Exploring Large Language Models Integration in Higher Education: A Case Study in a Mathematics Laboratory for Civil Engineering Students

This study investigates the integration of large language models (LLMs) alongside computer algebra systems (CAS) in a mathematics laboratory for civil engineering students, examining their combined impact on problem-solving and inquiry-driven learning. The intervention was designed using the integrate LLMs alongside CAS (ILAC) approach, which structures the inquiry process into key phases, guiding students through exploration, hypothesis testing, and solution validation. Six structured activities were implemented and assessed using quantitative and qualitative methods. Findings reveal that LLMs enhanced conceptual understanding, clarified methodologies, and assisted with command syntax, while CAS ensured computational accuracy and result validation. Many students critically cross-verified LLM-generated results with CAS, though some relied solely on LLMs, highlighting the need for better guidance on tool usage. While LLMs fostered engagement, skepticism remained regarding their ability to address deeper mathematical deficiencies. The intervention led to moderate improvements in students' familiarity with AI tools, though its short duration and the use of general-purpose LLMs limited perceived usefulness. To maximize educational benefits, future implementations should consider longer interventions, advanced training in prompt engineering, and tailored AI solutions.