Sep 26th 2016

Teaching Statistics Through Data Investigations (MOOC-Ed)

Our world is rich with data sources, and technology makes data more accessible than ever before! To help ensure students are future ready to use data for making informed decisions, many countries around the world have increased the emphasis on statistics and data analysis in school curriculum–from elementary/primary grades through college. This course allows you to learn, along with colleagues from other schools, an investigation cycle to teach statistics and to help students explore data to make evidence-based claims.

During the Data Investigations MOOC-Ed you will: Strengthen your understanding of how to engage students in a statistical investigation process; Explore a framework for guiding your teaching of statistical investigations to promote deeper data explorations for your students; Use rich data sources, dynamic graphing tools and key statistical concepts to support investigations of questions that are of interest to you and your students; Examine the ways students reason with data to make evidence-based claims; Personalize applications of statistical investigations to your students; Collaborate with colleagues near and far to gain different perspectives on data investigations and to build a library of teaching resources.

The Teaching Statistics Through Data Investigations MOOC-Ed is brought to you by the Friday Institute for Educational Innovation at NC State University's College of Education. Dr. Hollylynne Lee is the lead designer, working with a team of teachers, researchers, designers and technologists to develop and offer the course.

This MOOC-Ed is applicable to anyone interested in strengthening their approaches to teaching statistics through data investigations. The statistical concepts included are those often introduced to middle school through early college learners. Thus, teachers of statistics in grades 6-12 and in post-secondary contexts are the primary audience. This course may also be of interest to elementary teachers, teacher educators, and teachers of other disciplines that use data-based explorations extensively to make claims and inferences (e.g., science, social science).