One of the more ambitious goals of the Callysto project is to improve the computational thinking and digital literacy skills of Canadian teachers and students through the use of our platform. Assessing these skills, and determining if there have been any signs of improvements, is no easy matter. This is why we’ve teamed up with Cathy Adams, professor of education and Vargo teaching chair, and her team at the University of Alberta to run some before-and-after assessments of participants.
Now you may be wondering: what is computational thinking?
Essentially, this term describes a way of approaching problems in an analytical, algorithmic manner. It is when people use computational approaches to work step-by-step through a question or dilemma. (For example: I’ve been asked to bring snacks to a party. Some of the questions I could run through are: How many people will be there?, What kind of snacks would be appropriate?, Does anyone have any food allergies I should be aware of?, If I’m bringing perishable food, what time should I pick it up before the party, and how will I store it?, etc).
Why is it important for Canadians to develop their computational and data literacy skills?
Well for starters: as the world’s information sources grow more complex, and people are inundated with contrasting data, it’s important for us to have the means to sort fact from fiction, without relying on others to tell us what is correct or incorrect. As young people prepare to enter the workforce, they will need to have creative problem-solving skills that enable them to thrive in workplaces that, more and more, rely on machines and Artificial Intelligence.
But now for the tricky bit of the Callysto objective: in order to assess improvements in computational thinking, you first need to figure out how a person thinks, full-stop, and see if this changes over time.
Professor Adams and her colleagues have been assessing the impact of digital learning tools on the reasoning abilities of students for several years. For the Callysto initiative, they have created a list of questions that get participants to think about, well, how they think.
“We give context in our survey to help participants consider how they would normally approach solving a problem, such as planning a birthday party,” says Adams.
The survey then invites participants to solve a series of coding and problem-solving questions, sometimes asking them to explain how they came to their final solution.
“We’re not necessarily looking for people to go from incorrectly solving a coding problem to finding the correct solution, but rather, we want to see if the process they are using to solve a problem has changed over time.”
For example, when presented with a question of probability (a topic that some people, including myself, may not remember from their school days), a pre-Callysto participant may randomly guess at an answer. But after working with the Callysto platform, and using its coding or data analytics capabilities, the participant may find themselves taking a more logic-based approach to the problem (saying: “well, first we need to know A before we can look at B, and these are the steps we would need to take to determine A”).
So, what difference will this assessment make?
Determining if Callysto’s users have actually improved their data literacy or computational thinking skills, or at least have changed the way they approach a problem, will go a long way in helping educators build new learning resources to educate our youth. With provinces such as Alberta now adding computational thinking to their schools’ curriculum, everyone in the education space will need to figure out the best way to actually teach these skills!
We, therefore, invite any Alberta teachers or students interested in Callysto and willing to participate in this computational thinking assessment to fill in this form, and our researchers will approach your school district to get the approvals necessary to move forward. We are hoping to have at least 150 teachers and students take part, to provide a good group picture that we can then take back to education leaders.
It’s the logical first step in improving Canada’s computational thinking skills!