The Power of Data: How to Use Computational Thinking to Engage Students

The role and importance of trusted data in a global pandemic

SOURCE: Discovery Education

DESCRIPTION:

By Pedro Delgado, 15 years teaching experience, 7th grade science and computer science 1 and 2 at Young Women’s STEAM Research & Preparatory Academy, Ignite My Future in School Learning Leader
 

In the modern workforce, professionals use a variety of skills to solve problems. It’s uncommon that a task would be siloed to one specific subject – instead, we tend to take a transdisciplinary approach, using skills from various areas.

This is why more educators are working to incorporate computational thinking – the thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer in the anywhere classroom.

Computational thinking strategies equip students with problem-solving skills, such as analyzing data, in order to make inferences and break problems down into manageable pieces. This transdisciplinary mode of instruction ensures learners are prepared to tackle real-world problems both today and in their future careers.

Ignite My Future in School, a program from Tata Consultancy Services (TCS) and Discovery Education, provides no-cost transdisciplinary resources designed to equip students with the foundations of computational thinking.

Through a series of blogs, we’re going to leverage resources from Ignite My Future in School to explore how computational thinking relates to modern issues, and how to use it to engage students and equip them with skills for future success.

In this post, we’ll examine the role and importance of collecting and analyzing data and how it applies to crises like the COVID-19 outbreak.

Let’s review the seven computational thinking strategies:

  • Collect Data: Determine sources from which you will collect data, and decide which qualitative and quantitative data to collect.
     
  • Analyze Data: Produce and evaluate charts, and use appropriate statistical methods to test a hypothesis.
     
  • Find Patterns: Identify patterns to make predictions, create rules and solve other problems.
     
  • Decompose Problems: Take large complicated problems, and break them down into manageable pieces.
     
  • Abstract: Identify similarities and remove details to create a solution that works for many different problems.
     
  • Build Models: Test, tweak and refine an object before building it in real life using design software to predict outcomes.
     
  • Develop Algorithms: Create solutions using step-by-step instructions that operate like a road map for performing a task.

Collect Data

Collecting data is an essential skill necessary for the problem-solving process. This computational thinking skill engages students by helping them understand the role data play in solving current and future problems.

Reflect. How comfortable do you feel…

  • Explaining how data collection can help break down complex problems?
     
  • Identifying opportunities for students to express their content knowledge by collecting data?
     
  • Providing multiple examples of how data collection impacts you and your students’ lives?

Collecting data starts with identifying a problem, and then conducting research to come up with a solution. It’s crucial that we remain conscious of how bias can impact data collection. Bias can live in every part of the research process, including how we ask questions and how we interpret results. Computational thinking teaches students how to minimize bias by testing and refining each step in the research process.

Data is generally categorized into two main types, each using different collection methods:

  • Quantitative: Specific and measurable, such as distance, time, temperature and cost.
     
  • Qualitative: Not measurable, provides perspective, meaning and context, such as interviews, focus groups and field studies.

Collecting data empowers students to act as investigators, using curiosity and creativity to look at the world in new ways.

Analyze Data

By analyzing data, we can identify connections between things or people. This computational thinking strategy helps our students understand, make meaning of and predict real-world outcomes.

Reflect. How comfortable do you feel…

  • Explaining how data analysis can help break down complex problems?
     
  • Identifying opportunities for students to express their content knowledge by analyzing data?
     
  • Providing multiple examples of how data analysis impacts you and your students’ daily lives?

From charts and coordinates to emails and spreadsheets, there’s no shortage of data in today’s day and age. It’s crucial that students are prepared to navigate the information available to them.

Computers were created to help us collect and analyze large amounts of data. Data helps us make sense of the world and make decisions, but if we don’t know how to properly analyze data, it’s easy to become overwhelmed. By analyzing data, we can identify connections between things or people, understand how one event caused another to happen and predict future occurrences.

The ability to analyze data helps students understand big issues, spot patterns and drill down into the most important parts of a problem. It’s also an important component of virtually any career path.

Collecting and Analyzing Data During COVID-19

Data becomes especially crucial when the world is dealing with a crisis, such as the COVID-19 pandemic. Experts from Centers for Disease Control and Prevention (CDC), healthcare organizations and researchers are working tirelessly to understand the COVID-19 virus, and come up with sound solutions for combatting it.

Rather than exclude what’s happening around us, let’s work to include real-world examples as we teach students. For example, in “Outbreak”, a computational thinking activity from Ignite My Future, students learn how scientists use computational thinking skills to combat virus outbreaks.

Students are presented with an outbreak scenario, and act as public health analysts to determine a solution.

During this lesson, students utilize the computational thinking strategy of collecting data to construct questions relating to the spread of the virus outbreak, and learn the difference between qualitative and quantitative data, and why each form of data is valuable to the research process. They’ll analyze data to understand how viruses spread, and use the information they collected to create a flowchart designed to identify and stop a spreading virus.

You can find the full Outbreak lesson plan here.

Trusted data is invaluable.

Computational thinking goes way beyond computers. Without the computational thinking skills of collecting and analyzing data, we wouldn’t be able to find reliable, research-based solutions to our problems. By introducing students to these concepts early, we are preparing them for bright futures where they can combine creativity with computational skills for ultimate innovation and success.

To learn more about Ignite My Future in School, please visit https://www.ignitemyfutureinschool.org/

Tweet me: New school year = time to start planning for the future. Explore free, virtual resources from @tcs_na & @DiscoveryEd #IgniteMyFuture that dive into career readiness through videos profiles, digital lessons, and more! Discover more from: ignitemyfutureinschool.org

KEYWORDS: NYSE:DISCA, Tata Consultancy Services, discovery education, Computational Thinking, Ignite My Future in School, COVID-19

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