Role: Multimedia Designer
Focus: Data-driven decision-making
Format: Analytical + applied learning
Students often struggle to connect statistical concepts to real business decisions.
Existing content:
Tool-heavy
Lacked context for application
Business students and professionals
Mixed confidence with data and statistics
Making analytics approachable without losing depth
Bridging the gap between data and decision-making
Problem-first approach:
Define → Analyze → Decide
Real-world business scenarios
Guided walkthroughs of data interpretation
Step-by-step interactive exercises
Visualized datasets (charts, dashboards)
Case-based learning modules
Simplified UI to reduce intimidation
Relevant Subject Matter
Examples for this course included a pet database that made content exciting and refreshing for student engagment.
RStudio
RStudio was integral to lesson plans and demonstrations. This informed numerous design decisions in post production.
SMEs for technical accuracy
Iteration to balance complexity vs clarity
Improved comprehension of analytics concepts
Better learner confidence in applying data
Add more live-data simulations
Integrate tools like dashboards or sandbox environments
