Publication: A.I. adoption in tertiary education
Date
2025-03-04
Authors
Shaik Haris Zafran Shaik Ahmad Nazran
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Abstract
This paper examines the constructs that influence A.I. Adoption in Tertiary Education. This study used correlation analysis, and multiple regression to analyses the independent variable which is Perceived Risk, Performance Expectancy, Effort Expectancy and Facilitating conditions and the dependent variable is A.I. Adoption in Tertiary Education. A total of 350 respondents participated in this survey to analyses the relationship between these variables. As a result, the study's findings could be used to help UNITEN students and staffs toimprove or modify A.I. Adoption in Tertiary Education primarily UNITEN. Furthermore, universities can use this data to understand the path that leads to the transition from conventional method to a more modern method of teaching and learning.
Keywords: Perceived Risk, Performance Expectancy, Effort Expectancy and Facilitating
conditions and A.I. Adoption in Tertiary Education