Adjustment of Peruvian university students to artificial intelligence
- Dávila Cisneros, Juan Diego 1
- Flores Limo, Fernando Antonio 2
- Barrios Tinoco, Luis Magno 2
- Cavero Aybar, Hugo Neptali 3
- Calizaya Alarcon, Vaishnava Gorethy 4
- Medina Romero, Miguel Ángel 5
- Romero Flores, Robert Antonio 4
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1
Universidad Nacional Pedro Ruíz Gallo
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2
Universidad Nacional de Educación Enrique Guzmán y Valle
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- 3 Universidad Andina Néstor Cáceres Velásquez de Juliaca
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4
Universidad Nacional del Altiplano
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5
Universidad Michoacana de San Nicolás de Hidalgo
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ISSN: 2254-0709
Año de publicación: 2023
Número: 36
Páginas: 237-248
Tipo: Artículo
Otras publicaciones en: Artseduca
Resumen
The increasing presence of Artificial Intelligence (AI) in higher education presents both advantages and challenges for students. It is crucial to examine and evaluate the factors that can enhance the adoption of artificial intelligence (AI) among students. This study aimed to investigate factors influencing the adoption of AI. This study investigates the adaptation of Peruvian college students to artificial intelligence (AI), focusing on aspects such as fairness, privacy, and the utilisation of academic resources. Data was collected using a combination of quantitative and qualitative methods, with specific tools designed for each method. All 545 participants in the study were university students who were selected using convenience sampling. The university in question integrates AI into its teaching methods and research. We obtained 298 responses from the audience and conducted a statistical analysis using Smart PLS. Qualitative interviews were conducted with six participants. The study reveals students’ concerns regarding the incorporation of AI in education. The results of the study confirmed the significance of privacy, ethics, societal factors, and academic resources in enhancing the adoption of artificial intelligence. This study reveals various challenges that students face when adapting to AI technology. These challenges include a lack of technical knowledge, concerns regarding privacy and ethical considerations, and unequal access to AI resources.
Referencias bibliográficas
- 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
- Adero, V. O., & Otieno, H. A. (2023). The Impact of Free Primary Education in Kenya. Fronteras en ciencias de la educación, 2(2), 1-16. https:// doi.org/10.58283/fce.v2i2.143
- Ahmad, S. F., Han, H., Alam, M. M., Rehmat, M., Irshad, M., Arraño-Muñoz, M., & Ariza-Montes, A. (2023). Impact of artificial intelligence on human loss in decision making, laziness and safety in education. Humanities and Social Sciences Communications, 10(1), 1-14. https:// doi.org/10.1057/s41599-023-01787-8
- Alsheibani, S., Cheung, Y., & Messom, C. (2018). Artificial Intelligence Adoption: AI-readiness at Firm-Level. PACIS 2018 Proceedings, 37. https:// aisel.aisnet.org/pacis2018/37
- Arias Gonzáles, J. L., Covinos Gallardo, M. R., & Cáceres Chávez, M. D. R. (2022). Information and communication technologies versus upskilling and reskilling of public employees in times of covid-19. Revista Venezolana De Gerencia, 27(98), 565-579. https://doi. org/10.52080/rvgluz.27.98.12
- Autor, D., Mindell, D. A., Reynolds, E. B., & Solow, R. M. (2021). MIT Task Force on the Work of the Future. In The Work of the Future: Building Better Jobs in an Age of Intelligent Machines (pp. 165-167). MIT Press. https://ieeexplore. ieee.org/abstract/document/9740297
- Avolio Alecchi, B. E., Velezmoro Sánchez, C. E., Rojas Cangahuala, G. M., Moscoso Guerrero, J., Takahashi Sato, J., Paucar-Menacho, L. M., García, P. J., Carranza Oropeza, V., Torriani del Castillo, Y. F., & Carazo de Cabellos, M. I. (2021). Líneas orientadoras para la promoción de la mujer en la ciencia, tecnología e innovación tecnológica (CTI) 2021-2030. Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica (Concytec). http://hdl.handle.net/20.500.12390/2240
- Bécue, A., Praça, I., & Gama, J. (2021). Artificial intelligence, cyber-threats and Industry 4.0: Challenges and opportunities. Artificial Intelligence Review, 54(5), 3849-3886. https:// doi.org/10.1007/s10462-020-09942-2
- Boddington, P. (2017). How AI Challenges Professional Ethics. In P. Boddington (Ed.), Towards a Code of Ethics for Artificial Intelligence (pp. 59-65). Springer International Publishing. https://doi.org/10.1007/978-3- 319-60648-4_5
- Busuioc, M. (2021). Accountable artificial intelligence: Holding algorithms to account. Public Administration Review, 81(5), 825-836. https://doi.org/10.1111/puar.13293
- Cabrejos Chilge, G. E. (2022). Enseñanza virtual desde el enfoque de calidad educativa en instituciones educativas de nivel superior [Doctoral Dissertation, Universidad César Vallejo]. https://hdl.handle. net/20.500.12692/81928
- Castillo-Acobo, R. Y., Ramírez, A. A. V., Teves, R. M. V., Orellana, L. M. G., Quiñones-Negrete, M., Sernaqué, M. A. C., Valdivieso, J. V. P., Chávez, C. M. R., Gonzáles, J. L. A., & Carranza, C. P. M. (2022). Mediating role of inclusive leadership in innovative teaching behavior. Eurasian Journal of Educational Research, 100(100), 18-34. https:// doi.org/10.14689/ejer.2022.100.002
- Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). Lawrence Erlbaum Associates Publishers.
- Cockburn, I. M., Henderson, R., & Stern, S. (2019). The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis. In A. Agrawal, J. Gans, & A. Goldfarb (Eds.), The Economics of Artificial Intelligence: An Agenda (pp. 115-148). University of Chicago Press. https://doi.org/10.7208/9780226613475-006
- Córdova, P. R., & Vicari, R. M. (2022). Practical ethical issues for artificial intelligence in education. In International Conference on Technology and Innovation in Learning, Teaching and Education (pp. 437-445). Springer. https:// doi.org/10.1007/978-3-031-22918-3_34
- Cubric, M. (2020). Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study. Technology in Society, 62, 101257. https://doi.org/10.1016/j. techsoc.2020.101257
- Elliott, D., & Soifer, E. (2022). AI technologies, privacy, and security. Frontiers in Artificial Intelligence, 5, 826737. https://doi.org/10.3389/ frai.2022.826737
- Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24(5), 1709-1734. https://doi. org/10.1007/s10796-021-10186-w
- Filkins, B. L., Kim, J. Y., Roberts, B., Armstrong, W., Miller, M. A., Hultner, M. L., Castillo, A. P., Ducom, J.-C., Topol, E. J., & Steinhubl, S. R. (2016). Privacy and security in the era of digital health: what should translational researchers know and do about it? American Journal of Translational Research, 8(3), 1560-1580. https://e-century.us/files/ajtr/8/3/ ajtr0020863.pdf
- Fornell, C., & Larcker, D. F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.1177/002224378101800313
- Guerrero, S. I. C., Bernal, M. G., Rojas, F. Y. M., & Garcia, A. C. S. (2022). Inclusive classrooms: pedagogical practice of teachers that favour attention to diversity. Frontiers in Educational Sciences, 1(2), 15-29. https://doi.org/10.58283/ fs.v1i2.68
- Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121. https://doi. org/10.1108/EBR-10-2013-0128
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135. https://doi.org/10.1007/s11747- 014-0403-8
- Hoppler, S. S., Segerer, R., & Nikitin, J. (2022). The six components of social interactions: actor, partner, relation, activities, context, and evaluation. Frontiers in Psychology, 12, 743074. https://doi.org/10.3389/fpsyg.2021.743074
- Hsu, C.-L., & Lin, J. C.-C. (2016). An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives. Computers in Human Behavior, 62, 516-527. https://doi.org/10.1016/j.chb.2016.04.023
- Irfan, M., Aldulaylan, F., & Alqahtani, Y. (2023). Ethics and Privacy in Irish Higher Education: A Comprehensive Study of Artificial Intelligence (AI) Tools Implementation at University of Limerick. Global Social Sciences Review, 8(2), 201-210. https://doi.org/10.31703/gssr.2023(VIII-II).17
- Kessler, G. (2018). Technology and the future of language teaching. Foreign Language Annals, 51(1), 205-218. https://doi.org/10.1111/flan.12318
- Kinshuk, Chen, N.-S., Cheng, I.-L., & Chew, S. W. (2016). Evolution is not enough: Revolutionizing current learning environments to smart learning environments. International Journal of Artificial Intelligence in Education, 26, 561-581. https:// doi.org/10.1007/s40593-016-0108-x
- Kwon, O., Bae, S., & Shin, B. (2020). Understanding the adoption intention of AI through the ethics lens. In 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020 (pp. 4972-4981). IEEE Computer Society. https:// hdl.handle.net/10125/64353
- Lee, J., Kim, J., & Choi, J. Y. (2019). The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics and Informatics, 39, 37-48. https:// doi.org/10.1016/j.tele.2018.12.006
- Lemaître, D. (2019). Training engineers for innovation: Pedagogical initiatives for new challenges. European Journal of Education, 54(4), 566-576. https://doi.org/10.1111/ejed.12365
- Loader, R., & Hughes, J. (2017). Balancing cultural diversity and social cohesion in education: The potential of shared education in divided contexts. British Journal of Educational Studies, 65(1), 3-25. https://doi.org/10.1080/00071005.2016.1254156
- López de Mántaras, R. (2018). The Future of Artificial Intelligence: Toward Truly Intelligent Artificial Intelligences. In Towards a New Enlightenment? A Transcendent Decade. Madrid: BBVA. https:// www.bbvaopenmind.com/en/articles/the-futureof-ai-toward-truly-intelligent-artificial-intelligences
- Luckin, R., & Holmes, W. (2016). Intelligence unleashed: An argument for AI in education. Pearson. https://www.pearson.com/content/ dam/corporate/global/pearson-dot-com/files/ innovation/Intelligence-Unleashed-Publication.pdf
- Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60. https://doi. org/10.1016/j.futures.2017.03.006
- Mishra, P., & Mehta, R. (2017). What we educators get wrong about 21st-century learning: Results of a survey. Journal of Digital learning in Teacher education, 33(1), 6-19. https://doi.org/10.108 0/21532974.2016.1242392
- Munoko, I., Brown-Liburd, H. L., & Vasarhelyi, M. (2020). The ethical implications of using artificial intelligence in auditing. Journal of Business Ethics, 167, 209-234. https://doi.org/10.1007/ s10551-019-04407-1
- Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B.-P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221-4241. https://doi.org/10.1007/s10639-022-11316-w
- Olsson, T., Jarusriboonchai, P., Woźniak, P., Paasovaara, S., Väänänen, K., & Lucero, A. (2020). Technologies for enhancing collocated social interaction: review of design solutions and approaches. Computer Supported Cooperative Work (CSCW), 29, 29-83. https://doi.org/10.1007/s10606-019-09345-0
- Opicha, M. L. (2016). Influence of headteachers’ instructional supervision practices on pupils’ performance at Kenya certificate of primary education in Khwisero sub County, Kenya [Doctoral Dissertation, University of Nairobi]. http://hdl.handle. net/11295/100105
- Pannu, A. (2015). Artificial intelligence and its application in different areas. Artificial Intelligence, 4(10), 79-84. https://www.ijeit.com/ Vol%204/Issue%2010/IJEIT1412201504_15.pdf
- Purwanto, A. (2021). Partial least squares structural squation modeling (PLS-SEM) analysis for social and management research: a literature review. Journal of Industrial Engineering & Management Research, 2(4), 114-123. https://doi.org/10.7777/ jiemar.v2i4.168
- Ramos, W. R. M., Herrera, E. E., Manrique, G. M. L., Acevedo, J. E. R., Acosta, D. B., Palacios-Jimenez, A. S., Peña, P. F. P., Berrios, H. Q., Paricahua, E. P., & Vasquez-Pauca, M. J. (2022). Responsible leadership: a comparative study between Peruvian national and private universities. Eurasian Journal of Educational Research, 99(99), 143-154. https:// doi.org/10.14689/ejer.2022.99.009
- Saguy, I. S. (2016). Challenges and opportunities in food engineering: Modeling, virtualization, open innovation and social responsibility. Journal of Food Engineering, 176, 2-8. https:// doi.org/10.1016/j.jfoodeng.2015.07.012
- Sheikh, H., Prins, C., & Schrijvers, E. (2023). Artificial Intelligence: Definition and Background. In Mission AI: The New System Technology (pp. 15-41). Springer. https://doi.org/10.1007/978-3-031- 21448-6_2
- Simamora, R. M. (2020). The Challenges of online learning during the COVID-19 pandemic: An essay analysis of performing arts education students. Studies in Learning and Teaching, 1(2), 86-103. https://doi.org/10.46627/silet.v1i2.38
- Singh, D., & Ramutsheli, M. P. (2016). Student data protection in a South African ODL university context: Risks, challenges and lessons from comparative jurisdictions. Distance Education, 37(2), 164-179. https://doi.org/10.1080/01587919.2016.1184397
- Song, M., Xing, X., Duan, Y., Cohen, J., & Mou, J. (2022). Will artificial intelligence replace human customer service? The impact of communication quality and privacy risks on adoption intention. Journal of Retailing and Consumer Services, 66, 102900. https://doi.org/10.1016/j.jretconser.2021.102900
- Tegmark, M. (2018). Life 3.0: Being Human in the Age of Artificial Intelligence. Vintage. https:// mitpressbookstore.mit.edu/book/9781101970317
- Thayyib, P., Mamilla, R., Khan, M., Fatima, H., Asim, M., Anwar, I., Shamsudheen, M., & Khan, M. A. (2023). State-of-the-Art of Artificial Intelligence and Big Data Analytics Reviews in Five Different Domains: A Bibliometric Summary. Sustainability, 15(5), 4026. https://doi.org/10.3390/su15054026
- Venkateswarlu, Y., Baskar, K., Wongchai, A., Gauri Shankar, V., Paolo Martel Carranza, C., Gonzáles, J. L. A., & Murali Dharan, A. (2022). An efficient outlier detection with deep learningbased financial crisis prediction model in big data environment. Computational Intelligence and Neuroscience, 2022, 4948947. https://doi. org/10.1155/2022/4948947
- Wamba-Taguimdje, S.-L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AIbased transformation projects. Business Process Management Journal, 26(7), 1893-1924. https:// doi.org/10.1108/BPMJ-10-2019-0411
- Wang, M.-Y., Luan, P., Zhang, J., Xiang, Y.-T., Niu, H., & Yuan, Z. (2018). Concurrent mapping of brain activation from multiple subjects during social interaction by hyperscanning: a minireview. Quantitative Imaging in Medicine and Surgery, 8(8), 819-837. https://doi. org/10.21037/qims.2018.09.07
- Wang, S., Meng, J., Xie, Y., Jiang, L., Ding, H., & Shao, X. (2021). Reference training system for intelligent manufacturing talent education: platform construction and curriculum development. Journal of Intelligent Manufacturing, 34, 1125-1164. https:// doi.org/10.1007/s10845-021-01838-4
- Warkentin, M., Goel, S., & Menard, P. (2017). Shared benefits and information privacy: what determines smart meter technology adoption? Journal of the Association for Information Systems, 18(11), 3. https://doi.org/10.17705/1jais.00474
- Xu, J., Yang, P., Xue, S., Sharma, B., SanchezMartin, M., Wang, F., Beaty, K. A., Dehan, E., & Parikh, B. (2019). Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives. Human Genetics, 138(2), 109-124. https://doi. org/10.1007/s00439-019-01970-5
- Yusuf, T. I., Adebayo, O. A., Bello, L. A., & Kayode, J. O. (2022). Adoption of artificial intelligence for effective library service delivery in academic libraries in Nigeria. Library Philosophy and Practice (e-journal), 6804. https://digitalcommons.unl.edu/ libphilprac/6804
- Southworth, J., Migliaccio, K., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/j.caeai.2023.100127