Artificial Intelligence
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12265/187
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Item 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 KarimThis 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.Item 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 LibermanThis 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.Item Open Access Emerging Technology Acceptable Use Policy Sample Language(Digital Promise, 2024-09) Ruiz, Pati; Karim, Sana; Armstrong, Amanda LaTasha; Shell, Alison; Singmaster, Heather; Giang, Marci; Liberman, BabeThis presentation includes sample and exemplar GenAI acceptable use policies (R/AUPs) that center responsibility, ethics, and equity.Item Open Access Teaching Partner, Grading Assistant, Substitute Teacher: Three Ways Teachers Positioned an Artificial Intelligence Tool in Writing Instruction(Digital Promise, 2024-09) Hillary Greene Nolan, Ph.D.; Merijke Coenraad, Ph.D.; Viki Young, Ph.D.This study investigates how teachers understand and position AI tools in middle school writing instruction, drawing on 27 teacher interviews collected during a study called Project Topeka that used an interactive argumentative writing platform with AI-generated scores and feedback. Based on the interviews, we generate an initial theoretical framework of how teachers position AI tools — and therefore themselves — in their teaching. We found that some teachers leveraged AI as a “teaching partner” that provided insights to help enhance teaching and learning while remaining central to instruction themselves and interacting with students in numerous ways. Others delegated aspects of assessment and learning to AI as a “grading assistant” to save time and increase efficiency, interacting with students with a slight emphasis on score attainment over skill development. Another group turned instruction over to the AI tool as if it were a “substitute teacher,” interacting minimally with students and placing themselves on the instructional periphery. We describe each approach in detail and discuss implications for teaching practices, teachers’ roles, the profession, and students’ experiences and opportunities.Item 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 WeisgrauTo 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.Item 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 RuizThis 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.Item Open Access Artificial Intelligence and the Future of Teaching and Learning(Digital Promise, 2024-03) Jeremy Roschelle; Judi Fusco; Pati RuizThis 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.Item Open Access Executive Summary: A Look at AI Literacy, and AI and Digital Equity(Digital Promise, 2024-04) Pati Ruiz; Jeremy RoschelleThis 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.Item Open Access Review of Guidance from Seven States on AI in Education(Digital Promise, 2024-02) Jeremy Roschelle, Judi Fusco, Pati RuizAs Artificial Intelligence within education becomes increasingly important, Digital Promise reviewed the guidance documents released by seven states—California, North Carolina, Ohio, Oregon, Virginia, Washington state, and West Virginia—on how to approach artificial intelligence (AI) in education. Throughout this report we summarize the overall themes and considerations that each guidance document covers.Item Open Access Computational Thinking and Artificial Intelligence: The Future of Teaching and Learning(Digital Promise, 2023-09) Pati RuizItem Open Access Exploring ChatGPT and Artificial Intelligence: What do you need to know?(Digital Promise, 2023-08) Judi Fusco; Menko JohnsonItem Open Access Automated Essay Scoring in Middle School Writing: Understanding Key Predictors of Students’ Growth and Comparing Artificial Intelligence- and Teacher-Generated Scores and Feedback(Digital Promise, 2023-08) Hillary Greene Nolan; Mai Chou VangProviding feedback to students in a sustainable way represents a perennial challenge for secondary teachers of writing. Employing artificial intelligence (AI) tools to give students personalized and immediate feedback holds great promise. Project Topeka offered middle school teachers pre-curated teaching materials, foundational texts and videos, essay prompts, and a platform for students to submit and revise essay drafts with AI-generated scores and feedback. We analyze AI-generated writing scores of 3,233 7th- and 8th-grade students in school year 2021-22 and find that students’ growth over time generally was not explained by teachers’ (n=35) experience or self-reported instructional approaches. We also find that students’ growth increased significantly as their baseline score decreased (i.e., a student with the lowest possible baseline grew more than a student with a medium baseline). Lastly, based on an in-person convening of 16 Topeka teachers, we compared their scores and feedback to AI-generated scores and feedback on the same essays, finding that generally the AI tool was more generous, with differences likely driven by teachers’ ability to understand the whole essay’s success better than the AI tool.