Exploring Academics’ Acceptance of Technology in Statistics Education: Evidence from Confirmatory Factor Analysis
Exploring Academics’ Acceptance of Technology in Statistics Education: Evidence from Confirmatory Factor Analysis
Author(s): Asyraf Afthanorhan, Nur Zainatulhani MOHAMAD, Sheikh Ahmad Faiz Sheikh Ahmad Tajuddin, Nik Hazimi FOZIAH, Ahmad Nazim AIMRAN, Muhammad Takiyuddin Abdul GHANISubject(s): Social Sciences, Education, Higher Education
Published by: RITHA Publishing
Keywords: academic perception; statistics education; technology acceptance model; confirmatory factor analysis;
Summary/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.
Journal: Journal of Research, Innovation and Technologies
- Issue Year: IV/2025
- Issue No: 1(7)
- Page Range: 83-98
- Page Count: 16
- Language: English
- Content File-PDF
