使用自然语言处理与深度学习为本科生构建虚拟教学助手
Virtual teaching assistant for undergraduate students using natural language processing & deep learning
AI总结：
针对在线教育系统效率低导致学生留存率差的问题，本文提供了数据集并初步实现了名为VTA-bot的虚拟教学助手，通过可查询基础Python课程内容的聊天机器人来提升大一学生的在线参与度。
摘要：
过去几年中，在线教育的普及度持续上升。受COVID-19影响，许多大学被迫转向在线教育。在许多情况下，即使经过两年多的在线教学，高校仍无法恢复传统的课堂项目。越来越多的机构正考虑采用混合学习模式，部分为线下，其余在线进行。然而，许多在线教育系统效率低下，导致学生留存率偏低。本文提供了一个主要数据集、名为VTA-bot的虚拟教学助手的初步实现及其系统架构。所提系统的初步实现包含一个聊天机器人，可针对基础Python编程语言课程的内容和主题进行查询。这一策略旨在提高学生在在线教育中的参与度和投入度，将使大学一年级学生从中受益。
英文摘要：
Online education's popularity has been continuously increasing over the past few years. Many universities were forced to switch to online education as a result of COVID-19. In many cases, even after more than two years of online instruction, colleges were unable to resume their traditional classroom programs. A growing number of institutions are considering blended learning with some parts in-person and the rest of the learning taking place online. Nevertheless, many online education systems are inefficient, and this results in a poor rate of student retention. In this paper, we are offering a primary dataset, the initial implementation of a virtual teaching assistant named VTA-bot, and its system architecture. Our primary implementation of the suggested system consists of a chatbot that can be queried about the content and topics of the fundamental python programming language course. Students in their first year of university will be benefited from this strategy, which aims to increase student participation and involvement in online education.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
