AI in Education Accelerator Program

Local Innovations with the Lasalle Network

Welcome to the AI in Education Accelerator Program, where innovation meets impact in transforming education through the power of AI. Our program empowers partner schools and universities to serve as hubs and catalysts for AI-enabled education in their local communities, fostering collaboration with school district superintendents, schools of education, city mayors, policymakers, and stakeholders.

Overview

The AI in Education Accelerator Program brings together educators, researchers, policymakers, and technologists to co-create and implement AI solutions tailored to local educational contexts. By leveraging the expertise and resources of our partner institutions, we aim to drive systemic change and improve learning outcomes for all students.

Key Features

Partnership Hubs: Partner schools and universities serve as hubs for AI innovation, experimentation, and collaboration within their localities.
Co-Creation: Engage with school district superintendents, city mayors, and policymakers to co-create solutions that address local educational challenges.
Capacity Building: Provide training, resources, and support to empower educators and stakeholders to effectively integrate AI into teaching and learning practices.
Research and Evaluation: Conduct research, evaluation, and impact assessment to inform evidence-based decision-making and drive continuous improvement.
Policy Advocacy: Advocate for policies and practices that promote responsible AI adoption, equity, and inclusivity in education at local, regional, and national levels.

Our Approach

At the core of the AI in Education Accelerator Program is a collaborative and participatory approach to innovation and change. We believe in the power of partnerships, co-creation, and collective action to drive meaningful and sustainable impact in education.

Program Components

Partner Schools and Universities: Schools that are early adopters localize learning and implementation. Partner universities co-create next generation curricula and support systems.
Local Collaborations: Explore how we work with school district superintendents, city mayors, and policymakers to address local educational challenges.
Capacity Building Workshops: Discover our training programs, workshops, and resources designed to build educators' and stakeholders' capacity in AI integration.
Research and Evaluation: Explore our research agenda and evaluation framework for assessing the impact of AI in education initiatives.
Policy Advocacy Initiatives: Stay informed about our advocacy efforts and policy recommendations for responsible AI adoption and governance in education.

Partnership Models

Partnership Type

Description

Characteristics

Track 1 - Early Adopter of AI in Schools

Schools that are at the forefront of integrating AI technologies into their learning environments

- Proactive in exploring AI applications in teaching and learning.

- Willingness to experiment with innovative AI tools and approaches.

Track 2 - School-Level Research and Innovation Program

Collaboration between Eduimpact Lab and individual schools to conduct AI research and innovation projects within the school setting.

- Focus on conducting research and experimentation on AI applications tailored to the specific needs of the school community.

- Opportunities for educators and students to engage in hands-on AI projects.

Track 3 - Division/District Center of Excellence for AI in Education

Partnership between a local school, the Eduimpact Lab, and a school district to establish a center dedicated to AI research, innovation, and professional development in education.

-Scale-up approach, impacting multiple schools within a district.

- Provides centralized resources, expertise, and support for AI integration across schools.

- Focus on systemic change and capacity building.

Track 4 - Research and Innovation Partnership with University

University x Eduimpact Lab co-creation initiatives; co-develop AI-powered educational tools, and explore policy implications.

- Leveraging university resources, expertise, and infrastructure to advance AI in education.

- Opportunities for cross-disciplinary collaboration and knowledge exchange.

- Potential for scaling research findings to broader educational contexts.

Track 5 - Ideation and Incubation Partnership

Strengthening the innovation and startup ecosystems at the university and inter-university levels.

- Engagement with school incubators as well as business, entrepreneurship, technology, and education faculty.

- Focus on aligning faculty and student research, curricular outputs, internships, and other resources with startup programs.

- Collaboration on impact investments to support startups.

Track 6 - Education Policy and Governance Lab

Partnership focusing on the intersection of AI, education policy, and governance, aimed at shaping policies and practices to support responsible AI adoption in education.

- Engagement with local schools of governance/public administration, policymakers, education stakeholders, and advocacy groups.

- Focus on developing guidelines, regulations, and ethical frameworks for AI use in education.

- Advocacy for equitable access and inclusion in AI-driven educational systems.

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