2026 ASEE Annual Conference & Exposition

Providing engineering students with access to Generative AI (GenAI) tools, such as online resources for Large Language Models (LLMs), application programming interfaces (APIs), and the computational power of graphics processing units (GPUs), is an essential first step in fostering innovation within academic makerspaces. However, access alone is not enough to ensure these tools are used effectively, especially when students are tasked with solving complex and interdisciplinary problems. Addressing real world challenges requires more than technical proficiency; students must also learn to contextualize GenAI tools for specific applications, overcome infrastructure limitations, and thoughtfully navigate ethical considerations.
This work-in-progress paper investigates the problem of how to support students in effectively utilizing GenAI tools in academic makerspaces beyond simply providing access. It presents preliminary results from the first step of a study involving a group of expert users. 22 undergraduate students accomplished several impressive projects, including a simulation chatbot for social work training, a legal information assistant, and a moot court advocacy simulator. These projects highlight not only the potential of GenAI tools to address real-world challenges but also the significant achievements students can accomplish when given access to advanced tools and proper support. The work demonstrates how students can adapt GenAI to specific domains, overcome technical and infrastructure limitations, and collaborate across disciplines while learning valuable technical and problem-solving skills.
Through surveys, students shared their first-hand experiences with utilizing AI tools in academic makerspaces, highlighting common challenges and opportunities. They also provided insights into the steps academic makerspaces could take to better support students. Notably, while students ranked ethical awareness as the “least challenging” aspect compared to technical skill-building, they emphasized the importance of teaching ethics alongside technical topics to make it more actionable and relevant. Embedding ethical discussions into technical workshops, such as those focused on bias mitigation or the societal implications of AI, could help ensure that ethical considerations are directly connected to practical, real-world applications.
In addition to these observations, the survey highlights emerging trends in AI development for academic makerspaces, such as retrieval-augmented generation (RAG), multimodal AI, vision-language-action models, and multi-agent orchestration. These trends reflect students’ interest in advancing beyond foundational AI tools to tackle increasingly complex and hardware-integrated problems.
The findings propose a plan for academic makerspaces to transition from being mere access providers to becoming ecosystems of support. Recommendations include building resilient infrastructure, expanding access to advanced AI tools, fostering interdisciplinary collaboration, and offering structured training and mentorship opportunities. By adopting this plan, academic makerspaces can empower students to create innovative, contextually relevant, and socially responsible solutions to pressing societal challenges, equipping them with both technical expertise and ethical awareness to make a meaningful impact.