Title:
Predicting the Determinants of Dynamic Geometry Software Acceptance: A Two-Staged Structural Equation Modeling - Neural Network Approach
Author:
Chiu-Liang Chen
Published:
International Journal of Information and Education Technology, 10(6), 2020
http://www.ijiet.org/show-139-1634-1.html
Fact from the abstract:
"This research examined the predictors of dynamic geometry software adoption by using GeoGebra as a case study. The proposed model incorporated basic predictors of the technology acceptance model such as perceived usefulness (PU), perceived ease of use (PEOU), and attitude toward usage (ATU), as well as predictors relating to students’ mathematics attitudes, namely self-confidence in mathematics, perceived value of mathematics (VAL), and enjoyment of mathematics."