Year: 2024
Type: article
Study design: Observational Study
Abstract: 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.
DOI: 10.14198/ijd.28095
Institutions: University of Andorra, Universitat Autònoma de Barcelona
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4404362232