Assessing student-perceived impact of using artificial intelligence tools: Construction of a synthetic index of application in higher education

• Published in: Cogent education Vol. 11; no. 1
• Main Authors: Grájeda, Alberto, Burgos, Johnny, Córdova, Pamela, Sanjinés, Alberto
• Format: Journal Article
• Language: English
• Published: Taylor & Francis Group 31-12-2024
• Subjects: Artificial intelligence in higher education; Artificial Intelligence tools; ChatGpt; learning; synthetic index; teaching
• ISSN: 2331-186X; 2331-186X
• DOI: 10.1080/2331186X.2023.2287917

AbstractThis study aims to assess the adoption and impact of Artificial Intelligence (A.I.) tools in higher education, focusing on a private university in Latin America. Guided by the question, “What is the impact, as perceived by university students, of using Artificial Intelligence tools on various dimensions of learning and teaching within the context of higher education?” the study employs a rigorously validated 30-item instrument to examine five key dimensions: 1) Effectiveness use of A.I. tools, 2) Effectiveness use of ChatGPT, 3) Student’s proficiency using A.I. tools, 4) Teacher’s proficiency in A.I. and 5) Advanced student skills in A.I. These dimensions form a synthetic index used for comprehensive evaluation. Targeting 4,127 students from the university’s schools of Engineering, Business, and Arts, the study garnered 21,449 responses, analyzed using Confirmatory Factor Analysis for validity. Findings indicate a significantly positive impact of A.I. tools on student academic experiences, including enhanced comprehension, creativity, and productivity. Importantly, the study identifies areas with low and high A.I. integration, serving as an institutional diagnostic tool. The data underscores the importance of A.I. proficiency among both educators and students, advocating for its integration as a pedagogical evolution rather than just a technological shift. This research has critical implications for data-driven decision-making in higher education, offering a robust framework for institutions aiming to navigate the complexities of A.I. implementation.