Teaching Statistics Through Data Investigations
Who Should Take This Course?The Teaching Statistics Through Data Investigations MOOC-Ed is applicable to anyone interested in strengthening their approaches to teaching statistics through data investigations. The statistical content and strategies are appropriate for implementation with 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). There is no cost for participating in the Teaching Statistics Through Data Investigations MOOC-Ed.
- 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 and dynamic graphing tools 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.
Unit 1: Considering the Possibilities of Teaching Statistics with Data
This unit focuses on what statistics is and why it is taught in schools. This unit explores the possibilities of students engaging with real data and cool tools and of teaching statistics with data. You can engage with exciting readings and videos, use a web-based tool for exploring data, and engage with conceptual assessment items that may help you consider how students can be expected to reason with statistics.
Unit 2: Engaging in Statistics
This unit takes a careful look at what it means to engage in statistics. This includes examining the difference between mathematics and statistics, learning the statistical investigation cycle, and considering habits of mind when working with data, and watching as a teacher engages students in a statistical investigation. You will analyze mathematical and statistical tasks, explore additional web-based tools for data exploration, and extend your learning with online resources for data sets and lesson plans.
Unit 3: Introducing Levels of Statistical Sophistication
This unit explores a framework for supporting growth in students' statistical sophistication and digs deeper into statistical habits of mind. You will learn about a statistical task framework to design, adapt, and analyze instructional tasks and explore students' levels of statistical sophistication. We will offer some additional tools for data exploration and resources assisting in the teaching of statistics.
Unit 4: Delving Deeper into the Investigation Cycle
This unit provides teaching and learning materials to assist you in understanding the different components of a statistical investigation, including several resources that can be used directly with students. You will use data from the Census at School project using your favorite data tool and investigate students’ reasoning.
Unit 5: Putting It All Together
This unit considers how to change teaching practices that can really engage students in doing statistics with real data. You will reflect on, assess, and share what you have learned throughout the course, provide feedback for the work posted by colleagues, and contribute ideas for improving the MOOC-Ed.
Obtaining a Certificate of Completion
A certificate of completion for 20 hours of professional development will be provided to participants who do the following in each unit:
- Access and engage with all materials on the Engage with Essentials page.
- Complete the Investigate and Discuss; this includes engaging in activities and participating in the discussion forum.
- Post at least one discussion or comment in the Discuss Learning and Practices.
- Complete the end-of-course survey.
You can submit the certificate to your local agency with a request for Continuing Education Units (CEUs). Granting of CEUs will be subject to the policies and procedures of your state and local agency.
There are also opportunities to participate in performance assessments to demonstrate your competency with ideas presented in the course and apply them to your educational practices. These performance assessments, called micro-credentials, can allow you to earn additional CEUs. Our Teaching Statistics micro-credentials are portable and stackable. Once you demonstrate a competency and earn a micro-credential, you will receive a certificate and a virtual badge recognizing your accomplishment. We have created two stacks of micro-credentials that are purposefully stacked to help support you as you deepen your knowledge and competence in specific areas of teaching statistics. Each micro-credential can help you earn 0.5-0.75 CEUs. Note that you can earn CEUs by successfully completing any of the six Teaching Statistics micro-credentials, even if you choose to not complete the requirements for the 20-hour certificate.
Dr. Hollylynne S. Lee
|Dr. Hollylynne S. Lee is a Professor of Mathematics and Statistics Education in the department of Science, Technology, Engineering, and Mathematics Education at NC State. Her work focused on statistics education, spanning 17 years, began with developing the Probability Explorer software and conducting research on learners' ability to reason about probabilistic phenomena through a simulation approach. Her current work focuses on preparing teachers of statistics to use innovative approaches and powerful technology tools to engage learners in building statistical understandings. Her work has led to numerous books, research publications, and awards. In 2013, she was named a NC State University Faculty Scholar and received an Alumnae Association Outstanding Teacher award in 2014. She is a two time awardee of the National Technology Leadership Initiative Fellowship (2002, 2012), co-sponsored by the Association of Mathematics Teacher Education [AMTE] and the Society of Information Technology and Teacher Education. Dr. Lee is currently a member of the Technology Committee for AMTE and the Research Advisory Board of the Consortium for the Advancement of Undergraduate Statistics Education. She is the editor of Statistics Education Web: An Online Journal for K-12 Statistics Lessons, an associate editor of Statistics Education Research Journal, and a member of the editorial board for Mathematical Thinking and Learning.|
Dr. Dung Tran
|Dr. Dung Tran is a lecturer in the College of Education at Victoria University in Melbourne, Australia. Prior to joining VU, he was a Postdoctoral Research Associate at the Friday Institute for Educational Innovation at NC State University, where he worked on the development of several MOOC-Eds and research on teacher education of statistics as well as the teaching and learning of statistics. His interests focus on mathematics curriculum development, more specifically the impact of mathematical modeling and learning trajectories in curriculum design on student learning, with statistics being the focal content area. He has extensive experience in curriculum analysis and development at the middle and high school levels, conducting extensive clinical interviews with elementary children, and analyzing a diversity of both quantitative and qualitative data. He taught both mathematics and methods courses for preservice high school mathematics teachers at Hue University College of Education in Vietnam for five years. A native of Hue city, Vietnam, he earned a B.S. in Mathematics and an M.Ed. in Mathematics Education in Hue University College of Education. He graduated from the University of Missouri - Columbia with a Ph.D. in Mathematics Education and a Ph.D. Minor in Statistics.|
|Dr. Gemma F. Mojica is a Research Associate at the Friday Institute for Educational Innovation. Her current work focuses on instructional design, content development and research for the Institute's current series of Mathematics MOOC-Eds. She joined the Math MOOC-Ed team in Fall 2016. She earned her B.S. in Mathematics at East Carolina University, and she earned her M.S. and Ph.D. in Mathematics Education, with a minor in Statistics, from NC State University. Her previous professional experiences include teaching mathematics at rural and urban secondary public schools in North Carolina. She has also taught mathematics methods courses and mathematics content courses for elementary and secondary prospective and practicing teachers, as well as other mathematics education courses for both undergraduate and graduate students. Her research interests include designing and exploring the types of experiences in teacher education and professional development that support teachers in creating learning environments that supports students' mathematical thinking.|
Dr. Jennifer N. Lovett
|Dr. Jennifer N. Lovett completed her Ph.D. in Mathematics Education in 2016 from NC State University. Prior to starting the program and joining the team, she taught algebra and geometry for seven years in the suburbs of Cincinnati, Ohio. Currently, she is an Assistant Professor of Mathematics Education at Middle Tennessee State University. Her research interests lie in helping teachers incorporate technology into their teaching and preparing mathematics teachers to teach statistical thinking.|
|Alex Dreier is the Instructional Design Lead at the Friday Institute for Educational Innovation at NC State University's College of Education. His current work focuses on the instructional design and content development for the Institute's current series of MOOC-Eds. Prior to joining the Institute, Alex managed the online training courses for EdTech Leaders Online, a nationally recognized online professional development organization housed at Education Development Center, Inc., in Waltham, MA. Among the courses that Alex helped update and maintain were Using Real Data in the Math Classroom, Using Technology in the Elementary Classroom, and A Conceptual Introduction to Function: Using Visual Models. He holds a B.A. in Psychology from Tulane University and an Ed.M. from the Harvard Graduate School of Education.|
|Theresa Gibson is a Project Coordinator at the Friday Institute for Educational Innovation. She earned her B.S. in Mathematics and in Mathematics Education at Buffalo State College in NY. She has experience teaching algebra and geometry to students in Grades 8-12 and in academic intervention for mathematics working with students in Grades 6-12. Theresa also worked at the community college level as a developmental mathematics instructor. Prior to joining the research team, she worked as a program manager in a Title I program to provide tutoring in mathematics and reading to K-8 students throughout North Carolina, South Carolina, and Virginia. In her role as project coordinator, Theresa is interested in providing high-quality, accessible resources to educators and supporting a positive relationship with mathematics for both educators and students.|
|Christine Franklin is a senior lecturer and Lothar Tresp Honoratus Honors professor at the University of Georgia. Learn more about Christine Franklin.|
Dr. Susan Friel
|Dr. Susan Friel is a professor of Mathematics Education at the University of North Carolina at Chapel Hill. Learn more about Dr. Susan Friel.|
Dr. Webster West
|Dr. Webster West is currently on the faculty at North Carolina State University as a Statistics professor. Learn more about Dr. Webster West.|
- Self-directed learning, through personalizing your experience by identifying your own goals, selecting among a rich array of resources, and deciding whether, when, and how to engage in discussions and activities to further your own learning and meet your goals.
- Peer-supported learning, through engaging in online discussions, reviewing your colleagues' projects, rating posted ideas, recommending resources, crowdsourcing lessons learned, and participating in twitter chats and other exchanges appropriate to the individual course.
- Job-embedded learning, through the use of case studies, classroom and school related projects; developing action plans; and other activities that center your work on critical problems of practice and data-informed decision-making in your own classrooms, schools or districts.
- Multiple voices, through learning about the perspectives of other teachers and administrators along with those of students, researchers and experts in the field. Our courses are purposefully not designed around one or two experts who present online lectures. They provide exposure to a rich set of perspectives presented within the context of course elements that reflect these core principles.
You will see these design principles implemented in our courses through the following instructional elements:
- Conceptual Frameworks
- Resource Collections
- Asynchronous Discussions and Twitter Chats
- Student Scenarios
- Expert Panels
- Participant Projects and Peer Feedback
- Professional Learning Community (PLC) Guides
|Future Start Date(s)||
Grade 6-12 Teachers
Hollylynne Lee, Ph.D.
Gemma Mojica, Ph.D.
Teaching Statistics Through Inferential Reasoning
Micro-credentials (Learn More)
|Teaching Statistics: Understanding the SASI Framework|
|Teaching Statistics: Statistics Task Design|