Application of artificial intelligence in industrial engineering degrees: a case study

Abstract

Integrating emerging Artificial Intelligence (AI) tools into the teaching of Industrial Engineering courses has become a crucial aspect of the university environment. This requires both the continuous training of faculty members and the integration of new AI-based tools into teaching, as well as careful consideration of the significant ethical and social impact of these technologies. To address these objectives, the University of Valladolid (Spain) has funded an Innovative Educational Project at the Industrial Engineering School, with the participation of five different technological departments involved in its engineering degrees. This paper presents the main results and conclusions obtained during the initial phases of this project, which have primarily focused on training lecturers in the use of AI tools to effectively integrate them into their teaching methodologies and to develop new educational materials. Specifically, AI tools are being used to generate questionnaires for student self-assessment, based on the content covered in each session. A key finding is the necessity of encouraging students to develop a strong critical mindset when using AI tools, particularly in analysing the reasoning behind AI-generated solutions. It has been observed that AI-driven self-assessment is particularly beneficial for theoretical knowledge, although students are guided to critically evaluate the AI's output, especially in problem-solving, where errors in intermediate steps can occur. The paper also presents specific examples related to systems and automation engineering using different AI tools and analysing their responses collaboratively with students to identify their strengths and weaknesses, highlighting both the potential and the current limitations of AI tools in these practical domains. To summarize the main conclusions derived from this study, it is essential to encourage students to develop a strong critical mindset when evaluating responses provided by AI-based tools. To achieve this, it is important to allow and encourage the use of such tools in the classroom, guiding students in identifying inconsistencies in AI-generated texts or results, and comparing them with other sources of knowledge. Moreover, it is a priority for lecturers to stay continuously updated on advancements in AI-based tools. Anticipating the impact of these tools on teaching is crucial, as their development and applications are constantly evolving and improving. Furthermore, with the gradual integration of AI into teaching activities, future engineers will be well-positioned to adapt to and lead technological changes in their industrial careers. Initiatives and experiences like this study will help both lecturers and students in their daily activities, allowing them to adapt to constant technological changes and helping them become better professionals in the not-so-distant future.