Generative AI-based Personalized Semiconductor Education using Extended Reality

S. Salehi, P. Satam, E. Azimi, R. Straight, A. Salado
The University of Arizona,
United States

Keywords: Semiconductor Workforce Development, Extended Reality (XR), Generative AI, K-12 Outreach

Summary:

The CHIPS for America Act, signed in October 2022, aims to revitalize the U.S. semiconductor industry with a $280 billion investment, with a focus on semiconductor workforce development. Despite this, a talent shortage exists, exacerbated by issues like outdated curricula and the late introduction of semiconductor topics in educational settings. Addressing these challenges by sparking interest in the high K-12 stage could create a sustainable pipeline of skilled workers for the industry. Recent advancements in using virtual reality (VR) and augmented reality (AR) technologies for educational training and workforce development have shown to be promising and beneficial with respect to effectively achieving learning outcomes in various STEM disciplines. To address these challenges, herein we propose a scalable, personalized, and immersive VR/AR-enabled pedagogical framework for semiconductor education and workforce development in high K-12, community college, undergraduate, and graduate levels. The proposed framework consists of a series of interactive learning components that encompass the entire cycle of designing, manufacturing, and testing of a semiconductor device and circuit. The proposed framework uses generative AI along with sentiment analysis to personalize the difficulty level of the activities and content delivery as well as evaluate student interest and knowledge comprehension. We aim to explore the use of generative AI to create and deliver a personalized semiconductor curriculum to meet predefined learning outcomes as well as to create an interactive instructor to gauge the learner’s interest and assist with effectively guiding students throughout the activities. Furthermore, we will explore the benefits of using VR/AR-enabled semiconductor education components along with gamification to maximize learning outcomes in high K-12, community college, undergraduate, and graduate levels. We will identify ways to use such personalized curricula to help marginalized communities and underrepresented minorities in learning and overcoming systemic challenges. Research indicates that the primary barrier hindering the progress of underrepresented groups, especially in STEM, is the absence of early high-quality education, which results in lower success rates in the learners from these communities. The proposed framework aims to address the enduring challenges faced by these underserved and underrepresented communities. Finally, the success of this project offers a pathway for high K-12, community college, undergraduate, and graduate students to pursue high-paying careers in semiconductor design and manufacturing.