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Generative Artificial Intelligence (GAI), such as OpenAI’s ChatGPT, has rapidly emerged as a transformative tool in higher education, offering opportunities to enhance teaching and learning. This paper describes the design and implementation of ChatGPT-integrated curriculum activities, featuring coding learning in psychology and conceptual discussions in physics, and presents the findings of a year-long experimental study in both types of classrooms. Our findings suggest that students generally found ChatGPT easy to use and beneficial to their learning, reporting improved confidence, motivation, and engagement. However, its ability to address individual needs or replace instructors was viewed less favorably. Comparative analyses showed that coding activities in psychology led to higher levels of activity satisfaction and perceived usefulness of ChatGPT compared to the more abstract discussion activities in physics. While graduate students were more enthusiastic about using ChatGPT for skill acquisition than undergraduates, demographic factors such as gender, race, and first-generation college status showed no significant influence on such perceptions. Meanwhile, instructors’ reflections emphasize the importance of thoughtful integration, technical support, and pedagogical balance to maximize GAI’s potential while mitigating its limitations. Recommendations for integrating GAI into teaching practices and future research directions are discussed, contributing to the evolving discourse on GAI’s role in transforming modern classrooms. 

Analyzing the kinetics of biological processes plays a significant role in understanding fundamental cellular functions. Many physics-based technologies used to study such processes are limited by the shot noise inherent to the coherent states of light. These technologies can greatly benefit from leveraging quantum probes to improve the sensitivity of measurements in cellular biology. The surface plasmon resonance technique has been used effectively to achieve label-free, real-time measurements of protein binding kinetics, which constitutes an important biological phenomenon occurring near the cell membrane. Here, we demonstrate the integration of this technique with the two-mode bright squeezed state having fewer fluctuations as compared to the coherent state to improve the sensitivity of measurement in studying a protein-gold adsorption process. We show 4 dB of squeezing as we record the signal-to-noise ratio as the function of time, and it is maintained throughout the kinetic process. The improved signal-to-noise ratio leads to a $60\%$improvement in the sensitivity of measuring the observable rate constant $k_s$. The quantum advantage as shown in terms of squeezing is achieved despite the total absorption of $74\%$from the source until the final detection after the sensor. Overall, we provide the most practical setup for improving the sensitivity of the time-dependent measurements involved in various biological processes at the molecular level.