Pioneering AI Integration in Schools: The University of Florida’s Approach
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This is the third post in a five-part series. You can find all five posts here:
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Need an idea of what AI can do? This post was written by a human from a draft by ChatGPT.
To wrap up the series of featured speakers at the first meeting of the SREB Commission on AI in Education, Nancy Ruzycki, the director of undergraduate laboratories at the University of Florida, talked to the Commission about how the university is working with schools throughout the state to support teachers as they integrate model AI courses and pathways.
An Overview of The AI Program
In 2018, the University of Florida pioneered the Engaged Quality Instruction Through Professional Development Program, an AI Pathway Program designed to align with the state’s AI standards framework, ensuring access to high-quality AI education for students in all areas of the state.
Launched with a $5 million Supporting Effective Educator Development grant from the U.S. Department of Education, the program integrates system thinking and authentic workforce applications to support teachers and improve classroom instruction.
The program achieved significant improvements in teaching practices across 10 Florida school districts despite the challenges posed by COVID-19.
One significant achievement of UF’s program was meeting the What Works Clearinghouse level of statistical change in teacher practice, a first in the history of the Seed Program at the Department of Education. This recognition underscores the effectiveness of UF’s approach in transforming teaching practices, particularly in the fields of inquiry and science.
This holistic approach ensures that AI education is not just about technology but about empowering educators to deliver high-quality instruction for every student. UF started by developing a pedagogical model that combines the principles of system thinking with practical applications.
This model includes both curriculum design — what is taught—and pedagogy — how it is taught. System thinking helps educators understand teaching as a process-oriented field that can be improved with strategic interventions.
The goal was to support teachers in bringing real-world applications into the classroom, ensuring that students not only learn AI concepts but also understand their relevance in today’s workforce.
| EXAMPLE: The “Whales vs. Boats” module teaches students about data science and AI by analyzing whale migration patterns and ship traffic data. This module can be used in science classes to teach statistical analysis and environmental science, demonstrating how AI can solve real-world problems. |
By 2020, the program’s success prompted the state to seek UF’s guidance on implementing the AI standards framework. The collaboration with the state focused on creating a comprehensive plan for AI and data science education, emphasizing the need for robust support systems for teachers.
Designing Programs That Lead to Certification
As the UF team started this work, they reviewed opportunities that existed within career and technical education through Perkins requirements.
As Ruzycki stated, using Perkins and CTE as the launch pad to design AI courses and related curricular resources allows great flexibility within the design process.
“CTE programs are more agile,” Ruzycki said. “Perkins dollars can help fund new programs and will pay for states to develop new programs that are aligned with workforce skills.”
Perkins dollars can help fund new programs and will pay for states to develop new programs that are aligned with workforce skills.
To meet Perkins’s requirements, program designers must show alignment with both in-demand occupations and industry-valued credentials. The UF team conducted a crosswalk between the AI standards and in-demand occupations.
Next, the team focused on certifications and determined that the secondary AI standards could align with Microsoft Azure and Python Level 1 Certifications. By providing these certifications, UF ensures that students gain valuable credentials that can boost their career prospects in AI and related fields.
The initial implementation of AI courses has already yielded positive results. In the Okaloosa district, over 300 eighth-grade students earned Python certifications.
Developing Pathways for AI Education
Creating effective pathways for AI education involves strategic planning and collaboration across various educational levels. In Florida, UF started with high school programs, integrating AI and data science into the CTE framework due to its agility and alignment with workforce needs.
The pathways UF created include both designer and developer levels, catering to a broader range of students.
- Designer Level (Level 2): Open to all students, focusing on AI literacy and general applications. Certifications included Microsoft Azure, which was accessible to ninth graders.
- Developer Level (Level 3): Targeted more advanced skills, including Python programming, data storytelling with SQL and machine learning with tools like TensorFlow and neural networks. These courses aimed to prepare students for specific roles in AI and Data Science.
UF worked closely with technical colleges and community colleges to ensure seamless transitions and alignment of learning objectives through two main initiatives:
- They worked to make sure their frameworks lined up with the programs at these institutes so that the high school data science and AI frameworks flow directly into the colleges’ data science frameworks and into fintech.
- They are now writing clock-hour certificates matching programs their colleges offer, including FIU’s applied AI and robotics and Miami Dade College’s data science and AI and applied artificial intelligence bachelor’s programs.
To support these pathways, UF developed comprehensive curriculum resources and professional development programs, all available for free on platforms like Canvas. The curriculum is designed to be modular, allowing educators to integrate AI concepts into various subjects easily.
Supporting Teachers Through Professional Development
A crucial aspect of UF’s program is the focus on upskilling teachers.
“We believe…that every student needs a high-quality instructor in the classroom. And we have to do that through upskilling because things change and yet teaching has not changed very much,” Ruzycki said, adding, “You can’t introduce any new programs unless you have a way to support teachers. Because this is a new field. How are teachers supposed to know what to teach?”
Every student needs a high-quality instructor in the classroom. And we have to do that through upskilling.
One of the first things the UF team realized during this process was the lack of available resources for teachers to teach AI concepts to students. The few resources that existed were often inadequate.
So, the UF team started the work of creating their own and now have two years’ worth of curriculum to support both AI and data science pathways, which they make free and available on Canvas under a shared license through UF.
Along with curricula, the UF program offers a variety of professional development opportunities for teachers. To start, they asked their pilot districts to help identify teachers who would benefit from upskilling.
From there, they worked to provide free teacher boot camps. They started with three districts in these camps the first year and are currently at 15. Teachers become certified in the Azure program while working through content and pedagogy related to the curriculum.
Then, they created an AI Teacher in Residence program. In a train-the-trainer model, the UF team taught these key teachers about UF’s AI curriculum and program. These trained teachers become AI teachers in residence and can support districts that are starting to implement related AI courses.
The professional development programs are extensive, typically involving around 120 hours of training. UF emphasizes the importance of sustained support, providing coaching and mentorship to teachers throughout their first year of implementation.
This approach ensures that teachers are not only prepared to teach AI concepts but also have the ongoing support needed to adapt and continuously improve their teaching practices.
Exposing Students to AI Careers
UF has also made a commitment to expand awareness of AI careers for all students through various events. These “camp in a box” models provide all the necessary materials and training for districts to run AI camps, ensuring that students in remote or low-resource areas have the opportunity to learn about AI.
These “camp in a box” models provide all the necessary materials and training for districts to run AI camps.
UF also worked with Microsoft to design a pilot middle school program that is aligned with Minecraft, making learning engaging for younger students.
Scaling the Program
A robust program of this nature does not come without costs. The UF program was initially funded in large part by their $5 million grant. However, the UF team worked to secure additional funding sources to expand this valuable work, including state funding, securing additional grants and working through foundations and donors.
Ruzycki encouraged the group to consider a variety of funding sources, including seeking legislative allocations, when attempting to launch similar efforts in other states.
Funding considerations should include the development of curricular resources, training and coaching support for teachers and strategically exposing students to pathway options.
Final Thoughts
This is the end of our five-part series on the first meeting of the SREB Commission on AI in Education. If you haven’t already, make sure to read all the posts in this series for a comprehensive view of our first meeting.
Watch for updates on our second meeting, which will take place in Dallas, Texas, on June 21, and sign up for our AI newsletter to keep up with all of SREB’s upcoming AI resources.