151 - 160 of 228 results for: SOC

Prior arrangement required

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

Work in an apprentice-like relationship with faculty on an on-going research project. Prior arrangement required

This course examines the expansion, impact, and organization of higher education across the world. This course engages students with sociological theory and comparative research on global and national sources of influence on higher education developments, e.g. admissions criteria, curricular content, governance structure.. At the end of the course students should be able to compare and contrast developments across countries.

Where do people's political attitudes and behaviors come from, and how can they be changed? Social and psychological factors powerfully influence political views, and research in this area can help to understand our often confusing political landscape. 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. In this class we will read and discuss cutting-edge research from social psychology, sociology, political science, and beyond on topics such as polarization, persuasion, social activism, inequality, racial prejudice, and populism. Enrollment for SOC 298 is by permission of instructor. Apply here: 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.

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.

Educational success is shaped by educational opportunities in and out of formal schooling systems. But the extent to which educational outcomes and inequality are driven by school-based and non-school-based forces remains an open question. Nor do we have clarity on what features of schools and children's non-school experiences are most important in shaping patterns of educational success. In this year-long research lab, students will work together assembling and analyzing data to answer some of these questions. The research projects will draw on several large educational and social databases constructed by the Educational Opportunity Project at Stanford including the Stanford Educational Data Archive (SEDA) and the Segregation Explorer (SegX) (see more at https://edopportunity.org). It will be especially useful for PhD students who would like to conduct research using these data.