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Data Science and AI Academy
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Data Science and AI Education Share Fair

This innovative and engaging fair was designed for university and high school data science instructors, researchers, interest groups passionate about elevating data science education, and Data Science and AI Academy students.

About

This Data Science and AI Education Share Fair revolves around the NC State University Data Science and AI Academy ADAPT (All-campus Data science and AI Project-based Teaching and learning) course design model, a cutting-edge framework for developing and teaching data science. Our goal is to foster a comprehensive understanding and effective implementation of this model across various educational settings.

This event will help you:

  • Discover Innovative Teaching Strategies: Learn how to integrate the ADAPT framework effectively into your data science teaching practices.
  • Focus on Project-Based Learning: Dive deep into the benefits and methodologies of project-based learning in data science courses.
  • Explore Data Science Learning Elements: Gain insights into the essential elements of data science education and how to incorporate them effectively.
  • Promote Workforce Preparedness: Understand the importance of preparing students for a data-driven workforce.

Event Highlights

  • Data Science Project Showcase: See real-world examples of successful data science and AI final projects and witness how the ADAPT model is applied through their work. This event is an excellent opportunity to gather fresh ideas for your courses and observe the framework’s effectiveness.
  • Networking Opportunities: Connect with peers and experts during interactive discussion segments.
  • Actionable Takeaways: Leave with a wealth of knowledge and practical steps to implement in your teaching practice.
  • Post-Event Engagement: Follow-up email containing valuable resources and session recordings to further help with our data science teaching journey.

2025 Agenda

May 9, 2025 12:00 PM- 3:10 PM

This event is virtual.

Zoom Link

12:00 PM- 12:20 PM: Opening Remarks and Event Overview

  • Opening Remarks from Rachel (Ray) Levy, Executive Director, Data Science and AI Academy
  • Event Overview by the DSA postdoctoral cohort: Kelsey Virginia Dufresne, Tom R. Leppard, Jeanne McClure, and Zarifa Zakaria

12:20 PM – 1:15 PM: The History of ADAPT and ADAPT Q & A

  • Overview of the ADAPT model by DSA’s Sunghwan Byun and David Stokes
  • Q & A session moderated by DSA’s Kelsey Virginia Dufresne

1:15 PM- 1:40 PM: Student Presentations Session 1: Workforce Preparedness

See real-world examples of successful data science and AI final projects and witness how the ADAPT model is applied through their work.

  • Presenters: 
    • Justin Huang
    • Mannaka Green
    • Anna Doo 
  • Moderator:
    • Jeanne McClure

1:40 PM – 1:55 PM: Breakout Discussion Session

1:55 PM – 2:05 PM: Break

2:05 PM -2:35 PM: Student Presentations Session 2: 10 Common Learning Elements 

See real-world examples of successful data science and AI final projects and witness how the ADAPT model is applied through their work.

  • Presenters:
    • Soumya Pannala
    • Velma Shang
    • Frances LeMond-Glasser
  • Moderator:
    • Kelsey Virginia Dufresne

2:35 PM – 2:50 PM: Breakout Discussion Session

2:50 PM- 3:00 PM: Closing Remarks

Post-Event Survey and Asynchronous Workshop

Participants will receive a post-event feedback survey via email. We value your feedback and would appreciate it if you could take a few minutes to complete the survey. Your responses will help us enhance future events.

Please look out for an email next week, which will include asynchronous workshop materials, as well as recordings and visuals from the presentations. We believe these resources will be useful for your ongoing and future projects.

Thank you once again for your participation and engagement. We look forward to your feedback and hope to see you at our future events!

2024-2025 Share Fair Archive

2025 Event Recordings and Materials

Opening Remarks, The History of ADAPT, and Group Discussion

Opening Remarks from Rachel (Ray) Levy, Executive Director, Data Science and AI Academy

Event Overview by the DSA postdoctoral cohort: Kelsey Virginia Dufresne, Tom R. Leppard, Jeanne McClure, and Zarifa Zakaria

Overview of the ADAPT model by DSA’s Sunghwan Byun and David Stokes

Q & A session moderated by DSA’s Kelsey Virginia Dufresne

WATCH VIA VIMEO

Student Presentations Session 1: Workforce Preparedness

See real-world examples of successful data science and AI final projects and witness how the ADAPT model is applied through their work.

Presenters: 
Justin Huang
Mannaka Green
Anna Doo 

Moderator:
Jeanne McClure

WATCH VIA VIMEO

Student Presentations Session 2: 10 Common Learning Elements 

See real-world examples of successful data science and AI final projects and witness how the ADAPT model is applied through their work.

Presenters:
Soumya Pannala
Velma Shang
Frances LeMond-Glasser

Moderator:
Kelsey Virginia Dufresne

WATCH VIA VIMEO

Student Poster Presentations

View the detailed poster presentations provided by our 2025 student presenters.

ACCESS 2025 STUDENT POSTERS

The History of ADAPT

View and share a slideshow presentation on the history of the ADAPT model and its implementation.

ACCESS SLIDES

Post-Event Discussion Questions

Host an asynchronous workshop on ADAPT using these discussion questions curated by the DSA National Science Foundation Postdoctoral Cohort.

ACCESS DISCUSSION QUESTIONS

2024 Event Recordings

Welcome & Keynote Speaker

Introduction for the event and Keynote Speaker, Sunghwan Byun, and David Stokes.

WATCH VIA VIMEO

Rapid Fire Presentations

Breakout rooms focused on the 3 parts of the ADAPT Model: Project-Based Learning, the 10 Learning Elements, and Identity-Conscious Choices.

WATCH VIA VIMEO

Student Presentations

Two students provide their perspective about their experience learning via the ADAPT Model.

WATCH VIA VIMEO

Presentations and Guided Activities

Three breakout rooms focused on ways to implement the ADAPT model in the classroom.

WATCH VIA VIMEO

Please cite this work using CC-BY-NC-ND 2022