Exploring Academics’ Acceptance of Technology in Statistics Education: Evidence from Confirmatory Factor Analysis

Article DOI: https://doi.org/10.57017/jorit.v4.1(7).06

Author(s):

Asyraf AFTHANORHAN Operation Research & Management Sciences, Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Malaysia
Nur Zainatulhani MOHAMAD Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Malaysia
Sheikh Ahmad Faiz Sheikh Ahmad TAJUDDIN Operation Research & Management Sciences, Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Malaysia
Nik Hazimi FOZIAH Mathematical Modelling of Business Risks, Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Malaysia
Ahmad Nazim AIMRAN School of Mathematical Sciences, College of Computing, Informatics and Media, Universiti Teknologi MARA, Malaysia
Muhammad Takiyuddin Abdul GHANI Behavioural Management, Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Malaysia

Abstract:

The aim of this study is to evaluate the performance of a proposed model utilizing the Technology Acceptance Model (TAM) to forecast student perceptions of statistics education with advanced technology. A total of 379 undergraduate students from Malaysia’s East Coast region were recruited using a simple random sampling technique. This study incorporates six main constructs that are tested simultaneously, namely social influence, self-efficacy, perceived usefulness, perceived ease of use, attitude toward using, and behavioural intention. The Pooled Confirmatory Factor Analysis (PCFA) was employed to assess the factor loadings and fitness of the model being tested. Moreover, the Composite Reliability (CR) and Average Variance Extracted (AVE) were established to assess their reliability and validity. The results of the Confirmatory Factor Analysis (CFA) demonstrated that all six constructs achieved satisfactory levels of model fit, reliability, and validity. These findings confirm that the measurement model is statistically robust and that each construct is well-defined and appropriate for further analysis. Given their strong psychometric properties, these constructs provide a solid foundation for future research and should be considered for further investigation by examining the structural relationships among them, particularly in the context of technology adoption in statistics education.

© The Author(s) 2025. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.

How to cite:

Afthanorhan, A., Mohamad, N. Z., Tajuddin, S. A., Foziah, N. H., & Ghani, M. T. A. (2025). Exploring Academics’ Acceptance of Technology in Statistics Education: Evidence from Confirmatory Factor Analysis. Journal of Research, Innovation and Technologies, Volume IV, 1(7), 83-98. https://doi.org/10.57017/jorit.v4.1(7).06

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