EDTECH: What are the implications of your research for higher education, particularly for online learning engagement and student success?
WANG: Our research focuses on the design of natural communication between online learners and virtual teaching assistants (VTAs) being deployed in online learning contexts. As we try to scale up higher education to reach more students, there has been increasing use of different conversational agents in online learning, and VTA is a popular one.
VTAs can help answer student questions on course logistics such as assignment due dates, as well as common questions about class materials from previous semesters. All of these answers are largely delivered through text-based communications with online learners.
For VTAs like Jill Watson, the goal is to improve student engagement by providing timely and accurate responses to ensure student questions don’t go unanswered. However, similar to our less-than-satisfactory interactions with existing conversational agents like Amazon Alexa or Google Assistant in our daily lives, student communications with VTAs like Jill Watson are often viewed as unnatural and incoherent.
One reason for this is the gap between high user expectations of VTAs and the VTAs’ actual capabilities. In our case, with Jill Watson, students sometimes could not grasp what Jill could do, and therefore asked questions like, “Can you predict the score distribution at the end of the semester?” Jill, of course, could not answer this type of question.
When this kind of interaction happens more and more often, students became confused with Jill’s capability and frustrated with Jill over time. Our research focuses on how to help students and VTAs build a mutual understanding of VTA capabilities. This can ensure smoother and more natural communications.
When students can smoothly communicate with Jill, the interactions will be more enjoyable and engaging. More important, students will be able to get more out of the VTA’s ability to answer questions about online classes.
EDTECH: How can human-centered AI help support student retention?
WANG: One of the crucial factors in supporting student retention is to bring a personal touch that is commonly seen in physical classrooms to online classrooms. In physical classrooms, especially small classes, instructors can give personal attention to individual students through customized feedback and suggested learning strategies.
In the online learning environment, this kind of personal touch is almost completely lost, since the instructor-student ratio is often highly imbalanced. One potential way that human-centered AI could help with that is to not only create a VTA for the entire online class but also personal VTAs for every student in that class.
There are many ways this type of personal VTA can help. For instance, the VTA can identify student knowledge gaps by monitoring student learning activities and then suggest customized study strategies. It can help students navigate available learning tools. This can all help increase student retention in online learning significantly.