During this week, you will develop and articulate a professional development plan for how you will contribute to increasing student access to data science education. Your plan should consist of a specific, measurable goal or goals and a detailed action plan for how to get there. Include the learning resources you will use and define the deliverable you will produce. The plan should include a timeline for completion (ideally, this will be completed by the end of the summer). Each individual will submit a draft plan on Thursday morning and present an overview of their plan on Friday.

In addition to your individual plan, each institution will work to develop a short document that describes next steps for their school in terms of data science initiatives. These plans will be shared with the group on Friday.

Background reading

Please read the following:

  1. Fostering and Simplifying Data Science Transfer Pathways in Massachusetts
    Baumer and Horton (2022)
    Read full paper
  2. Report from The Two-Year College Data Science Summit
    Gould, et al. (2018)
    Read Executive Summary and browse full report
  3. Dana Center Data Science Course Framework
    The Charles A. Dana Center at The University of Texas at Austin (2021)
    Read the full paper

Monday: Symposium (see schedule)

Tuesday: Teaching Introductory Data Science

Welcome and introductions (9:00 am)

  • More in-depth introductions
  • Debrief, discuss, and take-aways from the Symposium
  • Overview of the Workshop
  • Return W-9 forms

: Models for introductory data science (9:30 am)

Three different introductory data science courses will be presented. A Q&A and discussion will follow.


Break (10:45 am)

: A day in the life (11:00 am)

Participants can choose to attend a sample class from one of the three courses presented in the morning panel.

Lunch (12:00 pm)

Walk to Jandon Center (Wright Hall) and eat outside (weather permitting) in amphitheater.

: We can work it out (1:15 pm)

Closing discussion (2:30pm)

  • Reflections: what got you excited today?
  • What are your next steps?
  • What additional topics are you interested in learning more about on Thursday?

Wednesday: Inclusive pedagogies for data science

: How we teach (9:00 am)

  • Leaders: Nick and Ben, slides

Pedagogy for data science

  • Active learning
  • Growth mindset
  • Problem solving
  • Authenticity

Break (10:30 am)

: Interactive discussion with Dana Center (10:45 am)

Leaders: Nick and Josh Recio (to appear via Zoom)

Dana Center Design Principles

: Identify topics of interest for Thursday lectures (11:45 am)

Lunch (12:00 pm)

: Discussions of data science program (1:00 pm)

: Developing an institutional plan (2:00 pm)

  • What do the next steps for data science at your institution look like over the next 12-24 months?

Thursday: Developing programs and pathways

: Introduction to GitHub (9:00 am)

Break (10:30 am)

: Professional development plans (10:45 am)

We have created an individual Google Drive folder for your use during and after the workshop. At some point prior to lunch we ask you to upload your draft professional development plan so that they can be reviewed later in the day. We will endeavor to provide feedback on the plans in a timely fashion.

Lunch (12:00 pm)

: Topics in data science (1:00 pm)

TBD based on attendee interest:

  • SQL and importing data into R
  • leaflet and dynamic maps
  • git and GitHub
  • Shiny and dynamic dashboards
  • CRAN and R packages
  • code style

: Work session (2:00 pm)

Friday: Reporting out

: Work session (9:00 am)

  • Prep individual slides

: Revisit five points of friction (10:00 am)

  • Symposium recap

Break (10:30 am)

: Present individual plans (10:45 am)

: Present institutional plans (11:15 am)

: Closing thoughts and survey (11:45 am)

We ask that all participants fill out the following short survey: