Miscommunication and communication challenges between instructors and students represents one of the primary barriers to post-secondary learning. Students often avoid or miss opportunities to ask questions during office hours due to insecurities or scheduling conflicts. Moreover, students need to work at their own pace to have the freedom and time for the self-contemplation needed to build conceptual understanding and develop creative thinking skills. To eliminate barriers to student engagement, academic institutions need to redefine their fundamental approach to education by proposing flexible educational pathways that recognize continuous learning. To this end, we developed an AI-augmented intelligent educational assistance framework based on a power language model (i.e., GPT-3) that automatically generates course-specific intelligent assistants regardless of discipline or academic level. The virtual intelligent teaching assistant (TA) system will serve as a voice-enabled helper capable of answering course-specific questions concerning curriculum, logistics and course policies. It is envisioned to improve access to course-related information for the students and reduce logistical workload for the instructors and TAs. Its GPT-3-based knowledge discovery component as well as the generalized system architecture is presented accompanied by a methodical evaluation of the system accuracy and performance.

翻译：教师与学生之间的沟通不畅及交流困难是高等教育的核心障碍之一。学生常因缺乏安全感或时间冲突而回避或错过在答疑时间提问的机会。此外，学生需要自主掌控学习节奏，以获得自由时间和自我反思空间，从而构建概念性理解并培养创造性思维能力。为消除学生参与教育过程的障碍，学术机构需重塑其基础教学方法，提出认可持续学习的灵活教育路径。为此，我们基于大型语言模型（即GPT-3）开发了一种人工智能增强型智能教育辅助框架，该框架能自动生成面向特定课程的智能辅助系统，且不受学科或学术水平限制。该虚拟智能助教系统将作为支持语音交互的辅助工具，能够回答与课程内容、教学安排及课程政策相关的特定问题。其设计目标包括：提升学生获取课程相关信息的便利性，同时减轻教师和助教的教学管理负担。本文介绍了基于GPT-3的知识发现组件及其通用系统架构，并通过系统准确性和性能的系统性评估进行了验证。