Biomaterials education through artificial intelligence-enabled product-based learning

Traditionally, materials engineering education has relied on direct teaching methods, with students often engaged in passive memorization. However, this approach is becoming inadequate in the modern educational context, characterized by global access to information and the rise of innovative technologies such as artificial intelligence (AI), augmented reality, virtual reality, and metaverse platforms. Education today requires fostering skills that empower students to develop innovative solutions and products addressing societal demands. Incorporating product-based learning (PBL) strategies into the curriculum of biomaterials education prepares students with essential skills, competencies, and expertise needed for success in the dynamics of the circular bioeconomy. This chapter outlines a strategic approach that utilizes AI technologies, including deep learning, generative pretrained transformers, and large language models, to enhance and accelerate the deployment of PBL methodologies within the context of biomaterials engineering education. This approach aims to actively engage students in solving real-world challenges with biomaterials while promoting creativity and entrepreneurship through brainstorming and product manufacturing-oriented processes. Furthermore, integrating principles of the circular bioeconomy—focusing on the use of renewable resources, waste reduction, and resource efficiency—into chemical engineering education equips students to make informed decisions within the circularity framework. This approach not only supports academic and professional growth but also fosters societal well-being by promoting the development and adoption of sustainable technologies and practices.