Browsing by Author "Pati Ruiz"

Now showing 1 - 7 of 7

Open Access
AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology
(Digital Promise, 2024-06) Kelly Mills; Pati Ruiz; Keun-woo Lee; Merijke Coenraad; Judi Fusco; Jeremy Roschelle; Josh Weisgrau
To enable all who participate in educational settings to leverage AI tools for powerful learning, this paper describes a framework and strategies for educational leaders to design and implement a clear approach to AI literacy for their specific audiences (e.g. learners, teachers, or others) that are safe and effective. The first part of the paper describes a framework that identifies essential components of AI literacy and connects them to existing initiatives that districts have been implementing for decades. The second part of the paper identifies strategies and illustrative examples as guidance for educational leaders to integrate AI literacy in PK–12 education and adapt to their unique contexts.
Open Access
AI-Powered Innovations in Mathematics Teaching & Learning: Initial Findings
(Digital Promise, 2024-09) Sierra Noakes; Alison Shell; Parker Van Nostrand; Alexis M. Murillo; Pati Ruiz; Babe Liberman
This report discusses findings based on responses to a request for information (RFI) led by the Bill & Melinda Gates Foundation and Digital Promise, which received nearly 200 responses that described a variety of innovative approaches to leveraging artificial intelligence (AI) for mathematics teaching and learning. As AI becomes increasingly prevalent in education, three key questions often drive conversations around this emerging technology: What does AI in education look like today; what are the risks to leveraging AI in education and how might those risks be mitigated; and, what should AI’s role be in education? The report shares findings to support both education leaders with decisions about AI as well as providers in learning more about market saturation and strategies to mitigate risks.
Open Access
An Ethical and Equitable Vision of AI in Education: Learning Across 28 Exploratory Projects
(Digital Promise, 2024-10) Sierra Noakes; Alison Shell; Alexis M. Murillo; Parker Van Nostrand; Pati Ruiz; Shayla Cornick; Sana Karim
This report shares the learnings across 28 exploratory projects from teams across K-12 school districts, nonprofits, and nonprofit and for-profit edtech companies, leveraging AI to support numerous goals across K-12 educational settings. Through this report, we aim to highlight the early successes of AI, surface the key barriers that call for cross-disciplinary and collective problem-solving, and consider the potential for each sector to drive forward an equitable future for AI in education. Preliminary findings from these projects show early evidence of AI’s effectiveness in various tasks, including translation, speech recognition, personalization, organizing and summarizing large qualitative datasets, and streamlining tasks to allow teachers more time with their students. However, these projects also experienced challenges with the current capabilities of AI, often leading to resource- and time-intensive processes, as well as difficulties around adoption and implementation. Additionally, many surfaced concerns around the ethical development and use of AI. Through this work, we have seen exciting ways that cross-sector collaborations are taking shape and gained a large sample of examples that emphasize the need for co-design to build meaningful AI-enabled tools. We call on education leaders, educators, students, product developers, nonprofits, and philanthropic organizations to step back from our day-to-day and imagine a revolutionized education system.
Open Access
Artificial Intelligence and the Future of Teaching and Learning
(Digital Promise, 2024-03) Jeremy Roschelle; Judi Fusco; Pati Ruiz
This talk, entitled "Artificial Intelligence and the Future of Teaching and Learning" focuses on AI Literacy, giving background and definitions to give educators a foundation as they bring AI into their practice. Originally presented at the AI K12 Deeper Learning Summit, it frames the discussion of AI in Education in the context of how people learn and considers how AI may change the process. It further considers equity, ethics, bias in AI, and some hidden costs of AI to humans and the environment. Links to resources are given.
Open Access
Computational Thinking and Artificial Intelligence: The Future of Teaching and Learning
(Digital Promise, 2023-09) Pati Ruiz
Open Access
Ethics, Artificial Intelligence, and Digital Equity: Making Informed Decisions about the Integration of AI
(Digital Promise, 2024-03) Jeremy Roschelle; Judi Fusco; Pati Ruiz
This talk, entitled "Ethics, Artificial Intelligence (AI), and Digital Equity: Making Informed Decisions about the Integration of AI" explores the intersection of digital equity, ethics, and artificial intelligence. Originally presented at the AI K12 Deeper Learning Summit, it aims to provide participants with knowledge and resources to make informed decisions regarding the integration of AI systems and tools in their learning context. In an interactive portion, attendees will consider scenarios and learn strategies for ensuring and impact of technology while fostering, responsible and inclusive uses of AI.
Open Access
Executive Summary: A Look at AI Literacy, and AI and Digital Equity
(Digital Promise, 2024-04) Pati Ruiz; Jeremy Roschelle
This one pager summarizes Digital Promise's vision for Artificial Intelligence in education. Digital Promise is focused on AI in education to foster a future where every person engages in sustained and impactful experiences of powerful learning that lead to a life of well-being, fulfillment, and economic mobility.