> [!summary]+ Summary > This page explains a workshop designed to give definition and meaning to potential learning partnerships with generative Artificial Intelligence (genAI). While examples were student use, such partnership can apply to anyone seeking to learn for courses, professional development, or simple curiosity. (See the bottom of this page for the results of this workshop.) # Types of Learning Partnership with genAI **Delivery details:** <u>Date</u>: Spring 2024 and Fall 2024 <u>Target audience</u>: University faculty, staff, and students <u>Delivery format</u>: Remote/Zoom <u>Duration</u>: 60 minutes ## About the workshop This workshop dived into tackling the potential for human-AI partnership in learning. In articles by Dell'Acqua et al. (2023), Mollick and Mollick (2023), and Hwang and Chen (2003), researcher addressed potential partnerships with AI. While studying business consultants using AI/LLMs in their work, Dell'Acqua (2023) identified 2 models of behavior they called **centaur** and **cyborg**. **Centaurs** applied the technology to specific tasks, and **cyborgs** applied the technology to all tasks. More specific to AI/LLM use in learning, Mollick and Mollick (2023) identified 7 roles: 1) mentor, 2) tutor, 3) coach, 4) teammate, 5) student, 6) simulator, and 7) tool. These relationships were the basis for this workshop. The workshop laid some foundations for kinds of AI, general partnerships, and areas of caution using it. Some insight was then provided from a survey I conducted with colleagues of undergraduate economics students and their use of genAI in December 2023 at George Washington University (GWU). From there, examples were provided of what learning partnership may look like with genAI. ### Description > In this workshop, we will demonstrate strategies that you may direct students towards in partnership with generative Artificial Intelligence (genAI). We will go over some fundamentals of human-AI partnership, highlight different types of learning (human-AI) partnership, and link them with real-world learning opportunities so you may imagine genAI used from both teaching and learning perspectives. This session aims to enable educators with knowledge of working in partnership with genAI in order to integrate it into pedagogy, thereby helping learners gain valuable practice using this technology. This workshop is introductory, some experience working with genAI tools (e.g ChatGPT) is useful but is not required. ### Learning objectives 1. Define the evolving working relationship between humans and generative Artificial Intelligence (genAI). 2. Outline types of teaching and learning partnerships found in the literature. 3. Provide strategies for leveraging genAI in pedagogy in addition to example prompts. ### Workshop goal **The goal was for participants to learn about and see in action what learning partnership may be for students with genAI.** The intent was to give some definition to partnership from research and to provide some ways to explore supporting these partnerships. ## Slide deck <div class="container"><iframe class="responsive-iframe-sd" src="https://1drv.ms/b/c/13829E5D2EB238DE/IQRF-km4Nm8gQYYYSaPjyQTdAYIotNVkpGTkutChEPgP3Y4" width="100%" height="400" frameborder="0" scrolling="no"></iframe></div> *Note: These slides were built with a custom slide deck that I made using Microsoft PowerPoint. Generative Artificial Intelligence (genAI) was used to create a comparison image on slide 8. Avatar and computer icons were created by [Leah Sims](https://www.leahsims.net/about). All stock images were provided by [Adobe Stock](https://stock.adobe.com) and [Getty Images](https://www.gettyimages.com).* ## 🎯 Results This workshop gave participants a solid sense of genAI as a partner in learning and work. Participants reported that the Mollick and Mollick (2023) framework gave them starting point imagining partnership and enjoyed the practice. This workshop led to many faculty consultations. ## Resources - Dell'Acqua, F., McFowland, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., ... & Lakhani, K. R. (2023). Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper, (24-013). URL: [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4573321](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4573321) - Hwang, G-J., Chen N-S. *Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions*. Educational Technology and Society. 26, 2. April 2023. URL: [https://doi.org/10/30191/ETS.202304_26(2).0014](https://doi.org/10.30191/ETS.202304_26(2).0014) - Mollick, E. R. and Mollick, L. *Assigning AI: Seven Approaches for Students, with Prompts* (September 23, 2023). The Wharton School Research Paper, Available at SSRN: [https://ssrn.com/abstract=4475995](https://ssrn.com/abstract=4475995) or [http://dx.doi.org/10.2139/ssrn.4475995](https://dx.doi.org/10.2139/ssrn.4475995) - Mollick, E. *[Centaurs and Cyborgs on the Jagged Frontier](https://www.oneusefulthing.org/p/centaurs-and-cyborgs-on-the-jagged).* One Useful Thing. September 16, 2023. - Mollick, E. *[I, Cyborg: Using Co-Intelligence](https://www.oneusefulthing.org/p/i-cyborg-using-co-intelligence).* One Useful Thing. March 14, 2024. - **Torres, J.**, Foster, I., & Dinneen, P. (2024). *genAI Undergraduate Student Survey (Pilot)*. Presented to George Washington University Faculty Senate on January 19, 2024. See page: [[2023, Undergrad genAI survey]]