Use of ChatGPT at university as a tool for complex thinkingStudents' perceived usefulness

  1. José-María Romero-Rodríguez 1
  2. María-Soledad Ramírez-Montoya 2
  3. Mariana Buenestado-Fernández 3
  4. Fernando Lara-Lara 1
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

  2. 2 Instituto Tecnológico y de Estudios Superiores de Monterrey
    info

    Instituto Tecnológico y de Estudios Superiores de Monterrey

    Monterrey, México

    ROR https://ror.org/03ayjn504

  3. 3 Universidad de Cantabria
    info

    Universidad de Cantabria

    Santander, España

    ROR https://ror.org/046ffzj20

Revista:
NAER: Journal of New Approaches in Educational Research

ISSN: 2254-7339

Año de publicación: 2023

Volumen: 12

Número: 2

Páginas: 323-339

Tipo: Artículo

DOI: 10.7821/NAER.2023.7.1458 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: NAER: Journal of New Approaches in Educational Research

Resumen

La inteligencia artificial (IA) y los chatbots basados en IA, como ChatGPT, están transformando el enfoque de la educación. En particular, el potencial de ChatGPT para procesar grandes cantidades de datos y aprender de las interacciones de los usuarios lo convierte en un recurso beneficioso para los estudiantes, aunque con ciertas reticencias por parte de algunos profesores. El objetivo de este estudio era explorar la aceptación de ChatGPT por parte de los estudiantes universitarios. Los investigadores administraron una encuesta en línea a 400 estudiantes universitarios españoles de entre 18 y 64 años (M = 21,80; DE = 6,40). Los resultados del enfoque metodológico basado en el modelo UTAUT2 para la adopción de tecnología mostraron que: 1) el género no fue una variable determinante en ningún constructo mientras que la experiencia de uso fue un factor condicionante de una mayor puntuación en todos los constructos; 2) la experiencia, la expectativa de rendimiento, la motivación hedónica, el valor del precio y el hábito fueron influyentes en la intención conductual de uso de ChatGPT; 3) las condiciones facilitadoras, el hábito y la intención conductual fueron factores condicionantes en el comportamiento del usuario. Por último, se discuten los resultados y las implicaciones prácticas del trabajo y se recomiendan algunos buenos usos de ChatGPT.

Información de financiación

Financiadores

Referencias bibliográficas

  • Anderson, N., Belavy, D. L., Perle, S. M., Hendricks, S., Hespanhol, L., Verhagen, E. & Memon, A. R. (2023). AI did not write this manuscript, or did it? Can we trick the AI text detector into generated texts? The potential future of ChatGPT and AI in Sports & Exercise Medicine manuscript generation. BMJ Open Sport & Exercise Medicine, 9(1). http://dx.doi.org/10.1136/bmjsem-2023-001568
  • Arista, A. & Abbas, B. S. (2022). Using the UTAUT2 model to explain teacher acceptance of work performance assessment system. International Journal of Evaluation and Research in Education, 11(4), 2200–2208. https://doi.org/10.11591/ijere.v11i4.22561
  • Bollen, K. A. (1989). Structural equations with latent variables. John Wiley & Sons. http://dx.doi.org/10.1002/9781118619179
  • Byrne, B. M. (2013). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Second Edition Multivariate Applications Series. Taylor & Francis.
  • Carrasco, J. P., García, E., Sánchez, D. A., Estrella-Porter, P. D., Puente, L. D. L., Navarro, J. & Cerame, A. (2023). Is "ChatGPT" capable of passing the 2022 MIR exam? Implications of artificial intelligence in medical education in Spain. Revista Española de Educación Médica, 4(1), 55–69. https://doi.org/10.6018/edumed.556511
  • Crawford, J., Cowling, M. & Allen, K. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI) Journal of University Teaching & Learning Practice, 20(3). https://doi.org/10.53761/1.20.3.02
  • Curtis, N. (2023). To ChatGPT or not to ChatGPT? The Impact of Artificial Intelligence on Academic Publishing. Pediatric Infectious Disease Journal, 42(4), 275. https://doi.org/10.1097/INF.0000000000003852
  • Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... Wright, R. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges, and implications of generative conversational AI for research, practice, and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
  • Engen, B. K. (2019). Understanding social and cultural aspects of teachers' digital competencies. Comunicar: Revista científica iberoamericana de comunicación y educación, 27(61), 9–19. Retrieved from https://doi.org/10.3916/C61-2019-01https://doi.org/10.3916/C61-2019-01
  • Gansser, O. A. & Reich, C. S. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, 65, 101535. https://doi.org/10.1016/j.techsoc.2021.101535
  • García, M., Sarmiento, J. R. & Antonovica, A. (2022). Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants. Frontiers in Psychology, 13, 993935. https://doi.org/10.3389/fpsyg.2022.993935
  • García-Martínez, I., Fernández-Batanero, J. M., Fernández-Cerero, J. & León, S. P. (2023). Analysing the Impact of Artificial Intelligence and Computational Sciences on Student Performance: Systematic Review and Meta-analysis. Journal of New Approaches in Educational Research, 12(1), 171–197. https://doi.org/10.7821/naer.2023.1.1240
  • García-Peñalvo, F. J. (2023). The perception of Artificial Intelligence in educational contexts after the launch of ChatGPT: Disruption or Panic? Education in the Knowledge Society, 24, 1–9. https://doi.org/10.14201/eks.31279
  • Graf, A. & Bernardi, R. E. (2023). ChatGPT in research: Balancing ethics, transparency, and advancement. Neuroscience, 515, 71–73. https://doi.org/10.1016/j.neuroscience.2023.02.008
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. & Tatham, R. L. (2006). Multivariate Data Analysis. Upper Saddle River.
  • Hair, J. F., Hult, G. T. M., Ringle, C. & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd). Sage.
  • Hassan, M. S., Islam, M. A., Yusof, M. F. B., Nasir, H. & Huda, N. (2023). Investigating the determinants of Islamic mobile FinTech service acceptance: A modified UTAUT2 approach. Risks, 11(2), 40. https://doi.org/10.3390/risks11020040
  • Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Kutyniok, . . & G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103. https://doi.org/10.1016/j.lindif.2023.102274
  • Khechine, H., Raymond, B. & Augier, M. (2020). The adoption of a social learning system: Intrinsic value in the UTAUT model. British Journal of Educational Technology, 51(6), 2306–2325. https://doi.org/10.1111/bjet.12905
  • Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd). Guilford Press.
  • Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., Leon, L. D., Elepaño, C., Madriaga, M., Aggabao, R., Díaz-Cándido, G., Maningo, J. & Tseng, V. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digital Health, 2(2). https://doi.org/10.1371/journal.pdig.0000198
  • Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I. & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. International Journal of Management Education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790
  • Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530. https://doi.org/10.1093/BIOMET/57.3.519
  • O'Connor, S. (2022). Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse? Nurse Education in Practice, 66, 103537. https://doi.org/10.1016/j.nepr.2022.103537
  • Ratchford, B. T. (1987). New insights about the FCB grid. Journal of Advertising Research, 27(4), 24–38.
  • Rozencwajg, S. & Kantor, E. (2023). Elevating scientific writing with ChatGPT: A guide for reviewers. Anaesthesia Critical Care and Pain Medicine, 42(3). https://doi.org/10.1016/j.accpm.2023.101209
  • Sallam, M. (2023). The Utility of ChatGPT as an Example of Large Language Models in Healthcare Education, Research and Practice: Systematic Review on the Future Perspectives and Potential Limitations. MedRxiv, 2(21), 1–34. https://doi.org/10.1101/2023.02.19.23286155
  • Salvagno, M., Taccone, F. S. & Gerli, A. G. (2023). Can artificial intelligence help with scientific writing? Critical Care, 27(1), 99. Retrieved from https://doi.org/10.1186/s13054-023-04380-2https://doi.org/10.1186/s13054-023-04380-2
  • Shinners, L., Aggar, C., Grace, S. & Smith, S. (2019). Exploring healthcare professionals' understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review. Health Informatics Journal, 1460458219874641. https://doi.org/10.1177/1460458219874641
  • Sohn, K. & Kwon, O. (2020). Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products. Telematics & Informatics, 47, 101324. https://doi.org/10.1016/j.tele.2019.101324
  • Stage, F. K., Carter, H. C. & Nora, A. (2010). Path Analysis: An Introduction and Analysis of a Decade of Research. The Journal of Educational Research, 98(1), 5–13. https://doi.org/10.3200/JOER.98.1.5-13
  • Stokel-Walker, C. (2022). AI bot ChatGPT writes smart essays - should professors worry? Nature . https://doi.org/10.1038/d41586-022-04397-7
  • Stokel-Walker, C. & Van Noorden, R. (2023). What ChatGPT and generative AI mean for science. Nature, 614, 214–216. https://doi.org/10.1038/d41586-023-00340-6
  • Tamboleo-García, R. (2023). Teaching innovation faced the challenges of the limitations of the covid-19 pandemic for industrial and laboral sociology. HUMAN REVIEW. International Humanities Review, 18(1), 1–8. https://doi.org/10.37467/revhuman.v18.4862
  • Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R. & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x
  • Tong, Y. & Zhang, L. (2023). Discovering the next decade's synthetic biology research trends with. ChatGPT. Synthetic and Systems Biotechnology, 8(2), 220–223. https://doi.org/10.1016/j.synbio.2023.02.004
  • Torres-Salinas, D. & Arroyo-Machado, W. (2023). ChatGPT en la universidad: usos prácticos en diferentes contextos académicos. Retrieved from https://www.youtube.com/watch?v=oJultNCHuAM&t=22s
  • Uncovska, M., Freitag, B., Meister, S. & Fehring, L. (2023). Patient acceptance of prescribed and fully reimbursed mHealth apps in Germany: An UTAUT2-based online survey study. Journal of Medical Systems, 47(1), 14. https://doi.org/10.1007/s10916-023-01910-x
  • UNESCO. Informe de los Objetivos de Desarrollo Sostenible. Retrieved from https://bit.ly/34nbq60
  • Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
  • Venkatesh, V., Thong, J. Y. & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412