Explore and create: Exploratory Creation lab 
Preregistration Required
Purpose:
The primary purpose of this session is to empower educators with the knowledge and skills to integrate generative AI tools effectively in educational settings, addressing the challenges posed by the dynamic nature of the educational landscape. The session aims to provide practical strategies for adapting assignments to maintain academic integrity and for leveraging AI as a collaborative partner in science writing and other learning activities.
Objectives (Participant Outcomes):
By the end of the session, participants will:
-->Understand the role and potential of generative AI tools in education, specifically focusing on ChatGPT.
-->Apply practical strategies to adapt existing assignments, making them more AI-proof to maintain academic integrity.
-->Leverage AI as a collaborator to enhance science writing and create enriched learning experiences.
-->Design and develop their own AI-adapted assignments and learning activities using the P.R.O.M.P.T. framework.
-->Share and reflect on their creations, gaining insights from the diverse perspectives of their peers.
-->Increase participants knowledge of the role of A.I. in science education, including benefits and potential pitfalls, including bias and misinformation.
Educational Challenge:
The dynamic and evolving nature of education, intensified by the rapid advancement of technology, poses challenges in maintaining academic integrity and in creating enriched and authentic learning experiences. The integration of AI in education necessitates innovative approaches to assignment design and instructional strategies.
Technology Intervention:
ChatGPT: A generative AI tool that can be used as a collaborative partner in science writing and other learning activities. It is the focal technology intervention in this session, providing a practical example of AI integration in education.
Models Employed:
P.R.O.M.P.T. Framework: A structured approach to designing assignments and learning activities, ensuring clarity, purpose, logical organization, and effective integration of AI tools.
Lesson Plans or Instructional Activities/Strategies:
-->Decision Tree for Using AI: A logical flowchart to guide educators in determining the appropriateness of AI integration in specific learning activities.
-->Interactive Design Lab: A hands-on activity where participants will create their own AI-adapted assignment, applying learned strategies and the P.R.O.M.P.T. framework.
-->Group Reflection and Sharing: An opportunity for participants to share their creations and gain insights from their peers, fostering collaborative learning and diverse perspectives.
Evidence of Success:
Success will be evidenced by participants’ ability to effectively design and develop AI-adapted assignments and learning activities, applying the strategies and models learned during the session. The interactive and collaborative nature of the session will facilitate immediate application and reflection, allowing participants to leave with tangible products and actionable insights that can be implemented in their educational settings to enhance learning experiences and outcomes.
0:00-0:05 (5 mins)
Introductions
-->Welcome and Overview of the Workshop
-->Brief Introduction of Presenters
--> Overview of Workshop Goals and Objectives
0:05-0:15 (10 mins): Decision Tree & P.R.O.M.P.T. Framework
-->Introduction to the Decision Tree for Using AI
-->Detailed Walkthrough of P.R.O.M.P.T.:
Purpose: Identifying the reason for the prompt.
Role: Assigning a role to AI (mentor, debate partner, expert, etc.).
Organize: Structuring the prompt logically and clearly.
Model: Specifying the form and giving examples of desired content.
Parameters: Defining the scope, boundaries, and specifying the data set.
Tweak: Proofreading, prompting, editing, and re-prompting.
0:15-0:25 (10 mins)
Examples of adapting assignments & AI collaboration
-->Demonstrating adaptation of a current assignment to be more AI-proof
-->Illustrating AI as a collaborator: Editing an Abstract for Lab Work
0:25-0:50 (25 mins): Participant Activity
Participants Create Their Own AI-Adapted Assignments
-->Application of the P.R.O.M.P.T. Framework
-->Hands-on Experience with AI Tools
-->Sharing Out to Tables
0:50-0:55 (5 mins)
Sharing Successes
-->Presenters Highlighting Successes in the Room
-->Recognition of Innovative and Effective Assignments
0:55-1:00 (5 mins)
Closure
-->Recapitulation of key learnings
-->Encouragement for continued exploration and implementation of AI tools
-->Thanking participants for their engagement and contributions
This structured timeline ensures a balanced approach, allowing participants to understand, apply, and reflect on the integration of AI in educational settings, fostering a collaborative and innovative learning environment.
Books:
Teaching AI: Exploring New Frontiers for Learning by Michelle Zimmerman
AMAZON LINK: https://www.amazon.com/Teaching-AI-Exploring-Frontiers-Learning/dp/1564847055
The A.I. Classroom by Dan Fitzpatrick, Amanda Fox, Brad Weinstein
AMAZON LINK: https://www.amazon.com/Classroom-Artificial-Intelligence-Education-Hitchhikers-ebook/dp/B0BVGV8GST
External Links:
P.R.O.M.P.T. Framework and A.I. Decision Tree:
https://docs.google.com/document/d/11aVAf1DlO-VIXY32WzM8xo0iyYM8iDV-omNvLkMi8kA/edit?usp=sharing
Poorvu Center of Teaching and Learning at Yale University - A.I. Guidance:
https://poorvucenter.yale.edu/AIguidance
Link to references, inspirations, and tools (Google Doc) in an organized format:
https://docs.google.com/document/d/1wY5jX-Nj3i8dtrSPjiFc1CwZ3-VzWj0W_RE0hhnHHwQ/edit?usp=sharing
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