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GAISEing into School Level Statistics and Data Science

Updated: Aug 29, 2023

Christine (Chris) Franklin is the ASA K-12 Statistics Ambassador, an ASA Fellow, and UGA Emerita Statistics faculty. She is the co-author of two introductory statistics textbooks, chair for the ASA policy documents Pre-K-12 GAISE (2005) and Statistical Education of Teachers (2015), and co-chair for the recently published Pre-K-12 GAISE II. She is a former AP Statistics Chief Reader and a past Fulbright scholar to NZ. Chris welcomes opportunities to collaborate and share her love of statistics and data science with teachers and teacher educators. She is ‘crazy’ about running, hiking, scoring baseball games, reading mysteries, and spoiling her grandson Henry. To learn more about Chris’ work with the American Statistical Association, visit: ASA K-12 Ambassador

As I write this blog entry, it was a year ago the world entered into a shutdown due to COVID-19, experiencing the first pandemic in a hundred years. As we are still grappling with coming out of the pandemic and coping with the disruptions in our lives, the pandemic has undeniably highlighted that being able to understand and reason with statistical information is more important than ever. I earnestly believe it is imperative that all students graduate from secondary school prepared to work and live in a data-driven society. Developing statistical reasoning skills must begin with students in the early grades and evolve throughout middle and secondary school.

Some Historical Perspective

Most people believe integrating statistics into the school curriculum is a recent phenomenon; however, the recommendation of introducing statistical thinking into the US school level curriculum began as early as the 1920’s with a 1923 Mathematics Association of America (MAA) curriculum publication, The Reorganization of Mathematics in Secondary Education. There have been efforts throughout the decades since then advocating that statistical thinking has more of a school level presence. To read more about these efforts, The Statistical Education of Teachers outlines a brief history in Chapter 9. It was with the publications of the NCTM Standards documents, Curriculum and Evaluation Standards for School Mathematics (1989) and Principles and Standard for School Mathematics (2000) that states began to seriously consider statistics standards within school level mathematics. To support these NCTM documents, ASA published in 2005 The Pre-K-12 GAISE Framework (revised in 2020) along with the College GAISE guidelines (revised in 2016) for the Introductory Statistics course. The Pre-K-12 GAISE significantly impacted the inclusion of statistics standards in the Common Core curriculum. The Pre-K-12 GAISE has also been used extensively in research – it has been cited over 850 times according to Google Scholar. It is this research that significantly informed the updating of the original Pre-K-12 GAISE.

It was also during the 1990’s and 2000’s that AP Statistics was introduced, established a firm footing in the high school curriculum, and grew each year in popularity. As Roxy Peck elegantly wrote about AP Statistics and the college introductory statistics course in the Stat Medic blog article, AP Statistics – Where We Need to Go From Here, “Emphasizing the importance of communication and the development of conceptual understanding through the use of simulation, AP Statistics was a leader, and colleges slowly followed suit.” Dedicated teachers and leaders in the AP Statistics community were successfully building the course as a prototype for developing students into statistical thinkers – implementing the recommendations of the two GAISE reports. As I reflect on the period from 2000 into the decade of 2010’s, I have often felt that the success of the AP Statistics course caused states and schools to default to AP Statistics as the way to integrate statistics into the school level, not the K-12 curriculum where all students are enrolled. The consequence of this has been that only a relatively small group of students receive an enriched exposure that supports their development as a statistical thinker.

As Roxy further stated in her post, “We can stop patting ourselves on the back! As the college courses changed, AP Statistics became the follower. With the focus on trying to maintain complete alignment with whatever the dominant college course looks like, there seems to be a hesitancy to innovate.”

Where Are We Today

Much has changed since AP statistics was developed. Our data-driven world is demanding that all students and members of society become data savvy. The types of data are no longer simply traditional measurements classified as categorial or quantitative. Data are also nontraditional such as photos, sounds, and text messages. We no longer only design studies that result in primary data based on sampling small samples from a larger population or randomly assigning treatments in experimental studies.

With the massive amount of secondary data now available, it is becoming more common for researchers to consider data that has been collected for other purposes. The researcher considers the secondary data to answer newly formulated statistical investigative questions. Computational ability has changed the dynamics of statistical analysis resulting in an evolution to what we now call data science. Using large data sets of secondary data for predicting and classifying are becoming commonplace, but these data can be messy and need ‘cleaning’. Given all of this, it is more important than ever that our students question the design of the study, to interrogate the data asking if the data are appropriate for answering the statistical investigative question, and evaluating the appropriateness of the conclusions.

The statistical problem-solving process (formulate statistical investigative questions, collect/consider data, analyze the data, and interpret the results) remains core to statistical reasoning. Technology allows visualizations beyond traditional dotplots, boxplots, scatterplots, and bar graphs. Given the abundance of data, students will naturally be asking investigative questions that require multivariate thinking.

GAISEing into the Future

The Joint ASA-NCTM committee recognized that it was time to update the Pre-K-12 GAISE document to reflect the changing nature of data and the skills needed to become data and statistically literate. Pre-K-12 GAISE II was released in November 2020. GAISE II maintains the spirit of the original Pre-K-12 GAISE but enhances the original framework:

  • To acknowledge the changes in computing

  • To recognize the important role of questioning throughout the statistical problem-solving process

  • To encourage the use of non-traditional data and multivariate thinking starting in the early grades

  • To highlight the connections to other fields such as science, while still maintaining the importance of communication.

Two examples from GAISE II that illustrate these enhancements can be found in a post at Allan Rossman’s outstanding blog, Ask Good Questions.

Several states are in the process of revising their school-level math standards and frameworks (e.g., Oregon and California) or states that recently released revised standards (e.g., Tennessee, Alabama, and Georgia). There appears to be a momentum building among K-12 educational leaders of the important role data plays in our lives and that revised state math curriculums must include more standards related to statistics and data science starting in the early grades. Statistical reasoning is challenging and it takes time to time to develop. If we are wanting ALL students to leave secondary school with these skills, we need to start early and nurture over time through all the grades. Even AP Statistics students need to start early – we can’t expect one course to accomplish the goal of mature statistical reasoning. We are also witnessing states adding high school elective courses and high school pathways in statistics and data science. Both the Pre-K-12 GAISE II document and the NCTM Catalyzing Change books are full of recommendations. Just as Roxy’s hope is that AP Statistics will become a partner with post-secondary in creating a course that is more modern, my hope is that AP Statistics teachers and leaders will partner with the K-12 educational leaders to create a seamless statistics and data science curriculum where students begin developing statistical thinking in the early grades, evolving through the secondary level, and finishing with a relevant AP Statistics course. AP Statistics teachers in my opinion are key to shepherding and making this happen!

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