Topic 2 The structure of information and computational thinking for young audiences, through engaging activities

Computational thinking (CT) is described as the use of abstraction, automation, and analysis in problem-solving. It is a term that describes a set of thinking skills, habits and approaches that are integral to solving complex problems using a computer and widely applicable in the information society. Thinking computationally draws on the concepts that are fundamental to computer science, and involves systematically and efficiently processing information and tasks (Lee at al., 2011).

Computational Thinking (CT) has been described as an essential skill which everyone should learn and can therefore include in their skill set. Seymour Papert is credited as concretising Computational Thinking in 1980 but since Jeannette Wing popularised the term in 2006 and brought it to the international community’s attention, more and more research has been conducted on CT in education. Jeannette Wing, a professor of computer science at Carnegie Mellon University, discussed computational thinking as “a way of solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science.” (National Research Council, 2010).

Computational Thinking (CT) is a problem-solving process that includes (but is not limited to) the following characteristics (Bocconi et al., 2016):

  • Formulating problems in a way that enables us to use a computer and other tools to help solve them;
  • Logically organizing and analysing data;
  • Representing data through abstractions such as models and simulations;
  • Automating solutions through algorithmic thinking (a series of ordered steps);
  • Identifying, analysing, and implementing possible solutions with the goal of achieving the most efficient and effective combination of steps and resources;
  • Generalizing and transferring this problem-solving process to a wide variety of problems.

Computational Thinking been incorporated into already existing subjects/courses

Sabitzer & Paster (2014) present a review on their course called “COOL Informatics” where they hope to show that informatics is “cool” and can be fun and easy. They do this by using CS Unplugged style activities but also going further by using informatics concepts such as algorithms to support learning in a variety of subjects in the curriculum. The “Cool Informatics” approach has several overarching principles which are as follows (also included are some teaching/learning methods): 

  • Discovery – solution based learning, video tutorials, hand’s-on etc.
  • Cooperation – Team and group work, pair programming
  • Individuality – Questioning, competence-based learning
  • Activity – Hand’s on, learning by doing

They have tested this approach on several pilot projects in primary level, secondary level and higher education and they give some case studies of some of these projects.

Examples include Encryption, PowerPoint and Brain-based Programming. Evaluation results in different schools and university indicate that “Cool Informatics” is appreciated by teachers and students as well as being an effective way of teaching. Exercises for discovery and step-by-step learning assist with learning and understanding complex topics.

The following research examines how computational thinking takes shape for middle and high school youth.

Computational Thinking for Youth in Practice

(Computational_thinking_for_youth_in_practice.pdf)

The following resources, including the curated collection of lesson plans, videos, and other resources were created to provide a better understanding of CT for educators and administrators, and to support those who want to integrate CT into their own classroom content, teaching practice, and learning

Exploring Computational Thinking

When watching the following video ask yourself: How does Dagen adapt the activity to support youth in seeing themselves as computational thinkers?

Overview Playing a Game without Rules

Read this article Early Learning Strategies for Developing Computational Thinking Skills and discuss with your peers what strategies could be engaged in young audiences to familiarize them with CT.

Case study

A group of thieves attempted to steal a large piece of construction equipment. While the thieves prepared for most of the basic logistics surrounding the crime, they did not ultimately understand the computational-thinking-based technology at work in the system, and their efforts were ultimately thwarted. In particular, several men attempted to steal a piece of Caterpillar construction equipment by loading it on a truck to haul it away. The equipment had an active condition-based maintenance system within it broadcasting its exact location and condition as the thieves attempted to run off with the machine. They did not get far.

Why did the thieves get caught? (Your answers should be related to computational thinking)

CT describes the thought processes entailed in formulating a problem so as to admit a computational solution involving abstraction, algorithmic thinking, automation, decomposition, debugging and generalization. The definitions of these items are provided in the following Table (Bocconi et al., 2016).

The process of efficient and effective computer use, known as “Computer-like Thinking” or “Computational Thinking”, is seen as a field with the potential to support individual and societal development in our rapidly progressing world. This topic presented basic concepts related to computational thinking that young audiences should get familiar through specific educational practices.