The
This content will become publicly available on June 1, 2025
A framework for inclusive AI learning design for diverse learners
As artificial intelligence (AI) becomes more prominent in children’s lives, an increasing number of researchers and practitioners have underscored the importance of integrating AI as learning content in K-12. Despite the recent efforts in developing AI curricula and guiding frameworks in AI education, the educational opportunities
often do not provide equally engaging and inclusive learning experiences for all learners. To promote equality and equity in society and increase competitiveness in the AI workforce, it is essential to broaden participation in AI education. However, a framework that guides teachers and learning designers in designing inclusive learning opportunities tailored for AI education is lacking. Universal Design for Learning (UDL) provides guidelines for making learning more inclusive across disciplines. Based on the principles of UDL, this paper proposes a framework to guide the design of inclusive AI learning. We conducted a systematic literature review to identify AI learning design-related frameworks and synthesized them into our proposed framework, which includes the core component of AI learning content (i.e., five big ideas), anchored by the three UDL principles (the “why,” “what,” and “how” of learning), and six praxes with pedagogical examples of AI instruction. Alongside this, we present an illustrative example of the application of our proposed framework in the context of a middle school AI summer camp. We hope this paper will guide researchers and practitioners in designing more inclusive AI learning experiences.
more »
« less
- Award ID(s):
- 2048480
- NSF-PAR ID:
- 10497838
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Computers and Education: Artificial Intelligence
- Volume:
- 6
- Issue:
- C
- ISSN:
- 2666-920X
- Page Range / eLocation ID:
- 100212
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract Framework for K–12 Science Education (NRC; 2012) placed renewed emphasis on creating equitable science learning opportunities for all learners by engaging in three‐dimensional learning experiences: disciplinary core ideas, crosscutting concepts, and science and engineering practices. Additionally, theFramework calls for a more inclusive approach to science learning that builds upon learners' linguistic practices and funds of knowledge and integrates open‐ended, multimodal approaches to documenting learning throughout the assessment process. To support assessment developers in designing expansiveFramework ‐aligned classroom‐assessment approaches for emergent bilingual learners—learners developing two or more languages—tools are needed to guide design of assessments from their inception. This paper presents a literature‐based framework for science assessment design for emergent bilingual learners that includes components critical to support these learners. We then operationalize the framework into five categories and analyze nine publicly available Next Generation Science Standards sample classroom assessments. The sample tasks allow us to illustrate how those engaged in classroom assessment design might create more expansiveFramework ‐based science classroom assessments appropriate for emergent bilingual learners. -
The demand is growing for a populace that is AI literate; such literacy centers on enabling individuals to evaluate, collaborate with, and effectively use AI. Because the middle school years are a critical time for developing youths’ perceptions and dispositions toward STEM, creating engaging AI learning experiences for middle grades students (ages 11 to 14) is paramount. The need for providing enhanced access to AI learning opportunities is especially pronounced in rural areas, which are typically underserved and underresourced. Inspired by prior research that game design holds significant potential for cultivating student interest and knowledge in computer science, we are designing, developing, and iteratively refining an AI-centered game development environment that infuses AI learning into game design activities. In this work, we review design principles for game design interventions focused on middle grades computer science education and explore how to introduce AI learning experiences into interactive game-design activities. We also discuss results from our initial co-design sessions with middle grades students and teachers in rural communities.more » « less
-
more » « less
Some students with disabilities cannot fully engage in digital learning opportunities because of the inaccessible design of many online courses. In this commentary on policies and administration, I describe how the Universal Design in Higher Education (UDHE) Framework can be used to guide the design of accessible and inclusive online courses and share examples of best practices in applying it. I also present potential roles key stakeholders can play in applying the UDHE Framework. Taking meaningful steps in this regard can improve online learning opportunities by making them accessible to and inclusive of more learners.
-
As artificial intelligence (AI) profoundly reshapes our personal and professional lives, there are growing calls to support pre-college aged youth as they develop capacity to engage critically and productively with AI. While efforts to introduce AI concepts to pre-college aged youth have largely focused on older teens, there is growing recognition of the importance of developing AI literacy among younger children. Today’s youth already encounter and use AI regularly, but they might not yet be aware of its role, limitations, risks, or purpose in a particular encounter, and may not be positioned to question whether it should be doing what it’s doing. In response to this critical moment to develop AI learning experiences that can support children at this age, researchers and learning designers at the University of California’s Lawrence Hall of Science, in collaboration with AI developers at the University of Southern California’s Institute for Creative Technologies, have been iteratively developing and studying a series of interactive learning experiences for public science centers and similar out-of-school settings. The project is funded through a grant by the National Science Foundation and the resulting exhibit, The Virtually Human Experience (VHX), represents one of the first interactive museum exhibits in the United States designed explicitly to support young children and their families in developing understanding of AI. The coordinated experiences in VHX include both digital (computer-based) and non-digital (“unplugged”) activities designed to engage children (ages 7-12) and their families in learning about AI. In this paper, we describe emerging insights from a series of case studies that track small groups of museum visitors (e.g. a parent and two children) as they interact with the exhibit. The case studies reveal opportunities and challenges associated with designing AI learning experiences for young children in a free-choice environment like a public science center. In particular, we focus on three themes emerging from our analyses of case data: 1) relationships between design elements and collaborative discourse within intergenerational groups (i.e., families and other adult-child pairings); 2) relationships between design elements and impromptu visitor experimentation within the exhibit space; and 3) challenges in designing activities with a low threshold for initial engagement such that even the youngest visitors can engage meaningfully with the activity. Findings from this study are directly relevant to support researchers and learning designers engaged in rapidly expanding efforts to develop AI learning opportunities for youth, and are likely to be of interest to a broad range of researchers, designers, and practitioners as society encounters this transformative technology and its applications become increasingly integral to how we live and work.more » « less
-
This paper describes exploratory research that contributes to a more holistic model of professional development (PD) for middle school STEM teachers to support inclusive makerspace classrooms. Despite an increased focus on maker education in K-12 settings, teachers have reported limited support to deliver such instruction, especially with academically diverse learners. This case study examined instructional supports for teachers, including professional development and coaching focused on makerspace classroom activities, as well as structural conditions, the integration of metacognitive learning strategies, positive behavior supports, and Universal Design for Learning (UDL). Analysis of teacher interviews, surveys, and classroom observations revealed that teachers acknowledged the need for ongoing PD and the inclusion of UDL components into their lesson planning.more » « less
