Tutor Apprenticeship in Data Science 🧑🏫
DSC 95, Fall 2024 at UC San Diego
Class: Mondays (so far), 1-1:50PM, CENTER 222
Table of contents
Schedule
Note: This is a discussion-heavy course, and it’s hard to predict how long some discussions may take. As such, the schedule below is likely to change quite a bit throughout the quarter.
Deadlines will appear with a ✅, and all deadlines are subject to change.
Week | Class | Action Items |
---|---|---|
1 September 30th | Introduction, Responsibilities, Imposter Syndrome | Read:
Complete the Welcome Survey by ✅ Wed (October 2nd), 11:59pm. |
2 October 2nd | Professionalism and Office Hours | Watch Learning Styles Don't Exist. Find an experienced tutor in the class you are tutoring for and “shadow” them (i.e. follow them around and observe them) during their office hours for at least 30 minutes. Preferably choose a time that will be busier, e.g. the day that homework is due. Then, answer reflection questions on Gradescope by ✅ Wednesday, October 9th. |
3 October 4th | Grading, Productivity Tips | HW: Read the three readings, submit two questions for the tutor panel and complete the sample grading assignment here by ✅ Questions by Sunday, Grading by Wed; grading by Friday 11.. |
4 October 7th | Tutor Panel. | |
5 October 9th | Finish Scenarios, Start Grading | HW: Complete tutor shadowing, start grading |
6 October 11th | Finish Grading, Productivity tips | HW: Read the reading and the draft of the project: here by ✅ Must be done by Sunday, 11:59pm. |
8 October 16th | Students are stuck. Academic Integrity. | HW: Read the reading and the draft of the project: here by ✅ Must be done by Friday, 8:00am. |
9 October 18th | Students are stuck. Academic Integrity. </td> |
For discussion, we will use Slack, and you will submit any assignments (that aren’t Google Forms) to Gradescope. Let Marina know if you can’t access one of those platforms.
About
DSC 95 is a 2-unit, P/NP discussion-based course that is required of all first-time DSC tutors. The course is designed to guide new DSC tutors through their first quarter as a tutor. The specific topics we will cover are in the Schedule above.
Note that the class is not lecture based. We tell our students that the best way to learn concepts in data science is by doing data science, whether that’s actually writing pandas
code or practicing runtime analysis problems. Likewise, the best way to learn how to teach data science is to actually teach data science, which you will get practice with in office hours and on your class’ discussion board. DSC 95 provides you with a forum to reflect on your teaching with a group of students who are also at the start of their teaching journeys.
There is exactly one goal in this class, and that is to get you to think very carefully about your teaching, to consider different scenarios that might arise (and how to deal with them), and to get you to genuinely enjoy teaching! (Okay, that was actually three goals, but they’re basically the same thing in my mind.) - Victor Huang, CS 375 @ Berkeley
People
Instructor
Marina Langloisshe/her/hers
malanglois@ucsd you know the rest
Hi, I am Marina and I am originally from Russia (not France!). I moved to Chicago to continue my education and I earned my PhD in Computer Science from UIC. Then I worked at Yeshiva University, NYC and then moved to San Diego. I was a member of CS department at first but moved to Data Science and I am loving it! I am excited to be your instructor for this quarter and you are welcome to stop by just to chat :)
Fun fact: I play ping pong!💃
Tutor
Anastasiya Markovashe/her
Tutor
Nicole Zhangshe/her
Remember that dsc-courses.github.io contains links to course websites of several DSC courses.
Requirements
DSC 95 is graded P/NP. There are three things you need to do to pass:
- Attend and participate in all DSC 95 class sessions.
- This is a discussion-based class, so attendance and participation are mandatory. (How can you expect your students to be engaged if you’re not? 😉)
- If you need to miss a DSC 95 class session for any reason (e.g. if you’re sick or have a conflicting exam), let Marina know in advance on Slack.
- Note that lecture attendance for the class you’re tutoring for is not a requirement of DSC 95; your instructor may still require you to attend as part of your paid tutor duties.
- Complete weekly readings and homework assignments, TBD at 11:59PM.
- Each week, we will provide you with readings and tasks to complete that should help you reflect on your time as a tutor so far. These will all be posted in the above Schedule.
- Responses are graded on a 2/1/0 scale:
- 2: Thoughtful and complete.
- 1: Lack of effort.
- 0: Not submitted.
- Since the readings and homeworks are short (~1 hour per week), there are no slip days or extensions. We need your responses in no later than Tuesday night so that we can plan the next day’s class session.
- You can miss at most 1 weekly assignment and still pass.
- Complete a satisfactory Final Activity.
- More details to come.
Useful Information
Here’s an assortment of information that will be useful the first time you tutor.
Payment
To get paid for your tutoring hours, submit your hours biweekly into Ecotime.
- Resources for using Ecotime can be found here; a quick guide (that is also linked on this site) can be found here.
- Instructions for setting up Direct Deposit can be found here. Note that you must set up your UC Path account to access the Direct Deposit page. Follow this guide for accessing UC Path for the first time.
- The payroll calendar can be found here; it describes when timesheets are due and when you’ll be paid.
Outside Tutoring
As a tutor, you are not permitted to approach students to offer services of any kind in exchange for pay, including tutoring services. This is considered solicitation for business and is strictly prohibited by University policy.
On a related note, as a tutor, you should only help students in your course through official channels (e.g. office hours or Ed). You may be friends with some of your students and have them on social media, but they should not message you on social media with questions about the course. All students should have equal access to course staff – your friends shouldn’t have an unfair advantage just because you happen to be a tutor.
Acknowledgements
The content of DSC 95 has evolved over the years, thanks to the contributions of many individuals. Special recognition goes to:
- Christine Alvarado and Mia Minnes (CSE Department), who originally developed content through CSE 95.
- Victor Huang, whose work in CS 375 at Berkeley served as an inspiration.
- Suraj Rampure, who made significant improvements to the course.
- Colin Jemmott, who also contributed to the course’s development.
We extend our gratitude to all those who have played a role in shaping this course into what it is today.