Using Artificial Intelligence in a Captivate Project
On a recent project, we needed to develop a customer service eLearning course that could act as a live customer, i.e. accept natural language statements, process them, and respond accordingly. If you’ve ever developed a conversation-based eLearning course in the past, you probably created a limited set of questions and corresponding responses, each one branching out to a different slide based on the selected option. While this approach works in many situations, it significantly limits what the learner can “say” to a customer in the training. Here, because the learner should be allowed to freely structure her statements, the branching approach cannot be used. The approach we took was to create the core module in Adobe Captivate 2017 and link it to the AI engine.
You can click on the screenshot above to see the live module.
In addition to being able to “score” unstructured statements, AI provided more benefits, including:
- Tracking whether the learner sticks to the script required by the company policy
- Determining whether a particular step of the conversation was executed on time, early or late
- Identifying irrelevant and duplicate questions/responses
- Customizing feedback for each step of the conversation
- Recording all conversations for management to review and utilize for further coaching
- Using data collected by AI to predict the outcomes of the training
- Training the AI algorithm to improve understanding based on the collected data
As a company specializing in advanced eLearning technology, we are very excited about the availability of great tools that are currently available on the market. We will continue sharing interesting examples of our work, and also hope to see what innovations the rest of the eLearning community brings to their customers. We would love to connect with anyone interested in exploring innovative approaches in eLearning, and welcome everyone to get in touch with us to learn more about what we do.