Research in most Science, Technology, Engineering, and Mathematics (STEM) disciplines uses statistical methods. Thus as students develop into research scientists, introductory statistics serves as a gateway course. If students struggle to incorporate statistics into their knowledge base, they may be effectively kept from careers that rely on statistics. Students who are Deaf or Hard-of-Hearing (DHH) learn differently and thus may lag behind their hearing counterparts in mainstream classrooms. In part, a gap in language knowledge can impede the understanding of statistics topics. What is a variable? What does it mean to have a distribution? With sign language interpreters and other support services, many mainstream instructors believe that DHH students have equal access to learning in their classrooms. Yet variations of instructional skill, interpreter knowledge of the discipline, and the lack of alternative representations of content often result in access that falls short of "equal". This paper describes the work of a team of faculty and student researchers seeking best practices for creating supplemental online learning tools. Starting from a list of prioritized challenging topics in statistics, the team developed a number of strategies and produced a pilot set of instructional videos. Formative feedback led to revised videos, which provided a significant gain in knowledge for DHH students when shown in an experimental setting.
Dr. Carol Marchetti is an Associate Professor of Statistics at Rochester Institute of Technology, where she teaches introductory and advanced undergraduate statistics courses and conducts research in statistics education, deaf education, and online learning. She is PI on the NSF Thinking CAP project, leading the collaborative efforts for a team of diverse researchers. Jacqueline McClive, Rochester Institute of TechnologyJackie McClive has worked in the field of deaf education for more than a decade. She holds degrees in mathematics and American Sign Language interpreting. Her research interests cover a wide range from various topics in discrete mathematics to finding ways to support deaf and hard-of-hearing students in their learning of math and statistics.
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