A simulation-based safety training that lets learners practice critical table saw decisions — without real-world risk
Audience: Workshop members new to using a table saw
Responsibilities: Instructional Designer & eLearning Developer
Analyzing injury data and safety risks
Designing the instructional approach and interactions
Developing the full Articulate Storyline experience
Creating all visual assets and interface elements
Tools Used: Articulate Storyline, Adobe Creative Suite (Photoshop)
Table saws are one of the most dangerous tools in a woodshop. In the United States they account for approximately 30,000 injuries annually and are a leading cause of serious hand injuries and amputations. Notably, severe injuries occur not only among beginners, but also among experiences users with many years of experience.
Traditional safety training often relies on written guides or passive instruction, doing little to prepare learners for real-world decision making at the machine.
This project uses scenario-based simulation to let learners actively practice safe table saw operation. Instead of reading static rules, users interact with the environment by:
Selecting appropriate personal protective equipment (PPE)
Configuring the table saw correctly for different types of cuts (rip cuts vs. cross cuts)
Reviewing the condition of a board to determine if it is safe to cut (knots, nails in boards)
Receiving immediate, context-specific feedback when unsafe choices are made
The simulation emphasizes learning through consequences, making safety concepts more memorable and transferable to real-world use.
By the end of the eLearning experience users will be able to choose the proper PPE for table saw work as well as demonstrate safe table-saw operation practices for simple rip and cross cuts.
Early storyboard frames showing interaction flow and planned conditional feedback logic tied to learner decisions.
Conditional logic used to detect mutliple unsafe configurations
Contextual feedback without breaking learner flow
Non-linear progression based on learner actions