| Lectures: | Wednesdays, 3pm - 4:20pm, Rice 017 |
| Instructor: | Roberto Hoyle (roberto.hoyle@oberlin.edu) |
| Office: | King 223C |
| Office Hours: | Tu 15:00 – 17:00, Weds 10:00 – 12:00 or by appointment |
| Phone: | x58424 |
| Prerequisites: | CSCI 150 or consent of the instructor. |
Discussions
Discussions will be held using Piazza. The enrollment link is on Blackboard.
Textbooks
No textbooks are required. All readings are free for download through the Oberlin College network or available on Blackboard. Please do not purchase any papers for reading, as you will not need to.
Mask Policy
The Oberlin Computer Science Department is dedicated to making Computer Science accessible to all students. Because of this, we will be requiring that all students wear masks in our classrooms and lab spaces this semester. By masking, you are not only demonstrating respect and kindness for your classmates, but also making sure that medically at-risk students have a learning experience where they can feel comfortable and safe. Masking will be required for classes, lab periods, drop-in lab helping, and anytime you are using the CS labs or offices. If you have forgotten to bring a mask with you, an instructor can provide you with one.
Course Description
From the Oberlin catalog course description:
In this seminar, we will discuss current Computer Science education research on ways in which the discipline can be made to be more welcoming to all students (especially traditionally under-served populations such as non-male and non-white/asian students), and ways in which the pedagogical burden can be improved so that those who do not have substantial prior experience with computers can learn optimally. Students will be expected to read, critique, and present on current research in CS education. Prerequisites & Notes: Prerequisite: CSCI 150
Course Goals
My goals and objectives for students taking this course are as follows:
- Be comfortable reading primary literature in computer science education
- Understand issues surrounding computer science education, as they apply to diversity and equity
- Make judgments and draw appropriate conclusions based on the quantitative and/or formal analysis of data
- Identify the assumptions within formal reasoning / mathematical methods; assess the reliability, generalizability, and uncertainty of conclusions; recognize the risks of using methods improperly
- Relay results in a manner appropriate to the audience using suitable terminology, symbols, and conventions