Construction's AI story isn't just about autonomous equipment, computer vision or software that estimates project costs. One University of Florida research project is putting AI somewhere less obvious: inside the classroom.
Rui Liu of the University of Florida's College of Design, Construction and Planning has received a $750,000 National Science Foundation award to develop an AI-supported learning system designed to help construction and engineering students master plan interpretation and spatial reasoning.
The system, called DAISY, is intended to provide students with step-by-step guidance, timely feedback, visual learning support and personalized study aids while reinforcing responsible use of AI.
The NSF says the project is intended to help prepare students for an "AI-augmented workforce" while producing publicly available instructional resources and evidence about how AI can support complex visual-spatial learning.
AI Meets One of Construction's Hardest Skills
Reading construction plans is fundamental to architecture, engineering and construction. But it can also be difficult for students because it requires them to connect information across two-dimensional drawings and three-dimensional representations.
That's where DAISY comes in.
According to the NSF, the system will provide personalized support as students learn construction plan interpretation and estimation. Rather than simply giving students answers, the project is designed around guided learning, visual support and feedback.
The NSF describes the goal as helping students develop skills that are traditionally challenging to teach and learn.
That distinction matters. The project isn't simply using AI as a faster way to deliver information. It is investigating whether AI can provide a more personalized learning environment for a highly visual and technical discipline.
"DAISY" is designed to provide "step-by-step guidance, timely feedback, visual learning support, and personalized study aids" while reinforcing responsible AI use.
The research will also examine how students interact with those AI interventions and whether personalized support actually improves learning outcomes.
A Research Project, Not Just a Classroom Tool
The $750,000 award goes beyond developing a single educational application.
The NSF says the project has four main objectives: develop and evaluate DAISY; create an open-access knowledge base containing construction-specific materials and responsible-AI guidance; develop assessment tools for measuring the effects of AI-assisted learning; and investigate how personalized AI interventions affect student learning.
That makes the project as much about understanding how AI should be used in education as it is about building the technology itself.
Students will use DAISY within undergraduate courses, with researchers evaluating its effects through performance-based assessments, interaction data, surveys and interviews.
The project also plans to make research findings, instructional materials, assessment resources and implementation guidance available through open-source repositories, publications and workshops.
Why Spatial Reasoning Matters
Spatial reasoning is easy to overlook when discussing AI and education.
Yet construction and engineering depend heavily on the ability to understand how information represented on a page translates into physical space.
A student may need to interpret multiple drawings, understand how different views relate to one another and mentally connect two-dimensional plans with three-dimensional structures.
The NSF says DAISY will help students make those connections by providing visual learning support and personalized assistance outside normal class time.
That could make AI particularly useful in fields where students can't simply rely on memorizing information. The challenge is developing a mental model of how physical systems fit together.
The Bigger AI Education Question
The project also raises a broader question for universities.
As AI becomes increasingly capable of explaining concepts, generating examples and providing personalized feedback, the challenge may shift from whether students should use AI to how universities can design AI-supported learning without undermining the skills students are supposed to develop.
The NSF explicitly says the project will reinforce responsible AI use and generate guidance for educators.
That is significant because the value of an AI education tool isn't necessarily measured by how much work it allows a student to avoid. In disciplines such as construction and engineering, the underlying reasoning skills still matter.
DAISY is therefore being positioned as a support system rather than a replacement for learning.
What This Means for Miami
The research has particular relevance for South Florida, where construction remains central to development and where universities and workforce programs are increasingly experimenting with AI.
If DAISY demonstrates that personalized AI support can improve students' ability to interpret plans and develop spatial reasoning skills, the underlying approach could eventually extend beyond the University of Florida.
Miami-area institutions such as Miami Dade College and other technical and workforce-development programs could potentially benefit from similar approaches, particularly in programs connected to construction, engineering and the skilled trades.
For Miami's growing proptech and construction-tech ecosystem, the project also highlights an opportunity beyond the familiar applications of AI.
The next wave of construction technology may not simply automate tasks on the job site. It may help train the people who perform them.
That could matter in a region where development demand remains strong and employers need workers who can combine practical construction knowledge with increasingly digital workflows.
The larger significance of Liu's NSF project is therefore bigger than one AI teaching system. It offers a test of whether artificial intelligence can help universities teach difficult, discipline-specific skills more effectively — without losing the human reasoning those professions ultimately depend on.
Reporting Source: This article builds upon information from the National Science Foundation and adds analysis of what the development means for Miami and South Florida AI.
