Mixed reality (MR) and AI-powered pedagogical agents have been increasingly explored in STEM labs context as a means of providing hands-on practice with virtual teaching assistants. However, teaching microelectronics presents unique challenges because learners must integrate conceptual knowledge, procedural skills, and visual–spatial understanding to reason about multilayer chip structures and how fabrication processes optimize performance. We introduce ChipXR, a mixed-reality learning environment developed through a design-science approach and multistakeholder participatory design involving instructors, teaching assistants, students, education researchers, and HCI researchers to systematically refine interaction design and reduce potential cognitive load. The final prototype integrates interactive lecture modules for conceptual understanding, embodied MR activities for procedural skill development, and a LEGO-based building task to foster visual–spatial reasoning, all supported by a GPT-powered agent that explains the principles behind each activity. In a controlled study comparing MR+AI agent, MR-only, and traditional video-based lecture, we found no significant differences in conceptual quiz scores, but the MR+AI condition showed trends associated with visual–spatial understanding and perceived knowledge gains. A deployment in an introductory advanced semiconductor packaging course, supplemented by think-aloud sessions and focus groups, further contextualizes these findings. Together, these results suggest how MR+AI systems can be purposefully orchestrated to target complementary knowledge types and inform the design of future microelectronics curricula and other complex STEM domains requiring conceptual, procedural, and spatial reasoning.

Recent advancements in photogrammetry and 3D LiDAR scanners have led to a noticeable increase in the creation of 3D scans of museum artifacts. This trend has opened up new possibilities for museums to create interactive and immersive experiences using virtual reality (VR). In collaboration with the Florida Natural History Museum, we have developed an interactive VR game that utilizes the extensive 3D digital collection of the Florida Museum. The goal is to enhance the traditional museum experience by immersing visitors in dynamic VR environments that showcase 3D museum collections within context. Specifically, our VR game highlights 3D scans of endangered species of underwater creatures in the ocean. Children can swim alongside these sea creatures while an AI conversational agent provides scientific insights. Our VR game was showcased to the public at the Florida Natural History Museum during a public outreach event, attracting visits from three K-12 school trips. We conducted field observations to evaluate children’s interactions with the VR game and conducted semi-structured interviews with children’s guardians as well as museum staff. The findings from our observations emphasized the importance of shared experiences among visitors, which could be facilitated by projecting the VR gameplay on a large screen to mitigate the isolated nature of the HMD VR experience limitations. Additionally, museum staff emphasized the significance of considering visitor traffic when designing VR experiences in museum settings. The findings also highlighted a preference for seated experiences over standing ones due to safety concerns related to children colliding with others and museum artifacts. This paper provides an overview of our design process and the challenges of implementing HMD VR in museum settings, offering valuable insights for future endeavors aimed at designing public VR educational experiences targeting children.

Background: The United States has made substantial investments to restore the global competitiveness of the semiconductor industry; however, the nation continues to face a shortage of skilled labor in this sector. Despite the importance of this issue, there is limited research examining the barriers in individuals' educational and career choices in the semiconductor industry. To address this gap, our study aims to identify the contextual and psychological factors influencing decisions to pursue academic degrees and careers in semiconductors, using expectancy-value theory as our theoretical framework. Method: We first conducted interviews with engineering students and industry professionals in the semiconductor field to explore potential motivators and barriers. Thematic analysis of the interviews revealed multiple factors related to the utility, cost, and interest value. Based on these findings, we designed a survey and gathered responses from 178 participants, including students, faculty, and industry professionals in the semiconductor field. Findings: The results indicated that utility value (e.g., financial stability) plays a significant role in career aspirations for both industry professionals and students. When making career choices in semiconductors, its relative cost value compared to software engineering (e.g., lower pay, limited remote working) also played an important role. This suggests that semiconductor companies are competing not only with other semiconductor companies but also with other big tech companies, necessitating the provision of a comparable work environment to attract skilled engineers. Furthermore, both students and faculty identified limited lab activities and online resources as major barriers, highlighting the need to enhance accessibility to learning materials. Contribution: This study examines the varied perspectives of students, faculty, and industry professionals concerning the essential factors influencing career aspirations in the semiconductor field. To accomplish this, a survey questionnaire tailored to semiconductor career aspirations was developed, drawing insights from interviews with students and industry experts. The findings provide valuable insights for educational and industry approaches aimed at fostering the future workforce in the semiconductor industry.