Student Perceptions of NVIDIA DLSS in the Context of AI and Computer Graphics Education

Abstract

This study explores university students’ perceptions of NVIDIA Deep Learning Super Sampling (DLSS) in the context of artificial intelligence and computer graphics education. The research aimed to examine students’ prior awareness of DLSS, their basic understanding of its AI-based operation, and their views on its possible educational relevance in higher education. Data were collected through a questionnaire consisting of six yes/no questions; the present paper focuses on familiarity, perceived relevance, and educational applicability. The survey was completed by 39 university students.

The results indicate a high level of awareness of the technology among respondents. A total of 89.7% reported that they had previously heard about NVIDIA DLSS, while 82.1% stated that they knew the technology uses artificial intelligence to improve image resolution. The educational relevance of the topic was also strongly supported: 89.7% considered DLSS an interesting topic for computer science or engineering studies, and the same proportion expressed interest in learning more about how it works during their university studies. Furthermore, 66.7% believed that DLSS could support the practical understanding of artificial intelligence, and 69.2% agreed that it could help illustrate the operation of modern graphics technologies.

Overall, the findings suggest that NVIDIA DLSS has notable educational potential as a contemporary, technology-oriented topic that may enhance student engagement in AI and computer graphics education.