With traditional classes moving to online platforms and the need for online content growing exponentially, there is a deficit of customized content that helps students understand concepts well. It is the need of the hour to have round the clock support and resources to ensure smooth transition and continuity of academics. Our solution proposes the use of RASA, an open-source conversational Artificial Intelligence (AI) framework, to support students with contextual help and provide them with resources like specific slides of a presentation or real-world problems discussed in class in the form of a Virtual Teaching Assistant. It can also ask leading questions to provide tailored answers. Its responses are based on the material the Instructor teaches in class, making it relatable to the students, unlike generic responses. The Contextual Virtual Teaching Assistant will also assist the Instructor in identifying students that need additional help with academics, answering queries related to upcoming tests or assignments, and can even alert students about deadlines
Academics; Contextual Virtual Teaching Assistant (CVTA); Natural Language Processing (NLP); RASA, Artificial Intelligence (AI); Machine Learning