GenAI in private higher education: Student insights by gender, study level, and delivery mode
Year: 2025
Type: article
Study design: Observational Study
Abstract: As generative artificial intelligence (GenAI) tools gain importance in higher education, understanding how different student groups engage with these technologies is essential for equitable integration. This study investigates the perceived differences in awareness, use, and benefits of GenAI and reference management tools across gender, level of study (undergraduate vs. postgraduate), and mode of delivery (contact, part-time, distance) in five private higher education institutions (PHEIs) in South Africa. Following a quantitative research approach, a total of 1,866 students participated in a structured, Likert-scale questionnaire distributed via MS Forms. Based on Pearson’s chi-square test and the chi-square goodness-of-fit test, significant differences emerged across genders, modes of delivery, and study levels. Female students were more likely to use GenAI for paraphrasing and grammar support, while male students engaged more with tools for coding, image generation, and mathematics. Postgraduate and part-time students reported higher perceived benefits, particularly in terms of efficiency and academic support, while distance students consistently reported lower perceived value and confidence in usage. The results support the need for targeted AI literacy interventions, particularly for female students and those in distance learning, as well as training that aligns with specific fields and tasks. These differences highlight the urgent need for targeted AI literacy initiatives and pedagogical interventions that address structural inequities in private higher education settings.
Author: Shamola Pramjeeth
Institution: The Independent Institute of Education
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4413601929