Data Chaos

➡️ Spreadsheet Savvy

Data Chaos to Spreadsheet Savvy is an eLearning simulation designed to train project coordinators at Abingdon Workforce Solutions on essential spreadsheet skills. The goal is to improve data records and reporting by 50% in three months by helping coordinators reduce errors, increase formatting consistency, and improve data processing efficiency. The simulation guides learners through three main tasks: data entry, using formulas, and presenting data.

Audience

Project coordinators from the concept company, Abingdon Workforce Solutions (AWS)

Responsibilities

Instructional Design
eLearning Development
Text-based Storyboard
Action Mapping
Script Writing
Graphic Design
Video Creator/Editor

Tools Used

The Problem and Solution

Abingdon Workforce Solutions' project coordinators require an effective method to enhance data records and reporting. Currently, their limited knowledge of spreadsheets leads to inconsistent and inaccurate data, hindering their ability to meet organizational goals.

I selected a scenario-based eLearning approach because it allows learners to practice real-world decisions in a safe environment. Unlike job aids or classroom training, scenarios let coordinators see the consequences of their choices, which mirrors the challenges they face on the job.

Upon completion, coordinators will be able to organize data more efficiently and produce more accurate reports. Abingdon Workforce Solutions set this 50% target as a measurable benchmark for success. Designing the course around this metric ensured that the training directly supported organizational priorities.

My Process

I used the ADDIE model to guide my work, starting with an analysis of the performance gap, then moving through design (action map, storyboard, mockups), development (prototype and full build), and finally evaluation, which included peer testing and planned learner feedback. Utilizing a data-driven design strategy, I focused on addressing performance deficiencies to enhance both employee capabilities and business results.

Action Map

Drawing on 15+ years of workforce development experience, I served as the subject matter expert for this project. To structure the design, I used Action Mapping, a method developed by Cathy Moore. This approach identified the specific actions coordinators need to perform on the job and ensures the training focuses on practice rather than just theory.

My business goal was to improve data accuracy and reporting by 50%. I focused on the key actions coordinators need to perform—data collection, automation with formulas, and clear presentation. Centering the training on these actions ensured the solution directly supported the goal.

Aligning the blueprint with AWS goals focused the project’s design and implementation.

Text-based Storyboard

To bring focus on content and logic, I created a detailed text-based storyboard that served as the project’s blueprint. Key elements included:

Scenarios aligned with the action map → each one tied directly to the high-priority actions coordinators need on the job.
Realistic consequences → incorrect choices led to issues like inconsistent formatting or inaccurate reports, while correct decisions resulted in recognition or improved efficiency.
Mentor support → A mentor character provided on-demand guidance and explained the “why” behind correct actions.
Consistent scripting → emails, mentor responses, and feedback were scripted in advance for a seamless learner experience.

This approach ensured consistency, streamlined development, and kept the training tightly focused on learner performance.

Visual Mockups

To ensure the course design was cohesive and learner-friendly, I created:

Mood board for inspiration → explored different visual directions and identified a tone that fit Abingdon Workforce Solutions’ professional context.
Style guide for consistency → established colors, fonts, and iconography to reinforce brand identity and minimize distractions.
Structured wireframes → mapped out layouts for each screen type, ensuring intuitive navigation and clarity before adding design details.
Detailed mockups → provided a realistic preview of the final design, helping catch issues early and secure stakeholder buy-in.

These steps kept the visual design consistent, reduced costly revisions, and supported an interface that was clean, professional, and engaging for learners.

Custom Artwork

To adhere to the style guide’s color scheme, I modified the components of each scene. I used Figma to refine SVG components and align them with the color palette.

Original

Modified

Original

Modified

I created a background graphic using a masking technique to mimic a window. Applying this mask to a stock office image tailored the scene to a coordinator’s cubicle perspective and enhanced narrative consistency.

The final visual development design incorporated video screen recordings to demonstrate the exact steps learners needed to complete tasks. This effectively linked the commands and functions within the spreadsheet applications.

Interactive Prototype

After approval of the storyboard and visual mock-ups, I built an interactive prototype that included:

Title slide, introduction, and mentor introduction → gave stakeholders a clear preview of tone and learner guidance.
One complete scenario question with layers and triggers → demonstrated branching logic and feedback flow in action.
Purpose of the prototype:
- Test functionality and confirm branching logic.
- Gather feedback on navigation, timing, and flow.
- Provide a tangible preview to secure stakeholder confidence.
Early quality assurance review → ensured accessibility, usability, and consistency before full build.

This step reduced the risk of costly revisions later, streamlined development, and validated design choices with stakeholders early in the process.

Full Development

After the prototype was approved, I built the full eLearning course with personalized features that adapted to learner choices.

To support engagement and retention, I focused on two strategies:

📖 Story-Driven Consequences

Incorrect decisions extend the storyline and reveal long-term impacts.
Learners see the results through manager emails (Jordan) and mentor feedback (Alex), which explain the “why” behind each correct action.
This approach mirrors real-world decision-making and aligns with Clark & Mayer’s research on knowledge transfer.

🏅 Integrated Recognition

Learners earn badges and receive encouragement from Alex and Jordan for correct choices.
Microlearning events demonstrate specific spreadsheet functions, giving just-in-time support.
Together, these features build confidence and help meet AWS’s goal of 50% improvement in data accuracy.

Results and Takeaways

Peer testing feedback → testers found the course intuitive but suggested simplifying navigation on mentor feedback screens.
Design refinements made → reduced text density and added visual cues, which improved flow and clarity.
Content validation → cross-referenced with AWS reporting guidelines and industry best practices to ensure accuracy and relevance.
Next steps:
- Roll out the course with project coordinators.
- Gather supervisor and learner feedback on usability, engagement, and knowledge transfer.
- Evaluate whether the training meets the 50% improvement target in reporting accuracy within three months.
- Use findings to refine the course in future iterations.

Overall, this project not only strengthened my design process but also provided a scalable solution that can continue to evolve with feedback and measurable results.

Page updated

Report abuse