AI vs. human performance in university assessments: a case study in production management

This study explores the application of Google NLM, an AI model uniquely trained on lecture audio, in a specialized engineering course on Production Management. The model was tested under real exam conditions and compared to the performance of 14 students from the 2022-2023 academic year. Results show that the AI consistently passed the exam, achieving an average score of 23.5/30, comparable to the student average of 23/30. While demonstrating strong consistency and factual recall, the AI struggled with numerical reasoning and applied problem-solving, particularly in inventory management and statistical decision-making. Key contributions include the first application of an audiotrained AI in engineering education and an analysis of AI performance in a highly technical domain. While not exceeding top human scores, the AI's stability suggests potential as a benchmarking tool for exam design and student assessment. Future research should explore multilingual training, hybrid audio-text learning, and domain-specific fine-tuning to enhance AI's role in academic evaluation.