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Amplifying Statistics and Data Science in Classrooms

For those wanting to learn more about statistics and data science, Hollylynne Lee’s Amplifying Statistics and Data Science in Classrooms is a new set of free modules created in The PLACE that help educators:

  • Develop strategies for using an investigation cycle to teach statistics and data science
  • Ignite students’ interest in real-world data investigations with technology
  • Emphasize inferential reasoning by posing different types of investigative questions

Tui

This citizen science project aims to collect data about which birds and how many are in your backyard. This is done once a year during a particular window of time, usually for one week starting at the end of June, and the results contribute to New Zealand’s knowledge and monitoring of garden bird species and the health of the environment we live in.

Get involved! Visit The Science Learning Hub with ready-made resources.

Thank you for helping make today our biggest CensusAtSchool launch ever!

1,871 teachers registered
1,010 schools registered
1,877 students took part today

We look forward to a big day tomorrow. The survey remains open until the end of 2022.

We are proud to announce our new live dashboard. See if your school is one of the highest participating schools and fun stats coming in as students take part!

Need help exploring data using technology in your teaching and learning?

Catch up on the latest professional development for Data Science. These webinars are a great starting point to help structure and support STEM opportunities for your colleagues and students.

Data Science Education Meetups

Recommend starting with: What Kinds of Questions Do Students Generate as They View Data Visualizations?

“Thinking about questions makes me think of more questions.”

Ihaka Lecture Series 2021

For a general audience (with an interest in Statistics and/or Computing)

Learn more

Register for (free) in-person attendance

10 March at 6:30pm

Data Science in the Connected Era
Dr Simon Urbanek, Senior Lecturer, Department of Statistics, University of Auckland

17 March at 6:30pm

Implementing a Machine-Learning Tool to Support High-Stakes Decisions in Child Welfare: A case study in Human Centred AI
Professor Rhema Vaithianathan, Centre for Social Data Analytics, AUT

 

24 March at 6:30pm

Modelling to support the COVID-19 response in Aotearoa New Zealand
Dr Rachelle Binny, Manaaki Whenua-Landcare Research and Te Pūnaha Matatini

Data-Driven Art

Data-Driven Art

One of ODI’s NSF-funded projects, Building Students’ Data Literacy through the Co-design of Curriculum by Mathematics and Art Teachers, is creating learning experiences for middle school students which integrate data science with art.

This past spring, the project researchers conducted a classroom pilot study of a 3-week long unit in collaboration with a math and art teacher pair. The study’s goals were to explore how students use mathematics and art to describe and make claims from data, and to examine the concepts and skills in visual arts, mathematics and data literacy evident in their work. The unit—co-designed with teachers—guided students in two data-based inquiry activities. One activity focused on collecting and using data to describe their experiences during the pandemic, and the second focused on exploring data on teen use of social media collected by Pew Research. Both activities culminated in the creation of art pieces based on the data they analyzed.

Our Data Pathways Community of Practice—for colleges and community colleges building data programs—has more than 25 members and is meeting virtually on a monthly basis.
Join the Community of Practice
Initial results from the students’ culminating art projects suggest that students were engaged in thinking about the patterns in the data, what they meant in context, and how to represent them through art. However, students varied in the extent to which they connected both their inferences and artistic choices to the data evidence, sometimes drawing on personal experience to make inferences, rather than the data, and results from the study suggest students needed more careful scaffolding for making data-based inferences. In the top left example below, a student drew a representation of how many people they saw in the last 5 days of the pandemic and included a key to understanding the data. In the top right exhibit, the yarn represents the percentage of teens who use social media, based on data from the Pew Research survey. And in the bottom left image, a student created a 3-D abstraction of the same Pew data (on teen internet use) using more colorful crayons to represent the teens who use the internet, and using structure to represent the student’s claim that teens who don’t use the internet are more organized and focused.
Due to the pandemic, the research team wasn’t able to pilot test in as many classrooms as they had originally planned, but they were able to adapt the units for online and asynchronous use, using the Web-based Inquiry Science Environment (wise.berkeley.edu) platform. And in this school year, they are working with art and math teachers from four middle schools to build on last year’s findings, and codesign and pilot more arts-integrated data literacy units. This year they hope to incorporate dance as well as visual arts. (Aren’t you curious about dancing to data?!)

We don’t know the form the modules will take this year given the pandemic, but the team is developing curricula designs and plans that are flexible enough to adapt to the different teacher and student contexts—a challenging process, as school circumstances are changing rapidly.

Wishing you and yours a happy, healthy holiday!

Randy Kochevar
Director, ODI

Last week the University of California sent a momentous email to 20,000 high schools announcing that they would now accept data science as an alternative to algebra 2 – this has huge implications for schools & students. Read the full announcement

The ZDM special issue on Innovations in statistical modelling to connect data, chance and context is now freely available (open access) during October.

It would be great, if you could distribute the news via your networks.

https://www.springer.com/journal/11858/updates/18235366