技术进展国际期刊
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Assessing the Psychological Impact of Generative AI on Data Science Education: An Exploratory Study

Henrique Ramos Pinto, Vitor Meneghetti Ugulino de Araujo, Cleydson de Souza Ferreira Junior, Lutero Lima Goulart, Gabriel Silva Aguiar, João Vitor Cardoso Beltrão, Paloma Duarte de Lira, Samuel José Fernandes Mendes, Filipe de Lima Vaz Monteiro, Erlon Lacerda Avelino

The integration of AI in educational settings, particularly through Large Language Models (LLMs), is accelerating, reshaping pedagogical approaches due to students’ interactions with new learning tools. This study assesses the impact of generative AI on the educational experiences of computer and data science students at the Center for Informatics, University of Paraíba (CI/UFPB), Brazil. Through Exploratory Factorial Analysis (EFA) of five psychometric scales, the research examines students’ acceptance of LLMs, their associated burnout levels, technology anxiety, and the prevalence of metacognitive and dysfunctional learning strategies associated with LLMs. Results indicate significant adoption of AI technologies among students, accompanied by a low incidence of technology anxiety, manifesting as fears of losing jobs to AI. However, a significant correlation was observed between academic burnout and dysfunctional learning strategies, which could likely be attributed to the rigorous academic environment. Additionally, the employment of metacognitive strategies in conjunction with LLMs reflects an advanced learning approach, yet challenges with functional learning strategies persist. This study contributes to the discourse on AI in education, highlighting the need for educational frameworks that support effective AI adoption while addressing the psychological demands on students.