Project Profile

Semiconductors are essential components of electronic devices, enabling advances in all important applications and systems such as communication, healthcare, and national security. In order to sustain the U.S.’s global competitiveness in the semiconductor industry, there is a growing demand for skilled semiconductor workforce. High schoolers are among the most frequent users of electronic devices. However, many do not know how these devices are designed and manufactured. To address the knowledge gaps and workforce needs in an equitable manner, this project will develop a semiconductor curriculum with the high-school-aged students, and with partners in higher-education, K-12, and industries, enhanced with AI and innovative technologies. Game-based semiconductor modules will be created for the students to play and learn with peers choosing culturally diverse avatars. These learning modules will be made available to a wide range of students through the project collaborator Stemuli, a game-based learning company. In addition, approximately 50 students each summer (years 2-4) will be engaged in in-person workshops hosted in Maine and Texas. Through these workshops, students will be engaged in hands-on activities and field trips to semiconductor companies such as Texas Instruments where they will connect their game-based learning with industry experiences. Based on students’ feedback, the workshop and game curriculum will be designed and improved iteratively.

 The project aims to help high-school students develop skills and career interests in the semiconductor fields through an innovative game-based learning platform, hands-on activities, and industry field trips. The overarching research question is: To what extent do the designs and integration of AI Educator (a generative AI tool for education), game-based learning, and hands-on experiences provide equitable access and strengthen students’ engagements, awareness, interests, and knowledge in STEM careers? The AI Educator will provide students with suggestions, assistance, and additional insights about the subject. The AI component will tune the output content based on the student’s interests and preferences to make the experience more relatable. Data collection will include students’ attitudes, game activities, and hands-on learning outcomes. Design-based research methods will be used incorporating the NASA Task Load Index, t-test, interviews, and surveys to understand students’ learning and efficacy of the game and workshop curriculum. The Technology, Pedagogy, and Content Knowledge (TPACK) framework will be used and refined throughout the AI and game technology integration into the semiconductor curriculum and education pathways. The project will be designed with a focus on equity, accessibility, engagement, and collaboration, catering to students from diverse backgrounds.