Influence of critical thinking on LLM usage among Universitat d’Andorra students
DOI:
https://doi.org/10.14198/ijd.28095Paraules clau:
Artificial Intelligence, Large Language Models, Critical Thinking, Higher educationResum
As large language models continue to reshape educational practices, a comprehensive evaluation of critical thinking’s influence on large language models’ usage becomes essential. This study examines how students in the fields of education and computer science at the Universitat d’Andorra interact with large language models, with a particular focus on understanding their learning experiences, decision-making strategies, and problem-solving approaches. Using qualitative and quantitative methods, the research analyzes the frequency and purposes of using these technologies, as well as the critical thinking processes students employ to assess the reliability and relevance of content generated by artificial intelligence. Findings reveal a spectrum of attitudes towards large language models, ranging from enthusiastic adoption to skepticism. While many students appreciate the immediate and personalized academic support, content generation assistance, and writing skill improvement offered by these tools, concerns about the accuracy and potential biases of the outputs are prevalent. Notably, students demonstrate varying levels of the activation of their critical thinking skills when engaging with large language models, with some actively investigate the reliability of artificial intelligence generated information, while others exhibit a more passive reliance on these technologies. The study also highlights distinct usage patterns between computer science and education students. The results contribute to a deeper understanding of student behavior in the context of artificial intelligence enhanced education, providing valuable insights for educational institutions aiming to integrate these tools into their curricula effectively. Furthermore, this research emphasizes the need to enhance critical thinking skills within educational programs to empower students to navigate the complexities of large language models capabilities and limitations.
Referències
Alaeddine, M. and Tannoury, A. (2021). Artificial Intelligence in Music Composition. in Artificial Intelligence Applications and Innovations: 17th IFIP WG 12.5 International Conference, AIAI 2021, Hersonissos, Crete, Greece, June 25-27, 2021, Proceedings 17, Springer, 387-397. https://doi.org/10.1007/978-3-030-79150-6_31
Allueva, P. (2002). Conceptos básicos sobre metacognición. P. Allueva, Desarrollo de habilidades metacognitivas: programa de intervención, 59-85.
Baidoo-Anu, D. and Ansah, L. O. (2023). Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
Baskara, F. R., Puri, A. D. and Wardhani, A. R. (2023). ChatGPT and the Pedagogical Challenge: Unveiling the Impact on Early-Career Academics in Higher Education. Indonesian Journal on Learning and Advanced Education (IJOLAE), 5(3), 311-322. https://doi.org/10.23917/ijolae.v5i3.22966
Bellman, R. E. (1978). Artificial intelligence: Can computers think? Boyd and Fraser Publishing Company
Bengio, Y., Ducharme, R. and Vincent, P. (2000). A Neural Probabilistic Language Model. Advances in neural information processing systems, 13. https://doi.org/10.1007/10985687_6
Berg, G. and Plessis, E. (2023). ChatGPT and Generative AI: Possibilities for Its Contribution to Lesson Planning, Critical Thinking and Openness in Teacher Education. Education Sciences, 13(10), 998. https://doi.org/10.3390/educsci13100998
Bliss, J., Monk, M., Ogborn, J. and Black, P. J. (1983). Qualitative data analysis for educational research: A guide to uses of systemic networks. London: Croom Helm.
Bloom, B. S., Engelhart, M. B., Furst, E. J., Hill, W. H. and Krathwohl, D. R. (1956). TAXONOMY OF EDUCATIONAL OBJECTIVES The Classification of Educational Goals. New York: Longmans Green.
Carrera, F. X., Vaquero, E., Balsells, M. À. et al. (2011). Instrumento de evaluación de competencias digitales para adolescentes en riesgo social. Edutec: revista electrónica de tecnología educativa. https://doi.org/10.21556/edutec.2011.35.410
Couso, D. and Márquez, C. (2023). Pensar críticament a l'aula de ciències. Activitats competencials per a estudiants de secundaria. Editorial Graó.
Dunn, D. S., Halonen J. S. and Smith, R. A. (2009). Teaching Critical Thinking in Psychology: A Handbook of Best Practices. John Wiley & Sons. https://doi.org/10.1002/9781444305173.ch1
Ennis, R. H. (1987). A taxonomy of critical thinking dispositions and abilities. WH Freeman/Times Books/Henry Holt & Co
Facione, P. (1990). Critical Thinking: A Statement of Expert Consensus for Purposes of Educational Assessment and Instruction. California State University.
George-Reyes, C. E., López-Caudana, E. O. and Ramírez-Montoya, M. S. (2023). Research competencies in university students: Intertwining complex thinking and Education 4.0. Contemporary Educational Technology, 15(4), ep478. https://doi.org/10.30935/cedtech/13767
González, L. A. O., Baren, C. Y. O. and Zapata, E. J. P. (2023). El impacto de la inteligencia artificial en el ámbito educativo. Revista Científica FIPCAEC (Fomento de la investigación y publicación científico-técnica multidisciplinaria). ISSN: 2588-090X. Polo de Capacitación, Investigación y Publicación (POCAIP), 8(3), 342-354.
Halpern, D. F. (1998). Teaching Critical Thinking for Transfer Across Domains Dispositions, Skills, Structure Training, and Metacognitive Monitoring. American psychologist 53(4), 449-455. https://doi.org/10.1037/0003-066X.53.4.449
Huschens, M., Briesch, M., Sobania, D. and Rothlauf, F. (2023). Do You Trust ChatGPT? - Perceived Credibility of Human and AI-Generated Content. arXiv (Cornell University). https://doi.org/10.48550/arXiv.2309.02524
Irfan, M., Murray, L. and Ali, S. (2023). Insights into Student Perceptions: Investigating Artificial Intelligence (AI) Tool Usability in Irish Higher Education at the University of Limerick. Global Digital & Print Media Review, VI(II), 48-63. https://doi.org/10.31703/gdpmr.2023(VI-II).05
Izquierdo, M. and Aliberas, J. (2021). Pensamiento crítico y valores en las distopías del no futuro [sesión de simposio]. XI Congreso Internacional sobre Investigación en la Didáctica de las Ciencias: Aportaciones de la educación científica para un mundo sostenible, 1923-1926.
Jiao, W., Wang, W., Huang, J.-t., Wang, X. and Tu, Z. (2023). Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine. arXiv (Cornell University). https://doi.org/10.48550/arXiv.2301.08745
Kasneci, E., Seßler, K., Kuchemann, S. et al. (2023). ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. Learning and individual differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kim, G. and Chun, S. Y. (2023). DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Model. in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 14203-14213. https://doi.org/10.1109/CVPR52729.2023.01365
Kurzweil, R., Richter, R., Kurzweil, R. and Schneider, M. L. (1990). The age of intelligent machines. MIT press Cambridge, 580.
Liu, B. L., Morales, D., Roser-Chinchilla, J. et al. (2023). Harnessing the Era of Artificial Intelligence in Higher Education: A Primer for Higher Education Stakeholders.
Liu, M., Wei, Y., Wu, X., Zuo, W. and Zhang, L. (2023). A Survey on Leveraging Pre-trained Generative Adversarial Networks for Image Editing and Restoration. Science China Information Sciences, 66(5), 1-28. https://doi.org/10.1007/s11432-022-3679-0
Lo, C. K. (2023). What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
Ningrum, S. et al. (2023). ChatGPT's Impact: The AI Revolution in EFL Writing. Borneo Engineering & Advanced Multidisciplinary International Journal, 2, 32-37.
OpenAI, Chatgpt. (2022). [Online]. Available: https://chat.openai.com
Paul, R. and Elder, L. (2005). Una Guía Para los Educadores en los Estándares de Competencia para el Pensamiento Crítico. Estándares, Principios, Desempeño, Indicadores y Resultados. Con una Rubrica maestra en el pensamiento crítico.
Pimentel, D. (2022). Learning to evaluate scientific evidence in the age of digital information. eBook of Synopses, 43.
Sabzalieva, E. and Valentini, A. (2023). ChatGPT and Artificial Intelligence in higher education: Quick start guide.
Sandoval, W. A. and Millwood, K. A. (2005). The quality of students' use of evidence in written scientific explanations. Cognition and Instruction, 23(1), 23-55. https://doi.org/10.1207/s1532690xci2301_2
Singh, H., Tayarani-Najaran, M.-H. and Yaqoob, M. (2023). Exploring Computer Science Students' Perception of ChatGPT in Higher Education: A Descriptive and Correlation Study. Education Sciences, 13(9), 924. https://doi.org/10.3390/educsci13090924
Solís, M. E. C., Martínez, E. L., Degante, E. C., Godoy, E. P. and Martínez, Y. A. (2023). Inteligencia artificial generativa para fortalecer la educación superior: Generative artificial intelligence to boost higher education. LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades, 4(3), 767-784. https://doi.org/10.56712/latam.v4i3.1113
Susnjak, T., & McIntosh, T. R. (2024). ChatGPT: The end of online exam integrity? Education Sciences, 14(6), 656. https://doi.org/10.3390/educsci14060656
Tura, L. V., Bargalló, C. M., Prat, B. O. et al. (2023). Una propuesta para el diseño de actividades que desarrollen el pensamiento crítico en el aula de ciencias. Revista Eureka Sobre Enseñanza Y Divulgación De Las Ciencias, 20(1). https://doi.org/10.25267/Rev_Eureka_ensen_divulg_cienc.2023.v20.i1.1302
UNESCO. (2019). BEIJING CONSENSUS on artificial intelligence and education.
Vaswani, A., Shazeer, N., Parmar, N. et al. (2017). Attention Is All You Need. Advances in neural information processing systems, 30. https://doi.org/10.48550/arXiv.1706.03762
Zhang, C., Zhang, C., Zheng, S. et al. (2023). A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need? arXiv (Cornell University). https://doi.org/10.48550/arXiv.2303.11717
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Drets d'autor (c) 2024 Marc Bleda Bejar, Aleix Dorca Josa, Begoña Oliveras Prat
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