Year: 2025
Type: article
Abstract: In recent years, large language models (LLMs) have gained considerable attention in academic environments, particularly for their potential to support student work. This paper investigates how the use of LLM tools influences graduate engineering students’ performance and perception during project-based learning. The study was conducted over the course of one semester at a Romanian technical university and involved 60 students, divided into two groups: one using AI tools such as ChatGPT and one working with traditional resources only. A mixed-method approach was employed, including pre- and post-project questionnaires and a dual evaluation system involving both human and AI grading, based on a shared rubric. Results show a significant increase in perceived satisfaction and a reduction in the reported difficulty among students who had access to AI tools. Moreover, their average grades were higher and more consistent compared to those in the non-AI group. The study also highlights the alignment between human and AI-based assessment and the growing openness among students toward adopting generative tools in future academic work. These findings suggest that integrating LLMs into higher education may improve learning experiences, but also raise questions about critical thinking, fairness, and ethical use.
Author: Alexandru Dinu
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4414353945