Platform-Independent and Curriculum-Oriented Intelligent Assistant for
Higher Education
- URL: http://arxiv.org/abs/2302.09294v1
- Date: Wed, 15 Feb 2023 19:02:01 GMT
- Title: Platform-Independent and Curriculum-Oriented Intelligent Assistant for
Higher Education
- Authors: Ramteja Sajja, Yusuf Sermet, David Cwiertny, Ibrahim Demir
- Abstract summary: We developed an AI-augmented intelligent educational assistance framework based on a power language model (i.e., GPT-3)
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.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
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