Cover Image

Investigating the factors of undergraduate students support for AI utilisation

This study investigates the factors that influence undergraduate students' support for AI utilisation, focusing on personality traits, creativity, and information quality. As AI becomes increasingly integrated into educational practices, understanding the determinants of student support for AI...

Full description

Saved in:
Bibliographic Details
Main Authors: Tan, Yen Yee, Lee, Hui Ni
Format: Final Year Project / Dissertation / Thesis
Published: 2024
Subjects:
HA Statistics
HM Sociology
Online Access:http://eprints.utar.edu.my/6911/1/Tan_Yen_Yee_2005427.pdf
http://eprints.utar.edu.my/6911/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utar-eprints.6911
record_format eprints
spelling my-utar-eprints.69112025-01-24T03:12:38Z Investigating the factors of undergraduate students support for AI utilisation Tan, Yen Yee Lee, Hui Ni HA Statistics HM Sociology This study investigates the factors that influence undergraduate students' support for AI utilisation, focusing on personality traits, creativity, and information quality. As AI becomes increasingly integrated into educational practices, understanding the determinants of student support for AI is crucial for enhancing learning outcomes and guiding the effective implementation of AI tools in academic settings. The research employs a quantitative approach, utilising a structured questionnaire to gather data from 400 undergraduate students across various public universities and private universities in Selangor, Kuala Lumpur, and Perak. The study applies the Big Five Personality Traits, Divergent Thinking Theory, and Technology Acceptance Model (TAM) to explore the effects of the independent variables (personality traits, creativity, and information quality) on the dependent variable (support for AI utilisation). The findings reveal that all three independent variables significantly influence students' support for AI, with creativity having the strongest impact, followed by information quality and personality traits. These results suggest that fostering creativity and ensuring high-quality, relevant, and reliable AI-generated information are key to gaining student support for AI tools in education. The study concludes with recommendations for educators to integrate AI thoughtfully into curricula and for AI developers to focus on creating tools that meet the evolving needs of educational environments. The implications of this research are significant for the future of AI in education, as it provides insights into how students' support can be harnessed to improve educational outcome 2024-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/6911/1/Tan_Yen_Yee_2005427.pdf Tan, Yen Yee and Lee, Hui Ni (2024) Investigating the factors of undergraduate students support for AI utilisation. Final Year Project, UTAR. http://eprints.utar.edu.my/6911/
institution Universiti Tunku Abdul Rahman
building UTAR Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
url_provider http://eprints.utar.edu.my
topic HA Statistics
HM Sociology
spellingShingle HA Statistics
HM Sociology
Tan, Yen Yee
Lee, Hui Ni
Investigating the factors of undergraduate students support for AI utilisation
description This study investigates the factors that influence undergraduate students' support for AI utilisation, focusing on personality traits, creativity, and information quality. As AI becomes increasingly integrated into educational practices, understanding the determinants of student support for AI is crucial for enhancing learning outcomes and guiding the effective implementation of AI tools in academic settings. The research employs a quantitative approach, utilising a structured questionnaire to gather data from 400 undergraduate students across various public universities and private universities in Selangor, Kuala Lumpur, and Perak. The study applies the Big Five Personality Traits, Divergent Thinking Theory, and Technology Acceptance Model (TAM) to explore the effects of the independent variables (personality traits, creativity, and information quality) on the dependent variable (support for AI utilisation). The findings reveal that all three independent variables significantly influence students' support for AI, with creativity having the strongest impact, followed by information quality and personality traits. These results suggest that fostering creativity and ensuring high-quality, relevant, and reliable AI-generated information are key to gaining student support for AI tools in education. The study concludes with recommendations for educators to integrate AI thoughtfully into curricula and for AI developers to focus on creating tools that meet the evolving needs of educational environments. The implications of this research are significant for the future of AI in education, as it provides insights into how students' support can be harnessed to improve educational outcome
format Final Year Project / Dissertation / Thesis
author Tan, Yen Yee
Lee, Hui Ni
author_facet Tan, Yen Yee
Lee, Hui Ni
author_sort Tan, Yen Yee
title Investigating the factors of undergraduate students support for AI utilisation
title_short Investigating the factors of undergraduate students support for AI utilisation
title_full Investigating the factors of undergraduate students support for AI utilisation
title_fullStr Investigating the factors of undergraduate students support for AI utilisation
title_full_unstemmed Investigating the factors of undergraduate students support for AI utilisation
title_sort investigating the factors of undergraduate students support for ai utilisation
publishDate 2024
url http://eprints.utar.edu.my/6911/1/Tan_Yen_Yee_2005427.pdf
http://eprints.utar.edu.my/6911/
_version_ 1822926524755476480
score 13.232389

Similar Items