📚 Teaching Model

A blueprint for an interactive, one-semester-long statistics and programming seminar that blends project-based learning with elements of an inverted classroom. The combined format supports students' learning progress and fosters engaging virtual classes. The same setting can be adapted to shorter or longer courses and to both introductory and advanced levels.

🛠️ How the Course Runs

The format is demonstrated with an introductory class on data wrangling and management using the statistical software program R. Students are guided through a typical data science workflow that emphasizes practical data tasks and culminates in a simulated mini-conference where first research results are presented.

Key course phases:

• Data acquisition and management
• Data wrangling and transformation in R
• Visualization and basic analysis
• Presentation of initial research results at a simulated mini-conference

🔎 Learning Benefits

The project-based seminar with inverted-classroom elements produces concrete learning gains by:

• Supporting incremental, applied skill development
• Encouraging active work on authentic data problems
• Creating interactive and engaging virtual sessions that mirror real research practice

📈 Adaptability and Audience

The seminar design suits a one-semester course but is scalable to shorter workshops or extended sequences. It is appropriate for both introductory students learning data wrangling and more advanced learners who need a structured, project-driven workflow.