Scenario Based Learning | Katharine Johnston

Scenario Based Learning in Financial Literacy

Business Context

The Foundation for Financial Wellness (FFW) sought to scale access to its retirement support services. While 1:1 coaching outcomes were strong, demand consistently exceeded capacity thus limiting reach. Program evaluations revealed that participants struggled to translate financial knowledge into sound retirement decisions. This is was particularly apparent when faced with uncertainty, competing priorities, or emotional pressure.

FFW wanted a scalable learning solution that would improve decision quality while also serving as a bridge to appropriate coaching services.

Findings from existing evaluations:

Coaches were overloaded and spent a lot of time correcting foundational decision errors
Participants wanted a safe environment to make financial decisions in a test atmosphere
Learners struggled to understand how multiple variables interacted
Calculation accuracy and long-term planning judgment remained inconsistent

FFW partnered with Blue Sky eLearn to design a scenario-based eLearning solution. I served as the instructional designer responsible for the retirement decision-making curriculum, focusing on behavioral change, consequence awareness, and real-world application.

Learning Challenge

Participants entered programs with:

Misconceptions about retirement readiness
Limited opportunities to test decisions
Low confidence for navigating risk, debt, and income timing

The program needs to focus on two areas: how participants evaluate and adjust retirement decisions and how FFW’s broader services catalogue can help with those decisions.

Learning Objectives

Upon completion, participants will be able to:

Given projected retirement income, expenses, and market assumptions, the participant determines whether current retirement readiness is sufficient. If needed the participant can select a corrective action that focuses on long-term sustainability without increasing overall risk exposure.
When presented with multiple retirement income sources, the participant prioritizes withdrawals to maintain a sustainable rate below 8% while minimizing depletion risk during market downturns.
When debt service exceeds 15% of projected retirement income, the participant chooses to rebalance savings and debt to preserve long-term stability.
Given market conditions, time horizon, and risk tolerance, the participant can adjust investments to align with retirement income needs
When evaluating withdrawal and contribution options across taxable, tax-deferred, and tax-free accounts, the participant can select a strategy that reduces tax burden without impacting future income
When life events occur the participant can reevaluate and adjust retirement decisions to preserve long-term income stability

Instructional Strategy

Initial stakeholder conversations originally framed the core issues as a lack of financial knowledge. However through analysis of coaching data and learner behavior, the core issue identified was decision-making under stress, ambiguity, and competing constraints.

I selected scenario-based learning because it:

Enables experiential practice without real financial risk
Supports pattern recognition across decisions
Encourages reflection and metacognition
Aligns with adult learning principles and experiential learning theory

Key Design Decisions

Branching decision paths focused on meaningful pivots (not excessive complexity)
Immediate, consequence-based feedback tied to learner choices
Embedded reflection prompts to reinforce judgment and reasoning
Personas grounded in real participant data to increase transfer

I was responsible for:

Creating realistic scenarios and branching logic design
Mimicking real work decision in an interactive module
Developing personas grounded in real client experiences and coaching challenges
Customizing a branching narrative using coaching-style feedback
Defining acceptable standards through appropriate knowledge checks, reflection prompts, and learner flow
Setting guardrails for SME input by aligning content with FFW instructional curriculum and resources
Establishing the decision model that prompts agency and personal responsibility

Building Personas

I developed three composite personas based on client data, coaching trends, and SME interviews.

Pre-Retiree Investor (primary example)- Stable income, limited investment strategy knowledge, time-constrained to recover from any financial mistakes.
Single Parent Rebuilding Finances
High debt load, limited financial literacy, strong emotional and practical constraints.
Low-Earning Couple Under Financial Strain
High fixed expenses, inconsistent income, relationship dynamics impacting decision-making.

Personas were designed as mechanics with distinct constraints, risk tolerances, and tradeoffs that directly altered available choices and consequences.

I created a branching experience focused on applying appropriate financial decision and provided reflection touchpoints for the learner.

Primary Decision Paths

Investment strategy and allocation information
Risk protection
Understanding income sources

Secondary Decision Paths

Goal prioritization
Investment recalibration to budget
Promotion of FFW tools and services

Design Priorities

Decisions tied to real calculations
Immediate feedback on decisions
Short-term relief vs long-term pain
Forced recovery decisions
Promotion of FFW coaching services
Opportunities to go back to portfolio calculator and try new calculations
Strong coaching-style feedback to build financial confidence

How Persona Constraints Altered Decision Space

Each persona introduced hard constraints that limited or reshaped available options:

Income stability affected contribution flexibility
Debt levels altered risk tolerance thresholds
Changes to household structure introduced secondary consequences

As a result, learners could not rely on a single “correct” strategy across all personas. They were required to adapt their decision-making thus mirroring real retirement planning complexity.

For this example, we will focus on Persona 1: The Pre- Retiree.

Decisions and Consequences

Increase retirement contributions- reduced liquidity, increased vulnerability to market volatility
Decrease investment risk- accelerated growth potential with amplified downside close to retirement
Delay retirement- improved portfolio stability with lifestyle tradeoffs
Aggressively pay down debt- improved cash flow at the expense of investment growth

Emotional Drivers

Time compression and regret avoidance
Opportunity cost awareness
Balancing mathematical outcomes with realistic decision making

Interaction Model

To support application while managing cognitive load, the experience was built around:

Decision Screens
Learners applied strategies and immediately saw modeled outcomes, mirroring financial planning software.

Inline Knowledge Checks
Low-stakes confirmation of understanding without interrupting scenario flow.

Reflection Prompts
Placed at key inflection points to support metacognition, emotional awareness, and evaluation of tradeoffs.

Branching Design

FFW Retirement Module Scenario Based Learning.png

Learners navigated realistic financial situations where each decision impacted future outcomes, simulating how financial plans evolve over time.

Performance impact:

Practiced trade-off analysis
Built recovery strategies
Increased confidence in long-term planning

Why This Level of Branching

Retirement planning errors tend to result from patterns of thinking thus branching was limited to three primary decision domains:

Investment strategy and tax implications
Risk protection and income stability
Debt repayment versus retirement contributions

Each domain contained 2–3 high-impact decisions previously identified in the coaching data.

Branch Convergence

Paths diverged to deliver consequences and feedback, then reconverged before introducing new domains ensuring instructional coherence and realism.

Managing Complexity

Rather than branching on every decision, I used state-based variables to track:

Risk tolerance
Liquidity pressure
Retirement readiness confidence

These variables influenced feedback tone, warnings, and consequence timing, allowing personalization without exponential content growth.

Learners received feedback explaining why a choice mattered. The design was intended to:

Reinforce mental models
Support transfer beyond the course
Reduce reliance on memorized rules

This maintained consistency across personas while supporting scale and maintainability.

Design Execution

Execution priorities included:

Progressive complexity to prevent overwhelming the person
Plain-language explanations of financial concepts
Consistent interaction patterns
Opportunities to revisit calculations and recalibrate decisions
Alignment with FFW brand and coaching philosophy

My focus was instructional clarity, scenario flow, and decision realism.

Design sample- Video made in Camtasia and used to introduce to the course.

Sample knowledge check reflection.

Feedback as a Driver

To move beyond simple corrective feedback, I designed consequence driven feedback to mimic a real-world coaching experience. Instead of labeling choices as "good" or "bad," I used state-based variables to show the immediate and long-term impact of decisions on the learner’s financial health. For the pre-retiree persona, this meant focusing on opportunity cost and time compression. By visualizing the trade-off between debt relief and retirement delays, the feedback forces learners to engage in metacognitive reflection, requiring them to "recover" from poor choices just as they would in real-life. This approach not only builds decision-making competence but also reinforces the value of FFW’s 1:1 coaching for navigating complex trade-offs. Below is an example of how this played out in the course.

Choice confirmation screen. Learners are prompted to review their choice before continuing. For this example, learners will confirm their choice.

Coaches feedback of the emotional consequence of the decision.

Coach shows how data has shifted.

Forced recovery decision.

Outcomes and Impact

Learner Impact

Foundational coaching corrections reduced by 75%
Improved accuracy in retirement readiness assessments
Increased learner confidence navigating financial decisions

Business Impact

Coaches spent more time on advanced strategy vs remediation
Participant engagement across programs increased
Adoption of affiliated services increased by 35%

Iteration and Refinement

The development of this program required balancing subject matter expertise with scalable logic. This led to two critical pivots during the design phase:

1. Reframing the "Coach vs. Course" Conflict- Initially, SMEs were resistant to this approach, fearing a digital solution would "replace" nuanced coaching. To build buy-in, I repositioned the eLearning as a pre-coaching sandbox. I demonstrated how the scenario would handle the repetitive, foundational decision-making errors which in turn would allow coaches to focus on high-level strategy during 1:1 session. This shift transformed the SMEs from skeptics into advocates. They saw this scenario-based eLearning as a way to increase the quality and quantity of their interactions.

2. Managing "logic bloat" and variable categorization- In the early build, the branching logic was hyper-specific, attempting to track every minor financial fluctuation. This created "logic bloat" that was difficult to maintain and confusing. I pivoted by moving from specific numeric tracking to broad state variables (categorizing "liquidity" as Low, Stable, or Surplus rather than exact dollar amounts). This simplified the backend architecture and allowed the feedback to focus on the principles of decision-making rather than getting bogged down in math. This ensured the instructional goals remained the primary focus.

My Role

I served as the lead instructional designer, responsible for:

Conducting needs analysis and reframing the problem as a performance issue
Designing personas, branching logic, and feedback architecture
Partnering with SMEs and coaching leadership to validate realism and accuracy
Managing complexity, scope, and instructional integrity
Iterating based on stakeholder feedback and learner behavior

This role required balancing instructional rigor, business constraints, and stakeholder expectations.