Faculty Case Studies
Course Production Efficiency
End-to-End Development Support
Strategy: Use AI to Support End-to-End Course Design in AI-Focused Disciplines
Artificial Intelligence can be leveraged as a design and development partner to support the creation of complex, technology-focused courses from initial conception through assessment and delivery. By using AI to assist with alignment, content generation, and activity design, instructors and designers can efficiently build cohesive learning experiences that integrate emerging technologies while maintaining clear learning objectives and ethical considerations.
ACG 6936 – Applications of Machine Learning and AI in Accounting
In ACG 6936 Applications of Machine Learning and AI in Accounting, Instructor Uday
Murthy, Ph.D. collaborated with Learning Designer Chad Garcia, Ph.D. to design a graduate-level
course that meaningfully integrates machine learning, AI, and generative AI applications
within accounting contexts. AI was used as a streamlining tool across multiple phases
of development, including structuring the course, defining and aligning learning outcomes,
and designing learning activities and assessments.
AI tools assisted with drafting quiz questions, discussion prompts, feedback language,
grading criteria, and assignments that intentionally incorporated AI tools and technologies.
These tools were also used to support the design and organization of lecture and presentation
materials, helping orient students to course topics and expectations. Additional analysis
supported the identification and evaluation of learning resources and technologies
aligned with course objectives.
Through this approach, AI functioned as a collaborative design aid, supporting efficiency,
consistency, and alignment, while instructional decisions and final validation remained
faculty-driven, with guidance and support from the learning designer. The course prepares
students to apply AI and machine learning tools to real-world accounting challenges,
culminating in a capstone project that demonstrates applied learning.
AI-Enabled Tools Used: ChatGPT, Microsoft Copilot, Claude, Gamma, Microsoft PowerPoint, KNIME Analytics
Digital Learning Designer Tips
1) Anchor AI-generated content in the course's specific disciplinary context by providing the AI with the relevant learning outcomes, tools used (e.g., KNIME), prompt frameworks (e.g., RTF, RTRO), and student prior knowledge (novice, expert, etc.) upfront, so generated output is aligned to the course and activity objectives.
2) Design student assignments that mirror how the development team used AI. For example, structuring student work around the same prompt-engineering frameworks (RTF, RTRO) used during the course design, reinforcing a consistent message that AI augments rather than replaces the faculty or student in the learning process.
3) Confirm tool access, licensing, and institutional availability early for both the
development team and students, especially if the course relies on paid subscriptions
(e.g., ChatGPT Plus) or open-source platforms (e.g., KNIME) that students will need
reliable access to throughout the course activities.
Quick Details
Faculty Developer: Uday Murthy
College: USF Muma College of Business
Learning Designer: Chad Garcia, Ph.D.
AI Tools Used: ChatGPT, Microsoft Copilot, Claude and more