TY - JOUR
T1 - Generative artificial intelligence in higher education
T2 - Students’ journey through opportunities, challenges, and the horizons of academic transformation
AU - Jwair, Amani Abdullah Bin
N1 - Publisher Copyright:
© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2025
Y1 - 2025
N2 - This study examined university students’ perceptions of generative artificial intelligence (Gen-AI) in supporting learning and academic achievement, using a descriptive quantitative method. Data were collected from a sample of 1,537 students across various academic disciplines and levels. Results revealed generally positive attitudes, with a high overall mean score (M = 3.72), reflecting Gen-AI’s perceived benefits in enhancing motivation, collaboration, academic performance, and decision-making. However, concerns were also reported (M = 3.87), including data privacy, limited Arabic-language tools, and a lack of technical support. Statistically significant differences (p < 0.05) were observed across gender, academic stage, field of specialization, and computer experience. Male and diploma-level students reported the highest levels of engagement with Gen-AI tools. This study contributes to the growing body of research by providing empirical insights into how diverse student populations perceive Gen-AI in higher education. The findings highlight the need for tailored training, ethical guidelines, and inclusive policies to support responsible AI integration in education.
AB - This study examined university students’ perceptions of generative artificial intelligence (Gen-AI) in supporting learning and academic achievement, using a descriptive quantitative method. Data were collected from a sample of 1,537 students across various academic disciplines and levels. Results revealed generally positive attitudes, with a high overall mean score (M = 3.72), reflecting Gen-AI’s perceived benefits in enhancing motivation, collaboration, academic performance, and decision-making. However, concerns were also reported (M = 3.87), including data privacy, limited Arabic-language tools, and a lack of technical support. Statistically significant differences (p < 0.05) were observed across gender, academic stage, field of specialization, and computer experience. Male and diploma-level students reported the highest levels of engagement with Gen-AI tools. This study contributes to the growing body of research by providing empirical insights into how diverse student populations perceive Gen-AI in higher education. The findings highlight the need for tailored training, ethical guidelines, and inclusive policies to support responsible AI integration in education.
KW - digital literacy
KW - Generative artificial intelligence
KW - higher education
KW - pedagogical practices
KW - technological ethics
UR - https://www.scopus.com/pages/publications/105022609561
U2 - 10.1080/2331186X.2025.2589495
DO - 10.1080/2331186X.2025.2589495
M3 - Article
AN - SCOPUS:105022609561
SN - 2331-186X
VL - 12
JO - Cogent Education
JF - Cogent Education
IS - 1
M1 - 2589495
ER -