ethics of science: An introduction (2nd ed.). Routledge.
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.
Selwyn, N. (2019). Digital technology and the contemporary university: Degrees of digitization. New York: Routledge.
Slimi, Z. (2023). The impact of artificial intelligence on higher education: An empirical study. European Journal of Education Studies, 10(1), 17-31. https://doi.org/10.19044/ejes.v10no1a17.
Sun, L., Zhang, Z., & Zuo, M. (2022). Teachers’ perceptions and implementations of artificial intelligence in education: A survey study. International Journal of Artificial Intelligence in Education, 32(2), 251–270.
UNINBE. (2023). Universidade do Namibe: Missão e valores. https://uninbe.ao
Universidade do Namibe. (n.d.). Estatuto Orgânico da Universidade do Namibe (UNINBE). Disponível em /mnt/data/Estatuto%20Organico%20da%20UNINBE.pdf.
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
Zhu, X., & Liu, Y. (2021). Professional development in the era of artificial intelligence: Challenges and opportunities for teachers. Computers & Education, 174, 104288.
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Copyright (c) 2024 Agostinho Cachapa; Martins Abel, Teresa Patatas, Bernardo Camunda
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