Enhancing Understanding of University Basic Science Courses Through Deep Learning Techniques: With an Emphasis on the Specialized Language of Chemistry and Related Courses

This research investigates the implementation of deep learning techniques to enhance comprehension of university-level chemistry courses, with a specific emphasis on general and organic chemistry. By employing cutting-edge technologies such as artificial intelligence and interactive simulations, personalized learning experiences are developed that cater to individual student requirements and knowledge gaps. The study underscores various methodologies, including AI-driven educational platforms, virtual laboratories, and collaborative initiatives, which promote active participation and critical analysis. These novel approaches facilitate a more profound understanding of intricate chemical concepts and improve practical skills through real-world applications. The results indicate that the integration of educational resources like Coursera and Labster significantly boosts academic performance and knowledge retention, while also fostering collaborative learning environments. Furthermore, the research highlights the significance of ongoing feedback mechanisms in recognizing misconceptions and promoting a growth-oriented mindset among students. Ultimately, the incorporation of deep learning techniques not only equips students for future scientific challenges but also enables them to link theoretical concepts with practical applications, nurturing a new generation of skilled problem solvers in the domain of chemistry.

کلیدواژه ها:

Deep Learning ، Chemistry Education ، Personalized Learning ، Virtual Simulations ، Collaborative Learning