171 - 180 of 255 results for: SOC

Work on a project of student's choice under supervision of a faculty member. Prior arrangement required

Where do individuals' political attitudes and behaviors come from, and how can they be changed? In this class we will read and discuss cutting-edge research from social psychology, sociology, and political science on topics such as polarization, persuasion, elitism, social activism, and racial resentment. A central idea of the class is that social and psychological factors powerfully influence political views, and research in this area can help to understand our often confusing political landscape. Additionally, understanding the causal architecture of political attitudes and behavior is essential for taking effective political action, especially in this time of deep and growing political divides. Enrollment for SOC 298 is permission by instructor only. Please complete the following application: https://sshs.qualtrics.com/jfe/form/SV_6lKEHvF817e7GND

Note: for first-year Sociology Doctoral Students only. This class will prepare you to teach Stanford students in your role as a TA or instructor. It rests on the idea that teaching is both an art to learn and cultivate, and a source of great joy and personal meaning during your graduate career and beyond. The course's main goal is to help you become an effective instructor in your day-to-day teaching, covering skills such as how to deliver a powerful lecture, lead an engaging discussion section, build an inclusive classroom, describe your personal pedagogy to others, juggle teaching logistics and competing demands, and make the best use of technology and campus resources. You will also discover that teaching is, above all, a deeply personal process that should take into account the different backgrounds, stories, and learning styles of both students and instructors to enable students to flourish academically and personally. Throughout this class, we will explore different philosophies and ways of teaching so that you can cultivate and employ your own, personalized pedagogy. It is my hope that you will use this course as a springboard to embark on your own teaching journey. With a growth mindset and the right tools in our hands, we can begin to both transform and be transformed by our students: this is the art and joy of teaching.

Social life would be unimaginable without play and games. Students will be introduced to social theories of play and games; the history of games and their variation; readings concerned with how play and games affect interaction and socialization; how race and gender are enacted in and through play and games; how play and games relate to creativity and innovation; and how games can be designed for engrossment and the accomplishment of various tasks and learning goals. Course intended mainly for doctoral students, though master¿s and undergraduate students are welcome. This is a new course, so please expect collaboration with instructor and other students to shape the course content.

Social scientists can benefit greatly from utilizing new data sources like electronic administration records or digital communications, but they require tools and techniques to make sense of their scope and complexity. This course offers the opportunity to understand and apply popular data science techniques regarding data visualization, data reduction and data analysis.

Quantitative data require considerable work before they are ready to be analyzed: they are often messy, incomplete and potentially biased. This course is designed to help you thoughtfully collect, manage, clean and represent data so it can offer substantive information researchers can act upon. In our weekly sessions you will take a critical and reflective approach to these tasks and learn the technical skills needed to get your data into shape. Education and social science datasets will be our focus.

This course centers on the question of how you can use various data science techniques to understand social phenomena. Applied to education and social science topics, the course will introduce you to supervised and unsupervised machine learning algorithms, new data, and provide you the skills to thoughtfully evaluate and assess machine learning performance and implications.