FOSTERING ARTIFICIAL INTELLIGENCE COMPETENCIES THROUGH PROJECT-BASED LEARNING: A CAPSTONE APPROACH
Year: 2024
Editor: Grierson, Hilary; Bohemia, Erik; Buck, Lyndon
Author: Ayala-Garcia, Ivo N.; Lugo-del-Real, Eloina; González, Alejandro
Series: E&PDE
Institution: School of Engineering and Sciences. Tecnologico de Monterrey.; Vicerrectoría de Investigación y Transferencia de Tecnología. Tecnologico de Monterrey.
Page(s): 443 - 448
DOI number: 10.35199/EPDE.2024.75
ISBN: 978-1-912254-200
ISSN: 3005-4753
Abstract
Introduction In today’s quickly evolving technological landscape, engineering graduates must be able to understand the fundamentals of cutting-edge techniques. Under this perspective both students and faculty must explore the digital world and artificial intelligence as allies in technological innovation. As the demand for Artificial Intelligence (AI) expertise continues to rise, equipping students with essential AI competencies has become imperative. For their final capstone projects, engineering students were asked to come up with an innovative system, under the supervision of four faculty members. This paper presents the student’s learning experience while designing AI based systems in real-world scenarios and resulted in fostering hands-on experience in novel technologies. Methods Currently, students have free access to tools for the development and innovation of technology using artificial intelligence such as neural networks. Final year engineering students were tasked with developing a capstone project to showcase their skills and were given ten weeks for ideation, implementation, and testing. Some of these teams decided on the integration of AI into their design. This required students to conceptualize, develop, and execute projects integrating AI solutions. For the product design using neural networks, there are many free access tools and algorithms, making the technology collaborative with teaching techniques. First, students followed an introductory course on the use of AI and AIoT systems. This first interaction guided them through the use of accessible tools such as Google’s Teachable Machine, and Edge Impulse. While the students recognized the ease of use of these tools, they quickly outgrew them and had to find other alternatives to suit their design requirements. Students had to evaluate the effectiveness of their respective systems. This opened the door to reinforce important concepts on AI such as ROC curves and confusion matrices. In this way, an open-ended self-assigned project may be guided towards the completion of learning objectives. Results Students presented three projects which depended on the use of AI. (i) An automated inventory system with object and speech recognition, (ii) a Human-Robot interactive tool capable of differentiating hand gestures, (iii) Vehicle and pedestrian detection system. The students’ exploration was mostly self-guided, allowing them to increase their confidence and be responsible for the learning process. The implementation of AI techniques felt novel and was able to keep them engaged on the task. The projects not only demonstrated technical proficiency but also underlined the students' ability to think critically, and to apply AI methodologies to solve real-world challenges through collaborative efforts. In this way, students gained practical insights into the challenges of implementing AI technologies. In conclusion, the outcomes of this capstone project underscore the necessity for integrating AI courses into the academic curriculum. The experiences gained through project-based learning offer a valuable foundation for students to grasp the complexities of AI technologies and their practical applications which are essential for preparing students for joining the workforce. This paper advocates for the integration of AI in higher education to empower students with the skills needed to navigate the dynamic landscape of emerging technologies regardless of their disciplines.
Keywords: Higher Education, educational innovation, artificial intelligence