
In Professor of Economics Ting Zhang's graduate economics class at the Merrick School of Business at the University of Baltimore, students aren't just reading about supply and demand curves—they're manipulating them in real-time, watching market equilibria shift as they adjust variables, and receiving instant feedback from AI-powered study companions that understand the nuances of managerial economics.
This transformation is the result of a collaboration between Dr. Zhang and Ranjith Keerikkattil, an MBA student whose technical expertise has helped build an ecosystem of AI-powered learning tools for ECON 606: Managerial Economics. Together, they've created what may be a model for how artificial intelligence can enhance—rather than replace—the educational experience.
Graduate economics education presents unique challenges. Students must master abstract reasoning through economic models that simplify complex systems. Only relying on lecture-based instruction often struggles to convey these dynamic concepts effectively. Static diagrams in textbooks show a supply curve, a demand curve, and an equilibrium point—but they don't show how these elements interact dynamically.
The question that drove this initiative was straightforward: What if students could see economic concepts in motion? What if they could manipulate variables and observe consequences in real-time? What if AI could provide personalized explanations grounded in their actual course materials?
The centerpiece of the initiative is the ECON 606 Study Bot, deployed on BoodleBox—the leading collaborative AI platform built specifically for higher education. The system coordinates a team of specialized AI agents, each optimized for specific tasks:
This multi-agent approach ensures that each task is handled by the model best suited for it, while the orchestration layer maintains consistency and academic rigor across all outputs.
Perhaps the most transformative component is the EconSim Interactive Simulator—a comprehensive platform featuring 78 interactive modules that bring abstract economic concepts to life. The platform integrates live data from FRED (Federal Reserve Economic Data), connecting classroom theory to real-world economic conditions. A comprehensive Student Guide provides learning objectives, step-by-step instructions, and textbook connections for each module, from the course teaching materials. Together, these 78 interactive modules transform economics from an academic exercise into a hands-on framework for understanding the world.
To provide quality reputable learning materials and avoid potential misinformation and hallucination, students are limited to those provided teaching materials and when a knowledge point is mentioned or applied, references of which teaching materials and where in the teaching materials are provided. Students can therefore go further into the teaching materials if they choose to.
Graphics is an important part of economic learning. This tool also provided needed graphs to illustrate the key concepts, graphic models and economic theories. Although not all graphs appeared as polished as Zhang and Keerikkattil would have liked, because of limitations in the underlying agent functions, the basic illustrative graphs were still helpful. More refined visualizations can be developed in the future as these functions improve.
This approach reflects a broader philosophy of how artificial intelligence is used in the classroom at Merrick. AI is not treated as a substitute for thinking, nor as something to be avoided. Students are required to submit working process files for the assignments and the transcript of each conversation is examined. BoodleBox's Enhanced AI Coach Mode actively develops student AI literacy through pattern recognition and evidence-based learning. The goal extends beyond preventing problematic AI use to actively transforming students from passive consumers of AI outputs into skilled practitioners who know how to collaborate effectively with AI tools. The classroom, in this sense, becomes a place where students learn not how to compete with AI, but how to collaborate with it without surrendering judgment. They learn to question outputs, to interrogate assumptions, and to distinguish between a well-written response and a well-reasoned one.
The success of AI-powered learning tools in ECON 606 offers a compelling blueprint for transformation across the University of Baltimore's four schools and colleges. As a University recognized by the Carnegie Foundation and designated as a Lead Institution in Civic Engagement, UBalt is uniquely positioned to pioneer AI-enhanced education that prepares students for the evolving workforce while maintaining the rigorous academic standards upheld by its accrediting bodies.
Employers aren't looking for those who hide AI use. They're looking for those who can use it effectively and transparently.
The ECON 606 tools embody this philosophy. Students learn to work alongside AI—questioning outputs, verifying sources, and distinguishing between well-written responses and well-reasoned ones. BoodleBox's Enhanced AI Coach Mode actively develops these metacognitive skills, transforming students from passive consumers of AI outputs into skilled practitioners who know how to collaborate effectively with AI tools. This matters because the workplace is changing.
As IBM's Lydia Logan described at the Chronicle of Higher Education forum, work is increasingly organized around "blended teams of humans and AI agents," where humans focus on judgment and collaboration while AI handles drafting and data analysis.
The Center for AI Learning and Community-Engaged Innovation (CAILI) supports faculty, staff and students across all schools in developing AI-enhanced educational tools.