Big Data and Data Science are the most frequent words, one can hear on a daily basis in today’s world, indicating the rapid growth and importance of these fields. As statistics forms the fundamentals of data science, more graduates are expected to acquire statistical knowledge and skills to become key players in the nations’ initiatives and needs pertaining to big data. However, students tend to be demotivated to learn statistics from an early stage itself. Incorporating technology into the existing instruction method by the means of statistical packages such as RStudio is deemed to be an effective tool to motivate students to learn statistics. Accordingly, this study determined the effects of teaching introductory statistics with RStudio on undergraduates’ statistics motivation in a Malaysian public university. A descriptive quasi-experimental survey design was employed using fifty first-year students enrolled in various non-mathematics/statistics oriented programs. Students were equally assigned to the experimental (utilized RStudio alongside conventional instruction method) and control (followed only conventional instruction method) groups. Findings showed that experimental group students had higher statistics motivation than control group students. It was also indicated that statistics motivation of experimental group students was high, while that of control group students was moderate. Further, there were significant differences in the levels of factors of statistics motivation i.e. statistics self-efficacy, statistics active learning strategies, statistics learning value, statistics performance goal, statistics achievement goal and statistics learning environment stimulation between students in both groups. These findings implied that integration of RStudio exerted positive effects on students’ motivation to learn statistics. In essence, technology can be an effective tool to enhance students’ acquirement statistical knowledge and skills.
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Gopal et al. (2018) studied this question.
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