Abstract:
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With the plethora of recent innovations in statistics education, assessing the impact of these changes on student learning is crucial. Statistical education research will not be able to sufficiently impact policy or the practice of teaching unless individual studies become grounded in a broader program of study. Several research paradigms offer strategies for gaining insights about student learning in introductory statistics courses. In deciding among research designs, one must consider the scope of the study, the nature of the subjects, and the desired knowledge to be gained. This talk will highlight what can be learned from our students and from each other, as well as from other disciplines such as mathematics and science education and cognitive psychology. A classroom-based research study of students' learning of sampling distributions will be given, highlighting outcomes such as tracking of student misconceptions, isolating effects of student interactions with technology, and formulation of a developmental model of student reasoning. Strengths and limitations of such research will be discussed, with the goal of expanding and integrating the alternative methods we use.
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