Responsible Use of AI in Research and Practice Settings: Learning from PK-12

• In Event: Toward Responsible Use of AI in Education Research and Development

Abstract

As the use of generative AI (GenAI) has increased, there has been a growing need for researchers and practitioners to integrate AI and GenAI responsibly in their various contexts. Two areas that our work focuses on are AI Literacy and supporting district leaders in the development of responsible use guidelines for students, educators, administrators, and families. This presentation will highlight the essential components of AI literacy as described in a framework our team developed and as learned from an NSF-funded collaboration, the Responsible Use Policy (RUP) Project, through which we engaged with 10 League of Innovative School Districts.

Both projects sought to understand, from multiple perspectives, the challenges and benefits of incorporating AI and other emerging technologies responsibly into teaching and learning contexts. The AI literacy project drew from grounded theory and critical theory to bring together data and perspectives synthesized from research as well as from teacher leaders (LaRossa, 2005; Freire, 1968). The RUP Project involved participatory design approaches, engaging community members throughout the research and development process (Abma, et al., 2019; Anaissie, Cary, Clifford, Malarkey, & Wise, 2021; Buolamwini, 2023; White & Scott, 2024). Finally, the RUP Project implemented a research-practitioner participatory process (Vaughn & Jacquez, 2020) that centered the knowledge of district leaders, their community, and researchers.

The AI Literacy framework was developed under the guidance of five researchers, two learning designers, and an advisory group consisting of 44 community members including PK-12 practitioners, learners, parents, and researchers. Our Responsible Use working group met monthly over the course of the 2023-24 school year to discuss incorporating emerging technologies into existing policies and focused on discussions of equity, ethics, responsibility, and protecting the school community members. Data sources included:
• Focus groups with district leaders
• Interviews about the integration of AI in learning contexts and empathy interviews (Ruiz, et al.) facilitated by district leaders with various school community members
• Written reviews of drafts of the framework
• Policy and process documents produced via the project

Findings shared in this presentation will include:
• The AI Literacy framework including the three interconnected Modes of Engagement: Understand, Evaluate, and Use
• District leaders’ approaches to working with their community audiences
• Methods of data analysis and insight about how to promote AI literacy and improve/adapt policies for future emerging technologies.
Attendees of this session will learn how the skills and practices that are relevant for learners and educators in the PK-12 context also apply to researchers and practitioners and are relevant and applicable to the research community. Making sense of emerging technologies is an ongoing process as technology evolves and users adapt to those changes. This work can inform researchers and organization-wide responses to AI and also support the adoption of future emerging technologies.

Authors

• Pati Ruiz, Digital Promise

• Julie Neisler, Digital Promise

• Kelly Mills, Digital Promise Global