Date
Publisher
arXiv
The role that highly curated knowledge, provided by domain experts, could
play in creating effective tutoring systems is often overlooked within the AI
for education community. In this paper, we highlight this topic by discussing
two ways such highly curated expert knowledge could help in creating novel
educational systems. First, we will look at how one could use explainable AI
(XAI) techniques to automatically create lessons. Most existing XAI methods are
primarily aimed at debugging AI systems. However, we will discuss how one could
use expert specified rules about solving specific problems along with novel XAI
techniques to automatically generate lessons that could be provided to
learners. Secondly, we will see how an expert specified curriculum for learning
a target concept can help develop adaptive tutoring systems, that can not only
provide a better learning experience, but could also allow us to use more
efficient algorithms to create these systems. Finally, we will highlight the
importance of such methods using a case study of creating a tutoring system for
pollinator identification, where such knowledge could easily be elicited from
experts.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
