Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education

Ramteja Sajja; Yusuf Sermet; Muhammed Cikmaz; David Cwiertny; Ibrahim Demir

doi:10.48550/arxiv.2309.10892

Back

Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education

Preprint

Open access

Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education

Ramteja Sajja, Yusuf Sermet, Muhammed Cikmaz, David Cwiertny and Ibrahim Demir

ArXiv.org

Cornell University

09/19/2023

DOI: 10.48550/arxiv.2309.10892

Files and links (1)

url

https://doi.org/10.48550/arxiv.2309.10892View

Preprint (Author's original)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

This paper presents a novel framework, Artificial Intelligence-Enabled Intelligent Assistant (AIIA), for personalized and adaptive learning in higher education. The AIIA system leverages advanced AI and Natural Language Processing (NLP) techniques to create an interactive and engaging learning platform. This platform is engineered to reduce cognitive load on learners by providing easy access to information, facilitating knowledge assessment, and delivering personalized learning support tailored to individual needs and learning styles. The AIIA's capabilities include understanding and responding to student inquiries, generating quizzes and flashcards, and offering personalized learning pathways. The research findings have the potential to significantly impact the design, implementation, and evaluation of AI-enabled Virtual Teaching Assistants (VTAs) in higher education, informing the development of innovative educational tools that can enhance student learning outcomes, engagement, and satisfaction. The paper presents the methodology, system architecture, intelligent services, and integration with Learning Management Systems (LMSs) while discussing the challenges, limitations, and future directions for the development of AI-enabled intelligent assistants in education.

Details

Title: Subtitle: Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education
Creators: Ramteja Sajja
Yusuf Sermet
Muhammed Cikmaz
David Cwiertny
Ibrahim Demir
Resource Type: Preprint
Publication Details: ArXiv.org
DOI: 10.48550/arxiv.2309.10892
ISSN: 2331-8422
Publisher: Cornell University
Language: English
Date posted: 09/19/2023
Academic Unit: Electrical and Computer Engineering; Center for Health Effects of Environmental Contamination; Civil and Environmental Engineering; IIHR--Hydroscience and Engineering; Injury Prevention Research Center; Public Policy Center (Archive); Chemistry; Chemical and Biochemical Engineering
Record Identifier: 9984471942402771

Metrics

50 Record Views