Chinese

This introductory semiconductor course is specifically designed for interdisciplinary learners. Leveraging professors from STEM (engineering, science, engineering, electrical engineering, and computer science) backgrounds, the course utilizes unit-based thematic teaching to help students understand semiconductor terminology, principles, and forward-looking applications, while also developing their ability to plan for further learning. The course features a holistic overview and does not emphasize related mathematical theories; therefore, it also serves as a general introductory course in contemporary materials science, suitable for students of all backgrounds and academic levels (including graduate students) interested in semiconductor technology. As an introductory course for interdisciplinary learners, this course first provides an overview of the current semiconductor world and how self-learners can modularly understand semiconductor technology. It then explores forward-looking chip applications and AI development to help students understand the importance of semiconductors for future societal development and even human civilization, and why undergraduate and graduate students should study semiconductor general knowledge. The course then progresses through basic solid-state physics and chemistry, materials and components, process equipment, and smart manufacturing modules, concluding with a comprehensive reflection on chip globalization and AI development. There are no exams for this course. Students  integrate the knowledge they have acquired and explore a personalized learning map by submitting handwritten study notes, group discussion assignments, and final forum poster activities.

This course focuses on discussing the changes in the "daily life experiences" of ordinary people within the People's Republic of China and the corresponding historical development and writing strategies. The focus is on re-examining the historical development of the People's Republic of China from the perspective of "ordinary people".

This course introduces the main concepts and theories of classroom management. It begins with an educational philosophy perspective to help prospective teachers reflect on the essential meaning of classroom management. This course helps establish a concept of classroom management, so as to benefit students when dealing with the issues arising from the interactions between teachers, students and parents that they will directly face in the teaching field. In the "Teacher Professional Development Assessment" currently implemented by the Ministry of Education in primary and secondary schools, classroom management indicators account for a significant proportion (6-1. Creating a positive and interactive classroom atmosphere, 6-2. Creating a safe and conducive learning environment, 6-3. Establishing classroom routines that facilitate student learning, etc.). Each sub-indicator emphasizes classroom vision, routines, cohesion, positive communication, learning environment, handling unexpected events, and the ability to provide respectful and differentiated guidance.

This course begins with an overview of the definition of personality and the primary research methods used in personality psychology. It systematically introduces major theoretical perspectives, including psychoanalytic approaches, phenomenological and humanistic theories, trait theories, and contemporary social-cognitive, cultural, and neurobiological perspectives. Across different course units, the instructor incorporates recent data science and neuroscience research related to personality, drawing in part from the instructor’s own ongoing work in these areas. In the research project component, students engage in collaborative interactions with AI tools (LLMs). Through this process, students not only learn how to use AI to deepen their understanding of theoretical frameworks, but also enhance their creativity and competence in applying personality theories to empirical research.

This course begins with an introduction to the evolution of computers and their operating principles. It then gradually guides students to become familiar with programming structures and application design processes, including: basic syntax, flow control, exception handling, input/output, and classes. The course topics are as follows: Introduction Python Basics Flow Control Functions Sequence, Dictionary, and Set Array-Oriented Programming with NumPy File, and Exception Object-Oriented Programming.

This course introduces the fundamental theory of linear algebra and its applications in the field of agronomy. It is designed for students with limited mathematical background who wish to apply linear algebra to practical problems. The course covers essential concepts such as matrices and systems of linear equations, vector spaces, and eigenvalues and eigenvectors. Through the use of applied examples and case studies, students learn how to use linear algebraic methods to analyze and solve real-world problems.