Mathematics education students’ utilization of statistical packages for innovation and advancement across STEM fields

Abstract

Statistical packages are software tools designed to assist with data analysis, statistical modelling, and visualization. They provide a user-friendly interface for performing complex statistical procedures without requiring advanced programming skills. These packages often include a range of statistical tests, data manipulation functions, and graphing capabilities, making them essential for research in social science discipline such as mathematics education. Some popular statistical packages include SPSS, SAS, R, GenStat, and Stata, each offering unique features and strengths to cater to different types of data analysis tasks. They help researchers, including mathematics education students, to avoid routine mathematical mistakes and produce accurate findings in their research. However, the acceptance and usage of these packages by student-researchers are below expectation given the present dearth of skills and motivation for deploying computational techniques in educational research. Theoretically grounded on self-efficacy theory, technology acceptance model, and expectancy-value theory, this article intends to conceptualize the dynamics of statistical package utilization among mathematics education students by exploring the foundational issues of educational research, statistics, available statistical software (SS), factors limiting usage, and measures for encouraging improved usage. This presentation stands out by addressing gaps in previous research, which often overlooked the unique challenges undergraduates face in adopting SS, focusing on the mathematical rigor and specific needs of mathematics education students, offering discipline-specific insights and strategies. By doing so, it not only enriches understanding but also provides practical recommendations to enhance software proficiency and statistical literacy required for driving innovations and advancements across science, technology, engineering, and mathematics fields.