Citation

Ahmed, Zishan and Shanto, Shakib Sadat and Rime, Most. Humayra Khanom and Morol, Md. Kishor and Fahad, Nafiz and Hossen, Md. Jakir and Abdullah-Al-Jubair, Md. (2024) The Generative AI Landscape in Education: Mapping the Terrain of Opportunities, Challenges and Student Perception. IEEE Access. p. 1. ISSN 2169-3536

Text The Generative AI Landscape in Education_ Mapping the Terrain of Opportunities, Challenges and Student Perception.pdf - Published Version Restricted to Repository staff only Download (1MB)

Abstract

Generative AI (GAI) technologies like ChatGPT are transforming the educational landscape. Their integration presents significant opportunities for personalized learning and enhanced student engagement but also raises challenges related to academic integrity and the role of human educators. This study aims to provide a comprehensive review on using multiple GAI tools and their influence on academic outcomes, bridging the gap in the current literature. A systematic literature review has been conducted, adhering to PRISMA guidelines, to discuss findings on the opportunities and challenges of GAI in education.This review includes theoretical and empirical studies employing qualitative, quantitative, and mixed-methods approaches. We have also examined conceptual frameworks and innovative AI applications, focusing on originality and ease of implementation. To gather insights into students’ experiences and perceptions regarding the use of Generative AI (GAI) in education, a survey has been conducted with 200 undergraduate university students. GAI offers opportunities for personalized learning, task automation, educator support, efficiency enhancement, innovative approaches, and increased student engagement. However, challenges include assessment integrity concerns, potential overshadowing of educational values, accuracy of AI-generated content, disruption of critical thinking skills, and ethical and privacy considerations. The student perception survey reveals that most students find AI systems helpful in assisting with academic work. Besides, they are aware of the challenges and limitations associated with the technology.

Item Type:	Article
Uncontrolled Keywords:	Chatbots
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 Oct 2024 05:42
Last Modified:	01 Oct 2024 05:42
URII:	http://shdl.mmu.edu.my/id/eprint/13023

Downloads

Edit (login required)