Jingjing Bao

Interactive Prototype · Proposal Under Consideration

Rethinking Pediatric Triage Training

From fragmented training to a connected learning experience

I proposed a responsive web solution connecting Emergency Severity Index (ESI) decision practice, facilitator-led discussions, and learning data to address limitations in existing Storyline training.

Explore the prototype Read the design story

The challenge & solution

An effective facilitation model limited by its technology

The existing pediatric triage training used Articulate Storyline for facilitator-led case discussions. I proposed connecting phone-friendly practice, response data, and facilitator insights in one experience.

BeforeExisting trainingAfterProposed solution
BeforeDifficult on phones
ProposedPhone-friendly practice
BeforeSeparate response and survey data
ProposedCentralized learning data
BeforeLimited participant visibility
ProposedConnected performance insights
From fragmented training to a connected experience.

Design decisions

01 / Design for the devices participants actually use

Since participants primarily use phones and tablets during facilitated sessions, I prioritized responsive layouts, readable text, and touch-friendly controls to make Emergency Severity Index (ESI) decision-making easier on their own devices.

Phone-friendly practice

Static interface preview

Facilitator is presenting the case

Small knee scrape
8 yr · child
Decision B
High risk–confused/distress?
YesNo

Your path: A: No

Not reached yetYour path
Compact ESI-style decision pathway Illustrative interface: the highlighted path follows No from decision A to decision B, with resources and vital signs shown below. NoNoYesYes ABCD Requires lifesaving intervention?High risk–confused/distress?How many resources?NoneOneManyHigh-risk vital signs? 125, 4, 3
Phone layout · Question above the decision tree. Fictional case. Try the working prototype

02 / Connect learning data

I proposed integrating scenario responses, individual performance, and survey data within one system using Supabase as a potential backend.

This would make it easier to track learning performance and support future evaluation rather than managing disconnected records.

Proposed connected workflow

Participant practice

Complete surveys and work through cases.

Responses
Shared learning data

Connect responses and performance records.

Response patterns
Facilitator insight

Review patterns and guide discussion.

Proposed workflow · Live data integration remains a future step.
Explore the detailed architecture

Proposed solution architecture

Goal: bring learning activity, facilitation, and data into one connected system.

Participant experience
  1. Pre-survey
  2. ESI-guided cases
  3. Individual results
  4. Post-survey

Complete surveys, make triage decisions, and review performance.

Responses
Supabase (proposed)
  • Survey responses
  • Case decisions
  • Performance records

Centralized data storage.

Response patterns
Facilitator experience
  1. Present case
  2. Review response patterns
  3. Guide discussion

Use learner response data to support live discussion.

Conceptual architecture · Database integration and real-time reporting are proposed capabilities.

03 / Make performance data actionable

I designed a dashboard that illustrates how individual and aggregated responses could help facilitators identify decisions worth discussing.

The enhanced prototype connects a suggested facilitation focus directly to case review and targeted discussion prompts.

Instead of simply revealing correct answers, facilitators can explore participants' reasoning and address potential misunderstandings.

Sample participant responses

Simulated data

Illustrative response patterns, not live participant data.

Decision A
  • Yes6%
  • No94%
Decision B
  • Yes12%
  • No88%
Decision C
  • None78%
  • One17%
  • Many5%
Decision D
  • Yes10%
  • No90%
ESI level
  • 13%
  • 25%
  • 37%
  • 416%
  • 569%
Facilitator view · Compare response patterns at each decision to identify where discussion may help.
How facilitators could use these responses

With a live data connection, facilitators could use response patterns to choose where to pause, ask participants to explain their reasoning, and focus discussion. The simulated responses above illustrate three opportunities:

  1. Explore a split in reasoning. At Decision B, 12% selected “Yes” and 88% selected “No.” A facilitator could ask, “Which case details led you to your answer?” and invite different perspectives before revisiting the decision criteria.
  2. Surface different interpretations. At Decision C, 78% selected “None,” 17% “One,” and 5% “Many.” Asking, “What resources did you anticipate, and why?” could help reveal differences in how participants interpreted the case and identify potential misunderstandings worth discussing.
  3. Trace the final decision. Although 69% selected ESI level 5, 31% chose another level. Rather than only revealing an answer, the facilitator could ask participants to trace their pathway and identify the first decision where their reasoning diverged.

The facilitator could then revisit the relevant case details or decision point, invite participants to reconsider their responses, and use a follow-up question or case to check understanding. This connects performance data with targeted discussion and further practice.

This is an illustrative use of simulated data. Real-time monitoring remains a proposed capability.

04 / Integrate the ESI chart as a job aid

I placed an interactive ESI decision tree alongside the questions to reduce the need to recall every step and reinforce familiarity with the algorithm.

As participants answer questions, their decision pathway is highlighted.

Because clinicians use the ESI chart in their actual workflow, the goal is proficiency in applying the job aid—not memorizing it.

10-second accelerated demo · The visual pathway highlights each decision as the learner progresses.
Text walkthrough · ESI-guided practice
  1. Review the current decision question alongside the ESI-style decision tree. The facilitator presents the case information separately.
  2. Select a response to the question. The visual pathway highlights the corresponding branch as the learner progresses.
  3. Use the highlighted chart to follow the reasoning behind the next decision, with the question and decision tree visible together.
  4. Continue through the case while the “Your path” summary records the selected responses. The chart stays available as a reference throughout the interaction.

The prototype

A functional proof of concept

Working prototype: Responsive participant practice, an interactive ESI decision tree, individual results, and facilitator dashboards using fictional cases and synthetic data.

Proposed next: Live data integration and clinical validation. Learning outcomes have not yet been measured.

Reflection

Design beyond individual learning activities

This project reinforced the importance of addressing the broader learning system rather than improving isolated interactions.

By examining mobile access, fragmented data, and facilitator needs together, I was able to propose a more connected solution.

The redesign also created opportunities to strengthen the learning experience through job-aid integration and data-informed facilitation.

My key takeaway: Effective learning solution design connects technology, practice, and performance needs—not just content and interactions.

Portfolio note: The public demonstration uses fictional clinical cases and simulated data. Original client materials are not included.

Explore the prototype