Teachers' perspectives on the application of technology in mathematics education in primary schools: A dataset from Vietnam

This dataset offers insights into the integration of technology in primary school mathematics education, as perceived and evaluated by primary school teachers in Vietnam. Based primarily on the Technology Acceptance Model (TAM), it covers five key aspects from teachers' perspectives: (a) Teacher background information, including gender, teaching experience, qualifications, and location; (b) Teachers' views on the role of technology, encompassing AR technology and its application in mathematics education; (c) Practical implementation of technology in primary school mathematics classrooms, detailing tools used, instructional methods, assessment practices, frequency of implementation, and evaluation; (d) Teachers' self-assessment of technology integration effectiveness, including high-tech applications like AR technology in primary school mathematics education; and (e) Teaching conditions related to technology integration and teacher readiness to prepare and utilize technology in mathematics teaching. The survey, conducted online via Google Forms from October to December 2023, involved 11,811 primary school teachers from ten provinces in Vietnam. This dataset aims to provide valuable insights for policymakers and educational administrators to understand the current landscape of technology use in mathematics education. It seeks to inform policy decisions and initiatives related to technology integration, including AR technology in mathematics teaching, and supports efforts to enhance the quality of mathematics instruction. Furthermore, the dataset contributes to evidence-based interventions aimed at supporting teachers' professional development in applying technology in mathematics education. Educational managers and researchers can leverage this dataset to gain insights into pedagogical improvements such as teacher training and policy formulation related to technology integration in mathematics education. Additionally, this dataset can assist educational technology developers in understanding teachers' needs, readiness, actual use, and practices to develop technology applications for mathematics teaching. Overall, this dataset is valuable in providing an overview of technology applications in mathematics education, supporting educators and policymakers with evidence-based strategies to enhance technology integration, and guiding educational technology developers in aligning future developments with teachers' practical needs and capabilities.