Digital technologies have been introduced for the purpose of enhancing the learning and teaching effectiveness, and many tools are designed specifically for mathematics education. However, whether pre-service teachers will actually intend to adopt the software or not in their future workspace is an important question. Even if they do, it is important to study the reasons behind their decision in this particular local context, and how the training curriculum can assist them in fulfilling their teaching goals. In this paper, our aim is to study the technology acceptance of our pre-service teachers in primary mathematics education, and investigate the incentives behind their decision of adoption in our local context based on their technology-enhanced learning experience in our Institute. Using multiple-regression analysis, we examine the factors influencing the technology acceptance of the pre-service teachers in their future teaching career. Our goal is to provide preliminary insights into how technology is perceived by these pre-service teachers in mathematics education training and career. This insight will help us build a better analytical model for a more formal analysis in our future study that fits both local and global contexts. Copyright © 2014 Asia-Pacific Society for Computers in Education.
|Title of host publication||Proceedings of the 22nd International Conference on Computers in Education, ICCE 2014|
|Editors||Chen-Chung LIU, Hiroaki OGATA, Siu Cheung KONG, Akihiro KASHIHARA|
|Place of Publication||Nara, Japan|
|Publisher||Asia-Pacific Society for Computers in Education|
|Publication status||Published - 2014|
CitationWong, G. K. W., & Cheung, H. Y. (2014). Analytical evaluation of technology acceptance in teachers training of primary mathematics education in Hong Kong: A preliminary study. In C.-C. Liu, H. Ogata, S. C. Kong, & A. Kashihara (Eds.), Proceedings of the 22nd International Conference on Computers in Education, ICCE 2014 (pp. 903-908). Nara, Japan: Asia-Pacific Society for Computers in Education.
- Technology acceptance
- Mathematics education
- Multiple regression analysis
- Teachers training