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

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As of September 30, 2024, researchers presented a framework called artificial intelligence-enabled intelligent assistant (AIIA) for higher education, detailing its architecture, NLP techniques, and integration with learning management systems to provide interactive, personalized support.
The work matters because it outlines a concrete design for virtual teaching assistants that could shape how universities deliver adaptive learning, but the source presents benefits as anticipated potential rather than observed outcomes, leaving effectiveness, scalability, and long-term impacts uncertain.
- Paper presents AIIA framework leveraging AI and NLP for interactive learning platform in higher education.
- System capabilities include responding to inquiries, generating quizzes and flashcards, and offering personalized pathways.
- Integration with learning management systems (LMSs) and discussion of architecture and intelligent services described.
- Authors note potential to impact design and evaluation of virtual teaching assistants for learning outcomes and engagement.
AIIA system designed to deliver personalized and adaptive learning support in higher education, intended to reduce cognitive load and provide tailored pathways and assessment tools.
The rundown
The paper describes the methodology, system architecture, and intelligent services of the AIIA, including NLP-based interaction and LMS integration, as of its September 2024 publication.
It frames the assistant as engineered to facilitate knowledge assessment and deliver support tailored to individual needs and learning styles, while noting that findings have potential to inform future VTA development.
Sources
- Peer-reviewedInformation2024-09-30
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