Generative Artificial Intelligence and Academic Performance
Year: 2025
Type: article
Study design: Observational Study
Abstract: The purpose of the study was to investigates the relationship between generative artificial intelligence (GAI), academic performance (AP) and smart learning environment (SLE) as a mediator. A convenience sampling technique was used to select a sample size of 456 respondents. Primary data was collected using a self-administered questionnaire and analysed using descriptive and inferential statistics. Partial least squares-structural equation model (PLS-SEM) was employed to analyse the structural model and determine the direct connections between the different elements. The results establish that generative artificial intelligence has a positive and significant influence on smart learning environment and academic performance (β = 0.523, t = 10.178, p < 0.000); β = 0.387, t = 7.353, p < 0.000 respectively). Simultaneously, smart learning environment partially mediates between the generative artificial intelligence and academic performance among university students (β = 0.06, t = 1.19, p < 0.234). The results of this study contributes to the current academic discourse on technology-enhanced education by showing that generative artificial intelligence have a positive impact on students’ academic performance.
Author: Joseph Ngugi Kamau
Institution: United States International University Africa
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4407891483