In curriculum development, it’s important not to make assumptions, especially about your audience – what they need, what they want, what they already know. My design process always starts with needs analysis and other information gathering that I can use to determine the best approach to the training being created, including the delivery strategy.

One strategy that I have found useful for rapid iteration of curriculum design on a new project, is to phase through multiple delivery models for the same content, evaluating at each phase to improve the design. So for example, if the ultimate goal is to create an asynchronous interactive eLearning course on a particular topic, I might still start with a lower LOE synchronous instructor-led training first and evaluate the curriculum through that lens before even beginning the storyboarding process for the eLearning design. Another upside to that approach is that there are typically sections of the live training that I can record and reuse within the asynch course.

Below is a storyboard for the first lesson in an interactive eLearning sample I’ve created (available in another section of this portfolio). You’ll see in this sample that the first page of my storyboards always outline the overall course objectives, with the associated evaluation metrics and learning design elements identified to address those objectives.

Data is everything when it comes to good learning experience design, but what types of data are needed to evaluate the success of a particular project can and should vary from project to project. There are generally four types of metrics I consider: user satisfaction, knowledge retention, behavior change, and business impact. The latter two are especially important, but typically require collaboration and alignment from a cross-section of project stakeholders.

For a recent project I completed – training users on new functionality within a software product – the initial iteration of the training course received a Net Promoter Score (NPS) of 63. NPS is a great metric to capture, as it indicates whether the users enjoyed the learning experience. A 63 is a fantastic score to achieve, especially on the first iteration of a course. NPS alone can’t tell us how effective the training was though.

So another metric we measured for the same project was a reduction in support calls on the topic of the training, representing the behavior change that we wanted to see from the learners. The training reduced support calls on the associated topic by 13%, which from a business impact standpoint meant that support resources were able to focus on higher impact calls, creating a more favorable impression of the company from customers, improving customer retention, and reducing support costs.

This sample course was built using Articulate Storyline. The audio was created using generative AI through NaturalReaders.com.

My design for this course includes persistent, in-module navigation (represented as a button bar on the bottom of the screen), allowing the user to easily jump between the different sections of the course content without relying on the less-customizable TOC feature within the standard player. I’ve also used color and icon-coded modern slide designs to indicate which section is currently active, and fluid animations to delineate content transitions and highlight user interactions.

Please note that as a sample course, only the first section of the course currently contains any content. This course is best viewed on a larger device screen, such as a tablet or computer. If you only see a spinner animation below, simply click the animation to load the course.