Guide to Chat Interactions

There are three types of AI chat interactions that can be found in a Kyron course. They are:

Our AI will automatically create the appropriate question and answer pair for these interactions when generating your course. However, if you choose to add additional additional interactions, you will need to provide the question and answer pair. Here are some guidelines for those inputs.

Kyron interactions are not typical chatbots because they start by asking the student a question and engaging them in a conversational learning dialogue. The question can be best thought of as a “check for understanding” to see if the student understands a concept or knows the steps of a procedure.

The answer field includes the material that should be covered in the chat interaction. If you want the student to think about the steps needed to get an answer, include those steps in the answer field as well.

The chat expectations represent the concepts in the answer or the steps in a procedure you would like the student to be able to articulate. If in testing it seems like a chat goes on too long try tightening or simplifying the concepts introduced in the answer field.

Enduring understandings are core insights or concepts that the lesson is designed to instill for long-term retention. This allows you, as the educator, to better support your students’ learning journey and ensure that these important ideas stick with them long after the lesson ends.

At Kyron, our courses always start with a learning objective. Our BackwardsByDesign workflow creates enduring understandings that represent the “big picture” or “big idea” that we want students to take away in the end. Thus, the Kyron chat uses this context as well in our interactions.

You can view the enduring understandings for your course in Course Settings under Course Context.