INTEGRATING INFORMATION PROCESSING THEORY WITH ARTIFICIAL INTELLIGENCE FOR ENHANCED LEARNING OUTCOMES

This paper explores the transformative potential of integrating Information Processing Theory (IPT) with Artificial Intelligence (AI) to enhance educational outcomes. By examining key concepts of IPT and their application in general learning and AI-driven educational tools, this review highlights how personalized learning, cognitive load management, and immediate feedback mechanisms can be optimized. The study reveals that significant improvements in student engagement, comprehension, retention, cognitive load management, and feedback can be realized through the intersection of AI and IPT a positive indicator for improving learning outcomes. However, the study recommends addressing challenges such as data privacy, algorithmic bias, and equity while working with AI tools and proposes future collaboration research between cognitive scientists, AI developers, and educators crucial for developing effective educational tools. Further research should focus on understanding the nuances of human learning processes and how AI can be designed to support these processes.

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Publication Details

Journal
International Conference on Aplied Social Sciences in Education
Published
2024-08-30
DOI
https://doi.org/10.31316/icasse.v1i1.6902
Citations
5
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
2.06
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article

INTEGRATING INFORMATION PROCESSING THEORY WITH ARTIFICIAL INTELLIGENCE FOR ENHANCED LEARNING OUTCOMES

Amr Abdullatif Yassin, Ashiraf Mabanja
5 citations
International Conference on Aplied Social Sciences in Education
Online Learning and Analytics
2.06
article

INTEGRATING INFORMATION PROCESSING THEORY WITH ARTIFICIAL INTELLIGENCE FOR ENHANCED LEARNING OUTCOMES

Amr Abdullatif Yassin, Ashiraf Mabanja
article en
5 citations

Abstract

This paper explores the transformative potential of integrating Information Processing Theory (IPT) with Artificial Intelligence (AI) to enhance educational outcomes. By examining key concepts of IPT and their application in general learning and AI-driven educational tools, this review highlights how personalized learning, cognitive load management, and immediate feedback mechanisms can be optimized. The study reveals that significant improvements in student engagement, comprehension, retention, cognitive load management, and feedback can be realized through the intersection of AI and IPT a positive indicator for improving learning outcomes. However, the study recommends addressing challenges such as data privacy, algorithmic bias, and equity while working with AI tools and proposes future collaboration research between cognitive scientists, AI developers, and educators crucial for developing effective educational tools. Further research should focus on understanding the nuances of human learning processes and how AI can be designed to support these processes.

International Conference on Aplied Social Sciences in EducationVol. 1(1)
Islamic University in Uganda (UG)
Openalex Percentile: Top 9%
Online Learning and Analytics
2.06
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