The Five-Minute Safety Reset

This interactive safety project guides learners through identifying workplace hazards, understanding their real‑world severity, and making informed corrective decisions. Learners practice ranking risks using national BLS injury and fatality data to ground their choices in real incident trends. Scenario‑based decision points reinforce when to fix hazards and how to avoid unsafe behaviors. A safety‑reset helps learners build practical habits they can apply immediately on the job. The final reflection summarizes safe actions, risky choices, and overall performance to strengthen long‑term safety awareness. 

Problem Statement

The shop’s three technicians begin work immediately each morning without assessing the environment. Because the shop is cluttered, poorly maintained, and filled with mixed equipment (farm machinery, marine engines, moving trucks), hazards accumulate daily: trip hazards, crush risks, chemical spills, unsecured tools, and PPE inconsistencies.

The Owner Reports:

• minor injuries

• near misses

• inconsistent housekeeping

• rushed starts to the day

• no formal safety process

The Core Problem: 

Technicians lack a simple, repeatable habit for identifying and addressing hazards before work begins.

The Business Impact: 

Preventable injuries, downtime, liability exposure, and reduced productivity.

Needs Analysis

Current Behavior:

Technicians walk in → start working → react to hazards only when they cause problems. 

Desired Behavior:

Technicians perform a quick, structured hazard scan → address high‑risk issues → begin work safely. 

Root Causes: 

• No formal safety training

• No morning routine

• Shop clutter and inconsistent housekeeping

• “We’re too busy” mindset

• Hazards vary daily due to mixed equipment types

• No visual or procedural cues to trigger hazard recognition

Audience Profile

Three Adult Technicians:

• Ages 20-30

• Experienced with machinery

• Hands‑on learners

• Prefer practical, no‑nonsense training

• Limited patience for long modules

• High familiarity with equipment, low familiarity with formal safety frameworks

Motivators: 

• Staying safe

• Avoiding downtime

• Keeping the shop running smoothly

• Pride in workmanship

• Respect for real‑world examples

Constraints: 

• Limited time

• No LMS

• No prior structured training

• Rural environment with inconsistent internet

Learning Objectives

By the end of the simulation, learners will be able to:

1. Identify common shop hazards (trip, crush, chemical, electrical, fire, PPE).

2. Prioritize hazards based on severity and likelihood.

3. Choose appropriate corrective actions for each hazard.

4. Apply a repeatable “Five‑Minute Safety Reset” process at the start of each shift.

5. Recognize consequences of ignoring hazards through scenario outcomes.

Bloom's Levels:

• Apply (hazard recognition)

• Analyze (prioritization)

• Evaluate (decision‑making)

• Create (safety reset plan)

ADDIE

Analysis:

Workplace injury data from the U.S. Bureau of Labor Statistics shows that slips, trips, falls, electrical exposure, struck‑by hazards, and unsecured equipment collectively cause thousands of serious injuries and over a thousand deaths each year. Workers often overlook these hazards due to routine, rushed behavior, or limited situational awareness. The training need is clear: employees must strengthen hazard recognition, understand severity based on real incident data, and make safer decisions during daily operations.

Design:

The solution is a scenario‑based micro‑simulation built around realistic shop environments with comic‑style overlays to emphasize hazards. Learners scan the environment, identify hazards, rank severity using real BLS fatality and injury numbers, choose corrective actions, and determine when escalation is required. Scoring and decision variables reinforce safe behaviors. The design prioritizes clarity, immediacy, and high‑impact micro‑training moments that connect decisions to real‑world consequences.

Development:

The module is developed in Storyline using layered interactions, drag‑and‑drop mechanics, conditional logic, and variable‑driven feedback. Hazard cards, micro‑layers, and personalized components are built with consistent comic‑style elements. Each decision updates score variables and populates a final reflection panel summarizing safe actions, risky choices, and the learner’s safety mindset. Accessibility is supported through alt text, keyboard navigation, and mobile‑friendly touch targets.

Implementation:

The experience is deployed as a standalone micro‑learning module or integrated into broader safety training programs. It is optimized for desktop, tablet, and mobile delivery. Supervisors can use the final score to guide coaching conversations. The module fits seamlessly into on-boarding, refresher training, or pre‑shift safety briefings. 

Evaluation:

Learner performance is measured through scoring and decision accuracy. Reflection data highlights patterns of unsafe decision‑making and areas requiring additional coaching or training. Feedback from learners and supervisors informs iterative improvements to hazard imagery, micro‑training content, and decision logic. Success is defined by improved hazard recognition, stronger escalation behavior, and measurable reductions in unsafe actions during work shifts.