RT Journal Article
A1 Asyraf Afthanorhan
A1 Nur Zainatulhani  Mohamad
A1 Nik Hazimi  Fouziah
A1 Mochammad Fahlevi
A1 Ahmad Nazim Aimran
A1 Sanad Al Maskari
T1 Technology acceptance in statistics education: Implications for human capital and community capacity development
JF Central Community Development Journal
YR 2025
VO 5
IS 2
SP 77-95
DO 10.55942/ccdj.v5i2.1147
AB This study evaluates the performance of a proposed model based on the Technology Acceptance Model (TAM) to forecast students' opinions of statistics education improved by advanced technology. Using a sample of 379 undergraduate students from Malaysia's East Coast, chosen by simple random sampling, this study examined six main constructs: social influence, self-efficacy, perceived usefulness, perceived ease of use, attitude toward using, and behavioral intention. The measurement model was validated using confirmatory factor analysis (CFA), which found that each construct satisfied the necessary thresholds for model fit, dependability, and validity. Students' attitudes toward using technology were found to be influenced by perceived usefulness, social influence, self-efficacy, and perceived ease of use, according to a structural model examined using Covariance-Based Structural Equation Modeling (CB-SEM). Attitude, perceived ease of use, social influence, and self-efficacy significantly affected behavioral intention; the direct path from perceived usefulness to behavioral intention was not statistically significant. Four major mediation effects were also found, which emphasizes the importance of attitude in connecting the antecedent variables to behavioral intention. Thus, by using the digital education for statistics course, the model under test is also sufficient to match the present development and will be helpful for future studies.
K1 Technology Acceptance Model, Statistics Education, Structural Equation Modeling, Undergraduate Students
LK https://journal.privietlab.org/index.php/CCDJ/article/view/1147
ER