Diagnose Before You Escalate is an interactive Storyline simulation that places learners in a learning systems support role, where they investigate real-world support scenarios, trace issues across interconnected systems, and determine when to resolve, reprocess, or escalate.
Format
Scenario-Based Simulation
Focus
Learning Systems Support
Skills
Troubleshooting
Systems Thinking
Performance Support
Tool
Articulate Storyline 360
Learning-system issues often appear as simple user problems—a missing course, an absent account, or a failed launch—but the actual failure may occur somewhere else in the learning ecosystem.
The challenge was to design an experience that moved beyond procedural “click here” training and instead developed the learner's ability to gather evidence, trace data across systems, identify the likely failure point, and determine an appropriate resolution or escalation path.
Represent the reasoning process behind effective systems support rather than simply demonstrating software steps.
Require learners to examine evidence across HRIS, LMS, data-transfer, SSO, and external-tool environments.
Allow learners to diagnose problems, make realistic support decisions, receive consequence-based feedback, and revisit evidence when needed.
I designed the experience around a repeatable troubleshooting workflow: gather information → identify the failure point → resolve or escalate → verify.
Rather than presenting information first and testing recall afterward, the simulation gives learners a support ticket and access to system evidence. Learners decide what to investigate, interpret what they find, commit to a diagnosis, and choose an appropriate response.
I built the simulation in Articulate Storyline 360 using variables, conditional triggers, layers, hotspots, and persistent learner states to create a nonlinear investigation experience.
NONLINEAR INVESTIGATION
Learners can examine systems in different orders and revisit evidence before committing to a diagnosis.
STATE & PROGRESS TRACKING
Variables track reviewed evidence, selected diagnoses, resolution decisions, and completed tickets.
CONSEQUENCE-BASED FEEDBACK
Incorrect resolution choices explain the operational consequence of the decision rather than simply displaying “incorrect.”
PROGRESSIVE CASE QUEUE
Completing each case returns the learner to an updated support queue and unlocks the next scenario.
The finished simulation transforms a technical troubleshooting workflow into a practice environment where learners can investigate, make decisions, receive feedback, and try again without real-world consequences.
The project reinforced the value of designing around performance decisions rather than content coverage. By allowing learners to inspect evidence and revisit information, the experience assesses their ability to interpret system data and choose an appropriate response - not their ability to memorize a troubleshooting checklist.