• University of Glasgow

Getting Started with Teaching Data Science in Schools

Learn the basics of data science and how to introduce data science in the classroom.

1,168 enrolled on this course

Getting Started with Teaching Data Science in Schools
  • Duration3 weeks
  • Weekly study3 hours

Learn practical ways to teach data science

Understanding how to use and interpret data will be essential for the next generation, but many schools and teachers aren’t equipped to teach basic data science to students. This course will help you introduce data science in the classroom so that your students are prepared for the future.

You will get an introduction to useful tools for exploring data, learn the basics of statistics and explore how you can embed data activities into your teaching plans. You will get hands on experience interpreting real data so that you feel comfortable helping students get started with data science.

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Skip to 0 minutes and 12 seconds Lovisa: Humanity generates more than two exabytes of data per day. That’s around two billion gigabytes, or hundreds of megabytes per person.

Skip to 0 minutes and 22 seconds Jeremy: At the lowest level, data is just electronic signals, ones and zeros, travelling along wires like this network cable or maybe stored on silicon chips. Data science is all about converting this low level information into high level insight, stuff that might change the world.

Skip to 0 minutes and 44 seconds Catherine: Open data allows us to share knowledge across disciplines, occupations, and methods. It allows us to create communities of open data practice and to better answer the pressing social questions of our time.

Skip to 0 minutes and 56 seconds Lovisa: Citizen Data Science is a force for good. It empowers you to investigate things that matter to you and use data to have a positive impact on your community.

Skip to 1 minute and 7 seconds Jeremy: Data relevant to your community may be collected by individuals, private organisations, or governments. For instance, think about traffic data, whether it’s car tax databases or air pollution monitoring or perhaps, lists of local potholes in your roads that need fixing. All of this data is relevant for citizen data science, and lots of it is available online for you to use.

Skip to 1 minute and 33 seconds Lovisa: You don’t need a supercomputer to do data science. In fact, you only need an ordinary computer and a web browser.

Skip to 1 minute and 40 seconds Jeremy: Whatever your subject, data is integral to it. You can embed data activities into all kinds of topics and projects– history, geography, modern studies, PE, religious education, psychology. You name it, data is involved.

Skip to 1 minute and 55 seconds Catherine: Research centres like the Urban Big Data Centre in Glasgow are working to make data more open and integrated for you to use. From cycling up data and social media data to GPS and satellite images, we’ve got data for you to use to help you explore the world around you.

Skip to 2 minutes and 11 seconds Lovisa: This course has been designed for the Centre of Computing Science Education and School of Education at University of Glasgow. It combines user friendly technology with research led, educational expertise.

Syllabus

  • Week 1

    First Steps in Data Science

    • Why is data important?

      Data is all around us. Each citizen is generating megabytes of data every second. Why should we care? What does this data look like, and what might we do with it?

    • Getting into data

      How can we process data using code? What are the basic steps in data science?

    • Reflective thinking

      Now we know a little about data science, why is it so important? Why should we be teaching data science in schools?

  • Week 2

    Understanding your Data

    • Visualizing data

      How do we create higher-level graphical summaries of our data?

    • Interpreting your data

      After all the analysis you have done, what can you learn from your data?

    • Taking things further

      Think about embedding data visualization and interpretation into your classroom learning activities.

  • Week 3

    Your Very Own Data Project

    • Preparing for your Mini-Project

      This is mini-projects week. Now you are going to work on your own data science investigation. First you need to identify an interesting research question and a relevant data set.

    • Carrying out your Data Investigation

      Apply the tools and techniques you have learned about during the course as you perform your investigation.

    • Reporting your Findings

      What did you discover? How can you inform people about the results of your mini-project investigation?

When would you like to start?

  • Date to be announced

Add to Wishlist to be emailed when new dates are announced

What will you achieve?

By the end of the course, you‘ll be able to...

  • Apply computational tools and techniques to topical open data sets
  • Explore large real-world data sets through computer-generated visualizations
  • Reflect on the value of data analytics, and the implications for society
  • Justify topical opinions based on evidence drawn from relevant data sets
  • Identify how data literacy tasks can be incorporated into school learning activities

Who is the course for?

This course is primarily for school teachers, but it might also be of interest to parents looking to teach their children about data science.

Who will you learn with?

I am a lecturer in Computing Science at the University of Glasgow. I am moderately fluent in the following languages: Haskell, Java, C, Scouse and New Testament Greek.

  • http://dcs.gla.ac.uk/~jsinger

I am a lecturer in CS Education at the University of Glasgow. Passionate about the power of education in transforming students lives and fluent in Python, Scratch & Auld Scots!

I am a PhD-student at the University of Glasgow investigating ways of improving the teaching of data scientific programming

Who developed the course?

The University of Glasgow

Founded in 1451, the University of Glasgow is the fourth oldest university in the English-speaking world. It is a member of the prestigious Russell Group of leading UK research universities.

  • Established1451
  • LocationGlasgow, Scotland, UK
  • World rankingTop 70Source: QS World University Rankings 2020

Supporters

funded by

The Data Lab

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