AI-Driven Contextual Virtual Teaching Assistant Using RASA

Gaurav Shekhar, Rhea D'souza, Kevin Fernandes
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引用次数: 1

Abstract

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
基于RASA的ai驱动情境虚拟教学助手
随着传统课程转向在线平台,对在线内容的需求呈指数级增长,帮助学生更好地理解概念的定制内容出现了短缺。我们需要全天候的支持和资源,以确保学术的顺利过渡和连续性。我们的解决方案建议使用RASA,一个开源的会话人工智能(AI)框架,为学生提供上下文帮助,并以虚拟教学助理的形式为他们提供诸如演示的特定幻灯片或课堂上讨论的现实问题等资源。它还可以提出引导性问题,提供量身定制的答案。它的回答是基于讲师在课堂上教授的材料,使其与学生相关,不像一般的回答。上下文虚拟教学助理还将协助教师识别需要额外学术帮助的学生,回答与即将到来的测试或作业相关的查询,甚至可以提醒学生截止日期
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