Catalog Description: This is a course for aspiring Academic Interns (AIs). It provides pedagogical training and guidance to students by introducing them to the Big Ideas of Teaching and Learning, and how to put them into practice. The course covers what makes a safe learning environment, how students learn, how to guide students toward mastery, and psychosocial factors that can negatively affect even the best students and best teachers. Class covers both theoretical and practical pedagogical aspects of teaching STEM subjects—specifically Computer Science. An integral feature of the course lies in the weekly AI experience that students perform to practice their teaching skills.

Units: 2-4

Prerequisites: Completion of any DS or CS lower-division course and concurrent participation in the Academic Intern experience in EECS at UC Berkeley.

Formats:
Summer: 4.0-4.0 hours of lecture and 6.0-18.0 hours of fieldwork per week
Spring: 2.0-2.0 hours of lecture and 3.0-9.0 hours of fieldwork per week
Fall: 2.0-2.0 hours of lecture and 3.0-9.0 hours of fieldwork per week

Grading basis: satisfactory

Final exam status: No final exam

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Class Schedule (Fall 2024):
CS 365 – Fr 12:00-13:59, Soda 438 – Christopher Todd Hunn, Justin Yokota

Class Schedule (Spring 2025):
CS 365 – Fr 10:00-11:59, Soda 438 –