Fall 2024 Data Science ASE Supplemental Application

Please submit this form in addition to the application on the Data Science ASE application portal. The supplemental information you provide here will give us a better picture of your background and interests. This will help us create wonderful ASE teams for each Data Science class.


Please note that if you have P grades in courses relevant to your application, we might approach your instructors in those courses for additional assessment of your performance.


The priority deadline for submitting the ASE Application and this Supplemental form is on Monday, May 20 at 11:59 PM (PT).

Personal Information

Please complete your personal information so we can sync this form with your ASE application.

(As it appears in the ASE Application)

(As it appears in the ASE Application)

(@berkeley.edu)

(As it appears on CalCentral)

Select
Caret IconCaret symbol

Employment Details

Academic Career*
  • Reader - Data C104 only
  • Undergraduate Course Staff 1 (UCS1)
  • Undergraduate Course Staff 2 (UCS2)

Will you have upper division status by the start of Fall 2024?


Upper division status is defined as 60 semester units completed before Fall 2024 (including in progress units and not including AP or other exam units).

Select
Caret IconCaret symbol

Please select the option that describes your current employment status.


Please note that if you hold another UC appointment it may impact your ASE appointment. Please contact your HR department to determine if/how the appointment will be impacted.

Select
Caret IconCaret symbol

Teaching Experience

In chronological order starting with the most recent, please list all of your experience in the positions below. For each experience listed, include the semester + year, the course, the number of hours/week, and the position. (Ex: Spring 2023: Data 8 20-hr UGSI, Fall 2022: Data 8 8-hr UGSI, Spring 2022: Data 8 8-hr Tutor, Fall 2021: CS 61A AI...)


Positions:

  • Academic Intern (or Lab Assistant)
  • Reader
  • Tutor/UCS1
  • UGSI/UCS2/GSI


If you have no such experience at Berkeley, please enter N/A.

If you have taught outside UC Berkeley, please list your experience. For each experience, please list the program name, semester + year, position, and number of hours worked per week.


If you have no such experience outside of Berkeley, please enter N/A.


Community

Diversity, equity, and inclusion are core values in the Division of Computing, Data Science, and Society. In this section you will be asked to reflect on those values and on experiences that contributed to those reflections. We are not looking for any fixed minimum or maximum length of response. You are welcome to write at whatever length you find most comfortable for responding substantively.

Describe any past experience or background that has made you aware of challenges that might be faced by data science students from populations that you think might be historically underrepresented in STEM fields.

Briefly explain what inclusion means to you, and provide examples of ways to increase inclusion in classroom environments. You can draw examples from your own experience as a student or teacher, or describe your plans for increasing inclusion as a teacher of data science.


Course Preference & Motivation

This section is about why you want to teach and which Data course you most want to teach.


NOTE: Data 198 is for the Foundations Scholars class. The class aims to provide academic and community support for students enrolled in Data 8. Please see the Data Scholars page on our website for more details. If you would like to be considered for ASE positions in Foundations Scholars, please make sure you apply for Data 198 in the Data ASE application portal.

Course Preference*

Among the courses listed below, please pick the one that you would most like to teach. If you have more than one favorite on the list, pick any one from that set. Note that regardless of your choice, your application will be considered for every course and position for which you have applied in the Data ASE portal.

Briefly explain why you want to teach, and in particular why you want to teach the course you picked above. If you have more than one favorite, feel free to mention them in this statement.


Maximum length: 250 words

If you would like to provide information about some of the grades on your transcript, please do so here.


Thank you for applying for the Fall 2024 Data Science ASE team!

We look forward to learning about you and your desire to contribute to the Data Science instructional community!


Note: Please verify your answers before you submit this form. You will not be able to go back and edit your submission afterwards.