During a recent event at the National Academy of Science, Engineering and Medicine focused on K-12 data science education, Distinguished Professor Hollylynne Lee and Friday Institute for Educational Innovation Senior Research Scholar Gemma Mojica heard repeated calls related to the urgent need to prepare educators who are able to engage students in investigations of real-world issues using data.
There is a national effort, Lee said, to create and implement standalone data science courses within the high school mathematics curriculum as well as better infuse data and statistics within other courses across subjects. However, prospective teachers often have few experiences with data science and statistical content in teacher preparation programs.
“University-based teacher preparation has got to find ways to transform their programs, licensure requirements, courses and faculty preparedness to address this issue now,” Lee said.
Since 2016, Lee and Mojica have been addressing this issue through the National Science Foundation-funded Enhancing Statistics Teacher Education with E-Modules (ESTEEM) project. ESTEEM provides free, accessible tools that allow pre-service middle and high school mathematics teachers to engage with meaningful materials and has been used in courses by more than 70 teacher educators across the country.
They are now expanding this work through the five-year, $2.5 million “Collaborative Research: Enhancing Data Science and Statistics Teacher Education – Transforming and Building Community” project, funded by the National Science Foundation.
‘Our prior work has filled a gap in teacher education by providing high-quality curricular materials. All of our materials have been packaged into learning management systems that faculty can upload into their own courses,” Mojica said. “We will be expanding our materials to incorporate more practices and processes related to data science.”
ESTEEM currently consists of three modules – one related to foundations in teaching statistics and two related to important statistical topics – and incorporates use of the free, web-based Common Online Data Analysis Platform (CODAP) to investigate data. Bill Finzer, senior scientist at Concord Consortium, is a co-principal investigator on the project.
“Our team will work together to expand features and compatibility in CODAP, as well as develop data investigations and other materials to support teachers in learning to teach statistics and data science,” Mojica said.
The project will begin with an investigation of the current systems in undergraduate teacher preparation for teaching data science and statistics, with a focus on identifying problems of practices related to data science and statistics education in teacher education programs.
Future teachers, Lee said, need to experience deep engagement with investigations of real-world issues using data, so they are able to develop their own data and statistical literacies before attempting to engage their students in data investigations.
It is also important, Mojica said, that future teachers learn to use complex, multivariate, messy data to make evidence-based decisions about solving real-world problems and learn to communicate their results, propose actions for solution and even generate new questions for further data investigations.
“Engaging in these practices themselves is necessary for them to be able to design classrooms where they use these approaches to engage their own students in a data investigation process,” Mojica said. “Future teachers need opportunities to develop dispositions like being curious, creative, persistent and resilient when investigating data, which are qualities required in using large, complex data to solve real problems. Developing these characteristics for themselves is a first step in understanding how to support building classrooms where students are encouraged to tap into these qualities to critically think and make decisions from data.”
Pre-service teachers also need to …….