Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education
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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.
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Los chatbots y asistentes virtuales han cobrado relevancia en contextos de educación híbrida y a distancia; operan las 24 horas del día, pueden responder preguntas frecuentes, orientar a los estudiantes en sus tareas y brindar asistencia personalizada de forma inmediata.
“Complementando estos desarrollos, el uso de chatbots y asistentes virtuales ha cobrado relevancia en contextos de educación híbrida y a distancia. Estas herramientas, que operan las 24 horas del día, pueden responder preguntas frecuentes, orientar a los estudiantes en sus tareas y brindar asistencia personalizada de forma inmediata [8].”
From Avances, Retos Éticos y Perspectivas de la Inteligencia Artificial (IA) en la Educación de América Latina (2025) · cites this paper as [8]
Sajja et al. (2023) describieron el marco AIIA para la educación superior, que utiliza técnicas de NLP para generar cuestionarios, retroalimentación y guías personalizadas, apuntando a reducir la carga cognitiva de los estudiantes.
“Sajja et al. (2023) describieron el marco AIIA (Artificial Intelligence-Enabled Intelligent Assistant) para la educación superior, que utiliza técnicas de NLP para generar cuestionarios, retroalimentación y guías personalizadas, apuntando a reducir la carga cognitiva de los estudiantes [8].”
From Avances, Retos Éticos y Perspectivas de la Inteligencia Artificial (IA) en la Educación de América Latina (2025) · cites this paper as [8]
LLMs can enhance personalization in learning provided they augment rather than replace human judgment.
“Likewise, Sajja et al. [56] emphasize that LLMs can enhance personalization in learning, provided they augment-rather than replace-human judgment.”
From Artificial Intelligence in Higher Education: A State-of-the-Art Overview of Pedagogical Integrity, Artificial Intelligence Literacy, and Policy Integration (2025) · cites this paper as [56]
LLMs can support learning when embedded within structured pedagogical frameworks.
“Yet, other studies suggest that LLMs can support learning when embedded within structured pedagogical frameworks.”
From Artificial Intelligence in Higher Education: A State-of-the-Art Overview of Pedagogical Integrity, Artificial Intelligence Literacy, and Policy Integration (2025) · cites this paper as [56]
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- Authors
- Sajja, R., Sermet, Y., Cikmaz, M., Cwiertny, D., & Demir, I.
- Affiliations
- University of Iowa (US)
- Department of Electrical Computer Engineering, University of Iowa, Iowa City, IA 52246, USA
- Corresponding author
- Sajja, Ramteja
- Venue
- Information
- Publisher
- MDPI AG
- Published
- 2024-09-30
- Volume
- 15
- Issue
- 10
- Pages
- 596
- ISSN
- 2078-2489 (ISSN-L)
- OpenAlex
- W4402988539
- Cited by
- 620
- References
- 34
- Citations by year
- 2026: 236 · 2025: 337 · 2024: 43 · 2023: 4
- FWCI
- 231.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Information (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- arXiv (Cornell University) (cc-by)
- Funders
- National Oceanic I& Atmospheric Administration (NOAA) (NA22NWS4320003, 2230710)
- National Science Foundation (NSF) (NA22NWS4320003, 2230710)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Edcuational Technology Systems
- Keywords
- personalized learning, adaptive learning, higher education, virtual teaching assistants, natural language processing, cognitive load reduction, personalized learning paths, virtual learning environments, student engagement, student satisfaction
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