Climbing to Creditville

Climbing to Creditville is an interactive, award-winning eLearning simulation that helps people raise their FICO credit scores.

• Responsibilities: Analysis, Instructional Design, eLearning Development, Narration, Graphic Design, Evaluation
• Target Audience: Current or soon-to-be financially independent 18-35 year olds in the USA
• Tools Used: Storyline 360, Illustrator, Audacity
• Budget: Medium to High
• Year: 2018

Process

I decided to design this learning experience after witnessing a severe gap in skill and knowledge on the personal finance front. Many of my peers in college were unfamiliar with general personal finance and credit score principles. So, as a graduate student eager to help people become more financially literate, I decided to build a learning solution that would help bridge the knowledge and skill gap surrounding credit scores.

I wanted to help people learn what made their credit score tick, as well as how they could make decisions that would lead to a credit score that would work for them rather than against them.

I validated this idea by interviewing 20 college students (undergraduate and graduate) in my network, and all except one of them expressed a desire for this learning experience and a lack of knowledge surrounding credit scores.

Having opened my first credit card at 18 and leveraged my credit to earn thousands of dollars in credit card rewards during college (as well as engage in multiple online personal finance communities), I felt confident that I could serve as Subject Matter Expert and conduct additional research as needed.

Instructional Design

As always, I began my instructional design process by identifying the instructional goal: to help people make financial decisions that contribute to a perfect FICO credit score.

From there, I identified three supporting learning objectives that would contribute to the overall goal:

1. Identify the five factors that comprise a FICO credit score.
2. State how large of an impact each factor has on the FICO credit score.
3. Determine how each financial decision impacts the FICO credit score.

I then located my sources: the Capitol One Creditwise credit score simulator, an article from the FICO website, and a video from the FICO YouTube channel.

I used these sources to write the raw content that my audience would need to know; particularly, the five factors that comprise a FICO credit score and the weight assigned to each.

With this content in hand, I considered how I would present it to the learner. Since I wanted my audience to be able to use what they learn to make decisions rather than just recite information, I decided to include a realistic scenario where the learner could make choices, see the consequences, and learn from their mistakes without hurting their real-world credit scores.

To respect the participants' learning preferences and unique backgrounds, I knew that I wanted to make the content available on-demand — not force them to go at a pre-determined pace. I decided to curate resources that the user would be able to access whenever they'd like.

I already had the video and article that I had used during my research, but I wanted to provide a podcast and infographic to round out the resources. I made note that I would have to design and develop these in conjunction with the interactive simulation.

Next, I put on my storytelling cap and devised a scenario for the simulation: James wants to purchase his dream home in Creditville, but he needs a credit score above 800 to move there. By framing the scenario like this, i hoped to build the learner's motivation by giving them a clear goal and helping them relate to the main character: a recent graduate who is feeling overwhelmed by personal finance responsibilities.

From there, I ironed out the content for the podcast, infographic, and simulation itself.

Designing the Podcast

I titled my podcast "Money Mondays," and I wrote a script that covers the FICO credit score. I wrote the script as if this episode were part of a longer, legitimate podcast series to help establish credibility and gain attention. I kept the script focused on the FICO credit score components, and I gave examples as needed to illustrate the effect that each component has on the overall score.

Designing the Infographic

For the infographic, I knew that I would have to pack a punch visually. I decided to include a pie chart that would signify the effect that each factor has on the overall credit score, and I wrote a brief one-sentence description of how each component works. I also decided to include a visual representation of what makes a "good" credit score, showing the different score brackets on a horizontal bar, differentiating each bracket by how the score appears to lenders.

Designing the Interactive Simulation

First, I wrote the script for a brief introductory video that would set the context for the scenario, build the user's motivation by introducing the game-based elements, and provide guidance by mentioning the optional resources.

Next, I wrote the questions that the user would be faced with. The questions were based directly on the objectives — for each FICO credit score component, I wrote two questions to test the user's comprehension of it.

I calculated the effect that each decision would have on James', the main character's, credit score using the Capitol One Creditwise simulator.

With all of this content in hand, I knew that I was ready to move into development.

eLearning Development

Moving into development, I considered my graphic design approach. I decided that I would use an illustrated, flat-vector approach to both the simulation and the infographic, whereas the podcast would obviously not have a visual component. With this art direction in mind, I began developing the instructional artifacts.

Developing the Podcast

With the script in hand, I recorded the podcast within several hours. I used Audacity and my Blue Yeti microphone to produce a high-end reading of the script, but at the same time, I am not a pro voiceover artist. The final reading was a good fit for my needs, and it sounded ready-to-go after working in the background music.

Developing the Infographic

Anticipating that the infographic would be the most useful resource in helping users make choices both during the simulation and after completing it, I prototyped the initial version, asked for feedback from my peers, and continued reworking it to optimize it. I used vector graphics from freepik.com, and I reworked them all in Illustrator to maintain a consistent color scheme.

I used negative space, contrast, repetition, and alignment to produce a well-balanced, easy-to-read final document.

Developing the Interactive Simulation

To start things off with the simulation, I recorded the narration for the intro video. Once again, I did this in Audacity, and I spent a decent amount of time incorporating upbeat background music to help gain and maintain the user's attention.

Once I was satisfied with the narration, I developed the video on a single slide in Storyline. I used assets from freepik.com, which is where I got the assets for all of the visuals in the project. (You can view this video below, but keep in mind that Storyline's mp4 output is a bit buggy, and the production version is much smoother.)

I continued with graphic treatments by designing a:

• Clean title screen
• Resources screen that links to each of the optional resources
• Template for the "feedback" screen that announces the credit score change and explains why it changed
• Template for the question slide that allowed me to swap out the text and background image
• "Transition screen" that shows the sun and moon moving across the sky, simulating the passing of time

From there, I plugged in the text for the questions and began handling the programming. I used one variable to hold the credit score, one variable to hold the year, and many variables to hold the user's response to each question.

On each feedback screen, I directed the user to the appropriate layer depending on their previous responses. This got quite complex as I had to account for every combination of responses to ensure that I displayed the appropriate credit score and feedback at that point in time.

Before bringing the project live, I incorporated custom JavaScript xAPI triggers to track user responses and measure the effectiveness of each resource. Despite asking for the user's email address, I wound up using anonymized actor data for privacy concerns.

Evaluation

After completing the simulation, I shared it with all of my peers. It was very well-received, and many people were surprised about the impact of their choices. It highlighted the need for an experience like this, and it sparked many of my peers into action insofar as starting new credit lines and establishing credit history was concerned.

From there, I shared the experience on the web and made it available publicly on my portfolio. Over 350 users have completed the simulation, and the users who viewed the optional resources performed signifcantly better than those who did not.

This confirmed that the supporting content was effective in helping the users acheive the learning objectives.

I also made several quality-of-life improvements based on the data that came in, such as reducing the amount of time on the transition screen, adding (and then removing) a SKIP button to the intro video, and updating the supporting resources.

The project won the Oustanding Practice by a Graduate Student in Instructional Design award at an AECT conference in 2018.

Project Takeaways

This project was, and continues to be, one of my biggest solo projects. I handled everything: initial user surveys, narration, graphic design, instructional design, development, and evaluation. It helped me build confidence as a one-stop-shop, and it reiterated my love for designing engaging eLearning experiences.

I've used what I learned on this project to support many future needs, especially those involving complex Storyline programming, building supporting resources in an online environment where the learner has freedom to access content as needed, and using xAPI data to make informed improvements to the program.