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How do we design artificial systems that learn as we do early in life -- as "scientists in the crib" who explore and experiment with our surroundings? How do we make AI "curious" so that it explores without explicit external feedback? Topics draw from cognitive science (intuitive physics and psychology, developmental differences), computational theory (active learning, optimal experiment design), and AI practice (self-supervised learning, deep reinforcement learning). Students present readings and complete both an introductory computational project (e.g. train a neural network on a self-supervised task) and a deeper-dive project in either cognitive science (e.g. design a novel human subject experiment) or AI (e.g. implement and test a curiosity variant in an RL environment). Prerequisites: python familiarity and practical data science (e.g. sklearn or R).

This is an ongoing workshop and reading group for students and faculty engaged in research in higher education. Topics include but are not limited to postsecondary access; late adolescent and college student development; adult and lifelong learning; teaching and learning in postsecondary settings; leadership and management; federal, state, and institutional policy; student and organizational culture; and finance and economics. The focus of the workshop is to provide a faculty led community of support for students, faculty, and others conducting research on higher education. Accordingly, the schedule of topics each quarter will be determined by participants in the workshop to flexibly focus on current research papers and projects. The workshop will provide a space for participants to present research ideas, workshop conceptual and methodological issues, give and receive feedback on conference paper proposals and drafts, and engage in focused discussion of papers and studies relevant to their work. It is open to master's and doctoral students, and with instructor approval, undergraduates working on theses and senior papers.

Is Artificial Intelligence really disrupting the EdTech industry or do its business impacts remain elusive? Despite booming interest around AI, concrete examples of how this is actually changing the way EdTech businesses operate remain scant. In this course, students will have the opportunity to engage with EdTech entrepreneurs, board members and venture capitalists around real business cases that illustrate the opportunities and challenges linked to incorporating AI into their product when it comes to driving sales, market share, and profitability.

Skills for developing a positive classroom learning environment. Theoretical issues and opportunities to acquire strategies and make links with practice teaching class. STEP elementary only.

This seminar will explore the impact and relative salience of racial/ethnic identity on select issues including: discrimination, social justice, mental health and academic performance. Theoretical perspectives on identity development will be reviewed, along with research on other social identity variables, such as social class, gender and regional identifications. New areas within this field such as the complexity of multiracial identity status and intersectional invisibility will also be discussed. Though the class will be rooted in psychology and psychological models of identity formation, no prior exposure to psychology is assumed and other disciplines-including cultural studies, feminist studies, and literature-will be incorporated into the course materials. Students will work with community partners to better understand the nuances of racial and ethnic identity development in different contexts. (Cardinal Course certified by the Haas Center)

Preparation and practice in issues and strategies for teaching in classrooms with diverse students. Topics: instruction, curricular planning, classroom interaction processes, portfolio development, teacher professionalism, patterns of school organization, teaching contexts, and government educational policy. Classroom observation and student teaching with accompanying seminars during each quarter of STEP year. Prerequisite: STEP student.

Integrating theory and practice in teacher development. Topics include: equity, democracy, and social justice in the context of teaching and learning; teacher reflection, inquiry, and research; parent/teacher relationships; youth development and community engagement; professional growth and development; teacher leadership and school change processes; preparation for the job search, the STEP Elementary Portfolio, and the STEP Elementary Conference. Prerequisite: STEP student.

This course will cover the material from EDUC 252 in an applied setting. Emphasis will be in developing a capacity for applying and interpreting psychometrics techniques to real-world and simulated data.

Digital Learning Design Workshop is a project-based course offered in Fall and Winter Quarters that students can take as part of the Digital Learning Initiative's Student Accelerator. In hands-on workshops, led by prominent academic and industry experts, students will define specific learning problems, recruit teammates, develop an approach to learning and community building using digital technology, create prototypes, test them with target learners, and progressively refine them for potential entry in the Digital Learning Design Challenge.