Student-Centered Learning: Room Design Matters
William S. Rayens, Ph.D, Associate Chair and Director of Educational Initiatives
Department of Statistics, University of Kentucky
There are fundamental reasons to inherently value a student-centered, activity-based classroom in which students are active participants in their own learning. This can be especially important in a statistical reasoning course where students need to appreciate the role of the mathematics that underwrite the familiar formulae, but are students not well served by having a purely mathematical encounter. At the University of Kentucky we have become profoundly aware of the challenges that the physical classroom space poses for student-centered learning and in this talk we will describe a space we have constructed that we believe is a true game-changer. This pilot room was designed by the speaker and was used as a model for twelve TEAL (Technology Enabled Active Learning) classrooms in the new $112 million Academic Sciences Building, set to open in the fall of 2016. We will describe these spaces and discuss the critical role of technology in the design and how we are using that technology to facilitate a student-centered pedagogy.
Research Experiences for Undergraduate Statistics Majors
Joseph Nolan, Northern Kentucky University
As we train our undergraduate majors, it is important to remember that statistical methodologies exist in large part because they are useful in research. Whether our statistics graduates go on for further schooling or move directly into the workforce, they consistently remind me that their undergraduate research experiences are immensely valuable in opening doors to their careers. In this presentation I’ll talk briefly about research opportunities available to our students at NKU, including the URSTEM program and the Burkardt Consulting Center. I’ll also review two nationally available programs available through CAUSE that can assist in generating enthusiasm for undergraduate research.
Reflections on Using Simulation Based Methods to Teach Statistical Methods
Amanda Ellis, University of Kentucky
In recent years using simulation based methods has become more popular when teaching undergraduate statistical methods courses. Over the last year at the University of Kentucky we have transitioned our statistical methods course to incorporate simulation based methods. Students are first introduced topics such as standard error, confidence intervals and hypothesis test by simulating sampling distributions, bootstrap distributions and randomized distributions respectively. Later in the course the formulaic based methods are introduced. In this talk we plan to briefly discuss how the simulation based methods are incorporated in the classroom and spend the majority of the talk discussing our experiences over the last year with the simulation based methods. We plan to highlight aspects that we thought have worked well and those that have not.
Teaching A Graduate Service Statistics Course Online
Christopher J. Mecklin, Murray State University
In this presentation, I will share some of my experiences in teaching a service course in biostatistics to graduate nursing students online. I have taught such a course in this format for the last four years. There are certain challenges that come up in teaching such a course online as opposed to a brick and mortar setting. I will talk about what has worked, what hasn’t worked, and what can be improved.
Statistics in a Liberal-Arts Context: Developing Basic Skills in Reading, Writing and Argumentation through Data Analysis Reporting in the RStudio Environment
Homer White, Georgetown College
Foundations is a two-semester sequence for first-year students at Georgetown College. the Fall course is common across all sections and stresses development of basic skills in analytical reading, argumentation and written communication in the context of material based largely in the humanities. The culminating act is the writing of thesis-driven essays. The Spring semester course varies in content by section and is intended to be a modestly interdiscipilinary course that continues basic skills development in a way that is appropriate to the discipline(s) under investigation. In this talk we review an attempt to teach elementary statistics as a second-semester Foundations course. We will examine the practice of reading, writing and argumentation in elemntary statistics, especially as they come together in data analysis reports – the statistical analogue of a thesis-driven essay. Although relatively timeless liberal-arts skills are the primary focus of Foundations, we find that in statistics careful attention to the computing environment is crucial for the conscious development of these skills.