Abstract:
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Undergraduate statistics courses include a diverse set of students from various mathematical backgrounds, many of whom have a low evaluation of the subject and little inclination to participate. In response, we collected survey data in an introductory biostatistics course at the University of Rhode Island. Our purpose was three-fold. First, we wanted to examine student motivation in the form of grade incentives on weekly quizzes using regression splines for longitudinal data. Next, we analyzed if students entered the course with negative attitudes and low value of the subject and investigated how their opinion changed by the end of the semester using mixed effect linear models. Finally, we worked to identify students at higher risk of failure by studying the relationship between students' attitudes and achievement by inferring a correlation network and utilizing structural equation modeling. Data were collected pertaining to 146 students' responses to introductory and SATS-36 surveys throughout the semester and student achievement was recorded in the form of grades on homework, quizzes and examinations.
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