Universitarios frente a las Fake News generadas por Inteligencia Artificialestrategias asociadas al pensamiento crítico que adoptan

  1. Mª Esther del Moral Pérez 1
  2. Nerea López-Bouzas 1
  3. Jonathan Castañeda Fernández 1
  4. Mª del Carmen Bellver Moreno 2
  1. 1 Universidad de Oviedo
    info
    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

    Geographic location of the organization Universidad de Oviedo
  2. 2 Universitat de València
    info
    Universitat de València

    Valencia, España

    ROR https://ror.org/043nxc105

    Geographic location of the organization Universitat de València
Journal:
Educación XX1: Revista de la Facultad de Educación

ISSN: 1139-613X,  2174-5374

Year of publication: 2025

Volume: 28

Issue: 2

Pages: 69-121

Type: Article

DOI: 10.5944/EDUCXX1.39811 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Educación XX1: Revista de la Facultad de Educación

Abstract

The arrival of Artificial Intelligence (AI) in the digital arena has increased the amount of fake news (FN) circulating on social networks (SNs), where young people are at particular risk of being deceived and manipulated. The study objectives were: 1) to analyse the criticalthinkingstrategies that university students (N=543) activate when dealing with FN; 2) to determine how much education and training they have been given for detecting FN; and 3) to describe the educational content that they believe to be most important for identifying FN. The methodology was empirical and non-experimental. The study was descriptive, exploratory, and comparative. A validated questionnaire (α=0.895) with 56 items was used to ascertain how much education they had received for detecting FN and to identify the criticalthinking strategies (cognitive, personal-attitudinal, logical-argumentative, communicativeexpressive, and ethical) they activated when dealing with FN. The results indicated that 76.6% reported having little or no education in this regard. The majority understood what FN with the aim of manipulation was, although around 40% reported not being aware of having received any. They did not habitually test the information they received against reliable sources nor check where it came from or who wrote it. Nonetheless, they did detect clickbait. The strategies they used did not always ensure that they determined the truth of the news stories they received, making them more vulnerable. They called for specific education and described the training content they would prioritize to understand how FN is created and to critically analyse its form and content, avoiding being manipulated. Finally, it is important to consider the role of generative AI in altering “evidence”, limiting the audience’s ability to determine the truth of any information they receive, potentially leading to widespread scepticism

Bibliographic References

  • Aboualola, M., Abualsaud, K., Khattab, T., Zorba, N., & Hassanein, H.S. (2023). Edge technologies for disaster management: A survey of social media and artificial intelligence integration. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3293035
  • Acosta, Y.J. (2021). Aportes de la psicología social en el estudio de las fake news. Comunicación: Estudios Venezolanos de Comunicación, 196, 87-93. http://bitly.ws/z6Yj
  • Alcalá, M., Alcolea, G., & Navarro, N. (2021). Factores de credibilidad e interés de las noticias en el paisaje (des)informativo. Estudios sobre el Mensaje Periodístico, 27(3), 739-751. https://doi.org/10.5209/esmp.71280
  • Aleinikov, A.V., Miletskiy, V.P., Pimenov, N.P., & Strebkov, A.I. (2019). The “Fake-News” Phenomenon and Transformation of Information Strategies in the Digital Society. Scientific and Technical Information Processing, 46, 117-122. https://doi.org/10.3103/S0147688219020126
  • Ballesteros-Aguayo, L. & Ruiz del Olmo, F.J. (2024). Vídeos falsos y desinformación ante la IA: el deepfake como vehículo de la posverdad. Revista de Ciencias de la Comunicación e Información, 29, 1-14. https://doi.org/10.35742/rcci.2024.29.e294
  • Batailler, C., Brannon, S.M., Teas, P.E., & Gawronski, B. (2022). A signal detection approach to understanding the identification of fake news. Perspectives on Psychological Science, 17(1), 78-98. https://doi.org/10.1177/1745691620986135
  • Britt, M.A., Rouet, J.F., Blaum, D., & Millis, K. (2019). A reasoned approach to dealing with fake news. Policy Insights from the Behavioral and Brain Sciences, 6(1), 94-101. https://doi.org/10.1177/2372732218814855
  • Bronstein, M.V., Pennycook, G., Buonomano, L., & Cannon, T.D. (2021). Belief in fake news, responsiveness to cognitive conflict, and analytic reasoning engagement. Thinking & Reasoning, 27(4), 510-535. https://doi.org/10.1080/13546783.2020.1847190
  • Carifio, J., & Perla, R. (2008). Resolving the 50-year debate around using and misusing Likert scales. Medical Education, 42, 1150-1152. https://doi.org/10.1111/j.1365-2923.2008.03172.x
  • Castells, N., García, M., Miralda, A., Luna, J., & Pérez, E. (2022). El razonamiento de los adolescentes para gestionar las noticias falsas. Educación XX1, 25(2), 291-313. https://doi.org/10.5944/educxx1.31693
  • Catalina, B., Sousa, J.P., & Sousa, L.C. (2019). Consumo de noticias y percepción de fake news entre estudiantes de Comunicación de Brasil, España y Portugal. Revista de Comunicación, 18(2), 93-115. http://dx.doi.org/10.26441/rc18.2-2019-a5
  • Chambers, S. (2021). Truth, deliberative democracy, and the virtues of accuracy: is fake news destroying the public sphere? Political Studies, 69(1), 147-163. https://doi.org/10.1177/00323217198908
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Earlbaum Associates.
  • Cohen, L., Manion, L., & Morrison, K. (2011). Research methods in education. Routledge.
  • Del Moral, M.E., Bellver, M.C., Guzman, A., & López-Bouzas, N. (2021). Concienciación juvenil frente al COVID-19 en España y Latinoamérica: análisis de spots en YouTube. Revista Latina de Comunicación Social, 79, 23-49. https://doi.org/10.4185/RLCS-2021-1510
  • Dumitru, E.A., Ivan, L., & Loos, E. (2022). A generational approach to fight fake news: In search of effective media literacy training and interventions. In International Conference on Human-Computer Interaction (pp. 291-310). Springer International Publishing. https://doi.org/10.1007/978-3-031-05581-2_22
  • Ennis, R.H. (1985). A logical basis for measuring critical thinking skills. Educational Leadership, 43(2), 44-48.
  • Espinar, E., González, C., & Martínez, R. (2020). Análisis del consumo de noticias entre estudiantes de la Universidad de Alicante. Convergencia, 27, 1-25. https://doi.org/10.29101/crcs.v27i0.13286
  • García-Peñalvo, F.J., Llorens-Largo, F., & Vidal, J. (2024). La nueva realidad de la educación ante los avances de la inteligencia artificial generativa. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 9-39. https://doi.org/10.5944/ried.27.1.37716
  • Gómez de Ágreda, Á., Feijoó, C.A., & Salazar, I.A. (2021). Una nueva taxonomía del uso de la imagen en la conformación interesada del relato digital. Deep fakes e inteligencia artificial. El Profesional de la Información, 30(2), 1-24. https://doi.org/10.3145/epi.2021.mar.16
  • Gómez, B., Córdoba, A., & Méndez, A. (2020). Jóvenes y fake news. Un análisis sociodemográfico aplicado al caso andaluz. IC: Revista Científica de Información y Comunicación, 17, 481-504. http://doi.org/10.12795/IC.2020.i01.21
  • Hernández, L. (2020). Desinformación: no es sinónimo de fake news. Comunicación: Estudios Venezolanos de Comunicación, 189, 29-34.
  • Karen, A., Christopher, M., Qomariyah, N.N., Manuaba, I.B.K., & Anom, A.K. (2023). Clarifact-AI: Detecting Fake News in Indonesian Language with Natural Language Processing Using BiLSTM and IndoBERT Models. In 2023 10th International Conference on ICT for Smart Society (ICISS) (pp. 1-6). IEEE. https://doi.org/10.1109/ICISS59129.2023.10291714
  • Kondamudi, M. R., Sahoo, S. R., Chouhan, L., & Yadav, N. (2023). A comprehensive survey of fake news in social networks: Attributes, features, and detection approaches. Journal of King Saud University-Computer and Information Sciences, 35(6), 101571. https://doi.org/10.1016/j.jksuci.2023.101571
  • López-Flamarique, M., & Planillo, S. (2021). El alumnado de educación secundaria frente a las noticias falsas: resultados de una intervención didáctica. RELATEC. Revista Latinoamericana de Tecnología Educativa, 20(1), 39-56. https://doi.org/10.17398/1695-288X.20.1.39
  • López, P. C., Mila, A., & Ribeiro, V. (2023). La desinformación en las democracias de América Latina y de la península ibérica: De las redes sociales a la inteligencia artificial (2015-2022). Uru: Revista de Comunicación y Cultura, 8, 69-89. https://doi.org/10.32719/26312514.2023.8.5
  • Lozano-Blasco, R., Mira-Aladrén, M., & Gil-Lamata, M. (2023). Redes sociales y su influencia en los jóvenes y niños: Análisis en Instagram, Twitter y YouTube. Comunicar, 31, 1-13. http://dx.doi.org/10.3916/C74-2023-10
  • Martín, A. & Buitrago, A. (2023). Valoración profesional del sector periodístico sobre el efecto de la desinformación y las fake news en el ecosistema mediático. ICONO 14. Revista científica de Comunicación y Tecnologías Emergentes, 21(1), 1-19. https://doi.org/10.7195/ri14.v21i1.1933
  • Meso, K., Larrondo, A., & Peña, S. (2023). Algoritmos, inteligencia artificial y periodismo automatizado en el sistema híbrido de medios. Textual & Visual Media, 17(1), 1-6. https://doi.org/10.56418/txt.17.1.2023.0
  • Nazari, Z., Oruji, M., & Jamali, H.R. (2022). News consumption and behavior of young adults and the issue of fake news. Journal of Information Science Theory and Practice, 10(2), 1-16. https://doi.org/10.1633/JISTaP.2022.10.2.1
  • Otero, I. (2022). Los cimientos de la Inteligencia Artificial en el sistema productivo de contenidos periodísticos automatizados. Redmarka. Revista de Marketing Aplicado, 26(1), 15-35. https://doi.org/10.17979/redma.2022.26.1.9056
  • Paul, R., & Elder, L. (2007). A Guide for Educators to Critical Thinking Competency Standards: Standards, Principles, Performance Indicators, and Outcomes with a Critical Thinking Master Rubric. Rowman & Littlefield Publishers/The Foundation for Critical Thinking. https://bit.ly/33C9qaB
  • Pérez-Escoda A., Ortega E., & Pedrero L.M. (2022) Alfabetización digital para combatir las fake news: Estrategias y carencias entre los/as universitarios/as. Revista Prisma Social, 38, 221-243. https://revistaprismasocial.es/article/view/4696
  • Preston, S., Anderson, A., Robertson, D.J., Shephard, M. P., & Huhe, N. (2021). Detecting fake news on Facebook: The role of emotional intelligence. Plos One, 16(3), e0258719. https://doi.org/10.1371/journal.pone.0246757
  • Román, A., Sánchez, N., & Zambrano, R. (2020). Las fake news durante el Estado de Alarma por COVID-19. Análisis desde el punto de vista político en la prensa española. Revista Latina de Comunicación Social, 78, 359-391. https://doi.org/10.4185/RLCS-2020-1481
  • Sádaba-Chalezquer, M., & Salaverría-Aliaga, R. (2023). Combatir la desinformación con alfabetización mediática: análisis de las tendencias en la Unión Europea. Revista Latina de Comunicación Social, 81, 17 - 33. https://www.doi.org/10.4185/RLCS-2023-1552
  • Samuel-Azran, T., & Hayat, T. (2019). La credibilidad de las noticias digitales: El vínculo es más impactante que la fuente. Comunicar, 60(27), 71-80. https://doi.org/10.3916/C60-2019-07
  • Sánchez-Mendiola, M., & Carbajal, E. (2023). La inteligencia artificial generativa y la educación universitaria. Perfiles Educativos, 45(Especial), 70-86. https://doi.org/10.22201/iisue.24486167e.2023.Especial.61692
  • Singh, M.K., Ahmed, J., Alam, M.A., Raghuvanshi, K.K., & Kumar, S. (2023). A comprehensive review on automatic detection of fake news on social media. Multimedia Tools and Applications, 1-34. https://doi.org/10.1007/s11042-023-17377-4
  • Sülflow, M., Schäfer, S., & Winter, S. (2019). Selective attention in the news feed: An eye-tracking study on the perception and selection of political news posts on Facebook. New Media & Society, 21(1), 168-190. https://doi.org/10.1177/1461444818791520
  • Swart, J. (2021). Experiencing algorithms: How young people understand, feel about, and engage with algorithmic news selection on social media. Social Media + Society, 7(2), 20563051211008828. https://doi.org/10.1177/20563051211008828
  • Tandoc, E.C., Chong, J., Sian, C., Sei, J., & Kai, S. (2023). No “Me” in Misinformation: The Role of Social Groups in the Spread of, and Fight Against, Fake News. In Mobile Communication and Online Falsehoods in Asia: Trends, Impact and Practice (pp. 131-147). Springer. https://doi.org/10.1007/978-94-024-2225-2_8
  • Valencia, A., Arango, D.M., Cardona, S., Paredes, S.S., & Gallegos, A. (2023). Understanding the Spread of Fake News: An Approach from the Perspective of Young People. Informatics, 10(2), 38. https://doi.org/10.3390/informatics10020038
  • Villena, D. (2019). Era posverdad: Comunicación, política y filosofía. Psicopraxia, 1(1), 17-26. https://philpapers.org/rec/SALEPC-3
  • Waisbord, S. (2018). Truth is what happens to news: On journalism, fake news, and post-truth. Journalism Studies, 19(13), 1866-1878. https://doi.org/10.1080/1461670X.2018.1492881
  • Wolfowicz, M., Weisburd, D., & Hasisi, B. (2023). Examining the interactive effects of the filter bubble and the echo chamber on radicalization. Journal of Experimental Criminology, 19(1), 119-141. https://doi.org/10.1007/s11292-021-09471-0
Data source: Dialnet