This is a session of Topic 3: Learning to teach statistics
(Monday 12th, 11:00-12:30)
Learning to teach data-based statistics at school and tertiary level
- Gail Burrill (United States)
AbstractNational and state standards and frameworks such as GAISE identify central statistical content that school and tertiary students need to learn to be productive citizens and workers. Research indicates, however, that many students master technical skills but are unable to use these skills in meaningful ways with little opportunity to design experiments, analyze data and connect the analysis with statistical reasoning. As a consequence, students have little understanding of the basic principles underlying data analysis and are unable to use statistics in their continued studies at the tertiary level and in their everyday and professional lives. This session will consider ways to meet this challenge by focusing on topics such as:
- why is a data based approach important for students?
- what do we know about using data that supports learning?
- what scaffolding is necessary to provide students with the background to understand and reason in sense-making ways about data?
- what is the role of technology in developing understanding of data and how can we effectively help teachers learn to use technology to make this happen?
- what attitudes and stances towards data analysis should teachers have to enable them to impart statistical ways of reasoning and thinking to their students.
|Presenter(s) / Author(s)
|Towards evaluation criteria for coherence of a data-based statistics curriculum
|Anneke Verschut (The Netherlands)
Arthur Bakker (The Netherlands)
|Some issues of data production in teaching statistics
|Carl Lee (United States)
|Models of teacher preparation designed around the GAISE Framework
|Christine Franklin (United States)
Gary Kader (United States)