Explore our new free pathway of environmental digital making projects for young people! These new step-by-step projects teach learners Scratch coding and include real-world data — from data about the impact of deforestation on wildlife to sea turtle tracking information.
By following along with the digital making projects online, young people will discover how they can use technology to protect our planet, all while improving their computing skills.
One of the new projects is an automatic creature counter based on colour recognition with Scratch
The projects help young people affect change
In the projects, learners are introduced to 5 of the United Nations’ 17 Sustainable Development Goals (SDGs) with an environment focus:
Affordable and Clean Energy
Responsible Consumption and Production
Climate Action
Life Below Water
Life on Land
The first project in the new pathway is an animation about the UN’s five SDGs focused on the environment.
Technology, science, maths, geography, and design all play a part in the projects. Following along with the digital making projects, young people learn coding and computing skills while drawing on a range of data from across the world. In this way they will discover how computing can be harnessed to collect environmental data, to explore causes of environmental degradation, to see how humans influence the environment, and ultimately to mitigate negative effects.
Where does the real-world data come from?
To help us develop these environmental digital making projects, we reached out to a number of organisations with green credentials:
We asked the team behind the Ecosia search engine, profits from which get invested in sustainability projects, for their guidance on growing trees. You can watch Ecosia software engineer Jessica Greene chat to us on our weekly Digital Making at Home live stream for young people.
We collaborated with the Shuttleworth Foundation who have developed inexpensive electronic tags that can be safely attached to real sea turtles to track their movement. You can watch Alasdair Davies, who is part of this wildlife project, chat to us on another round of our Digital Making at Home live stream for young people.
A sea turtle is being tagged so its movements can be tracked
Inspiring young people about coding with real-world data
The digital making projects, created with 9- to 11-year-old learners in mind, support young people on a step-by-step pathway to develop their skills gradually. Using the block-based visual programming language Scratch, learners build on programming foundations such as sequencing, loops, variables, and selection. The project pathway is designed so that learners can apply what they learned in earlier projects when following along with later projects!
The final project in the pathway, ‘Turtle tracker’, uses real-world data of migrating sea turtles!
We’re really excited to help learners explore the relationship between technology and the environment with these new digital making projects. Connecting their learning to real-world scenarios not only allows young people to build their knowledge of computing, but also gives them the opportunity to affect change and make a difference to their world!
Discover the new digital making projects yourself!
With Green goals, learners create an animation to present the United Nations’ environment-focused Sustainable Development Goals.
Through Save the shark, young people explore sharks’ favourite food source (fish, not humans!), as well as the impact of plastic in the sea, which harms sharks in their natural ocean habitat.
With the Tree life simulator project guide, learners create a project that shows the impact of land management and deforestation on trees, wildlife, and the environment.
Computers can be used to study wildlife in areas where it’s not practical to do so in person. In Count the creatures, learners create a wildlife camera using their computer’s camera and Scratch’s new video sensing extension!
Electricity is important. After all, it powers the computer that learners are using! In Electricity generation, learners input real data about the type and amount of natural resources countries across the world use to generate electricity, and they then compare the results using an animated data visualisation.
Understanding the movements of endangered turtles helps to protect these wonderful animals. In this new Turtle tracker project, learners use tracking data from real-life turtles to map their movements off the coast of West Africa.
Code along wherever you are!
All of our projects are free to access online at any time and include step-by-step instructions. They can be undertaken in a club, classroom, or at home. Young people can share the project they create with their peers, friends, family, and the wider Scratch community.
Visit the Protect our planet pathway to experience the projects yourself.
One of the keys to identifying timely and impactful actions is having enough raw material to work with. However, this up-to-date information typically lives in the databases that sit behind several different applications. One of the first steps to finding data-driven insights is gathering that information into a single store that an analyst can use without interfering with those applications.
For years, reporting environments have relied on a data warehouse stored in a single, separate relational database management system (RDBMS). But now, due to the growing use of Software as a service (SaaS) applications and NoSQL database options, data may be stored outside the data center and in formats other than tables of rows and columns. It’s increasingly difficult to access the data these applications maintain, and a data warehouse may not be flexible enough to house the gathered information.
For these reasons, reporting teams are building data lakes, and those responsible for using data analytics at universities and colleges are no different. However, it can be challenging to know exactly how to start building this expanded data repository so it can be ready to use quickly and still expandable as future requirements are uncovered. Helping higher education institutions address these challenges is the topic of this post.
About Maryville University
Maryville University is a nationally recognized private institution located in St. Louis, Missouri, and was recently named the second fastest growing private university by The Chronicle of Higher Education. Even with its enrollment growth, the university is committed to a highly personalized education for each student, which requires reliable data that is readily available to multiple departments. University leaders want to offer the right help at the right time to students who may be having difficulty completing the first semester of their course of study. To get started, the data experts in the Office of Strategic Information and members of the IT Department needed to create a data environment to identify students needing assistance.
Critical data sources
Like most universities, Maryville’s student-related data centers around two significant sources: the student information system (SIS), which houses student profiles, course completion, and financial aid information; and the learning management system (LMS) in which students review course materials, complete assignments, and engage in online discussions with faculty and fellow students.
The first of these, the SIS, stores its data in an on-premises relational database, and for several years, a significant subset of its contents had been incorporated into the university’s data warehouse. The LMS, however, contains data that the team had not tried to bring into their data warehouse. Moreover, that data is managed by a SaaS application from Instructure, called “Canvas,” and is not directly accessible for traditional extract, transform, and load (ETL) processing. The team recognized they needed a new approach and began down the path of creating a data lake in AWS to support their analysis goals.
Getting started on the data lake
The first step the team took in building their data lake made use of an open source solution that Harvard’s IT department developed. The solution, comprised of AWS Lambda functions and Amazon Simple Storage Service (S3) buckets, is deployed using AWS CloudFormation. It enables any university that uses Canvas for their LMS to implement a solution that moves LMS data into an S3 data lake on a daily basis. The following diagram illustrates this portion of Maryville’s data lake architecture:
Diagram 1: The data lake for the Learning Management System data
The AWS Lambda functions invoke the LMS REST API on a daily schedule resulting in Maryville’s data, which has been previously unloaded and compressed by Canvas, to be securely stored into S3 objects. AWS Glue tables are defined to provide access to these S3 objects. Amazon Simple Notification Service (SNS) informs stakeholders the status of the data loads.
Expanding the data lake
The next step was deciding how to copy the SIS data into S3. The team decided to use the AWS Database Migration Service (DMS) to create daily snapshots of more than 2,500 tables from this database. DMS uses a source endpoint for secure access to the on-premises database instance over VPN. A target endpoint determines the specific S3 bucket into which the data should be written. A migration task defines which tables to copy from the source database along with other migration options. Finally, a replication instance, a fully managed virtual machine, runs the migration task to copy the data. With this configuration in place, the data lake architecture for SIS data looks like this:
Diagram 2: Migrating data from the Student Information System
Handling sensitive data
In building a data lake you have several options for handling sensitive data including:
Leaving it behind in the source system and avoid copying it through the data replication process
Copying it into the data lake, but taking precautions to ensure that access to it is limited to authorized staff
Copying it into the data lake, but applying processes to eliminate, mask, or otherwise obfuscate the data before it is made accessible to analysts and data scientists
The Maryville team decided to take the first of these approaches. Building the data lake gave them a natural opportunity to assess where this data was stored in the source system and then make changes to the source database itself to limit the number of highly sensitive data fields.
Validating the data lake
With these steps completed, the team turned to the final task, which was to validate the data lake. For this process they chose to make use of Amazon Athena, AWS Glue, and Amazon Redshift. AWS Glue provided multiple capabilities including metadata extraction, ETL, and data orchestration. Metadata extraction, completed by Glue crawlers, quickly converted the information that DMS wrote to S3 into metadata defined in the Glue data catalog. This enabled the data in S3 to be accessed using standard SQL statements interactively in Athena. Without the added cost and complexity of a database, Maryville’s data analyst was able to confirm that the data loads were completing successfully. He was also able to resolve specific issues encountered on particular tables. The SQL queries, written in Athena, could later be converted to ETL jobs in AWS Glue, where they could be triggered on a schedule to create additional data in S3. Athena and Glue enabled the ETL that was needed to transform the raw data delivered to S3 into prepared datasets necessary for existing dashboards.
Once curated datasets were created and stored in S3, the data was loaded into an AWS Redshift data warehouse, which supported direct access by tools outside of AWS using ODBC/JDBC drivers. This capability enabled Maryville’s team to further validate the data by attaching the data in Redshift to existing dashboards that were running in Maryville’s own data center. Redshift’s stored procedure language allowed the team to port some key ETL logic so that the engineering of these datasets could follow a process similar to approaches used in Maryville’s on-premises data warehouse environment.
Conclusion
The overall data lake/data warehouse architecture that the Maryville team constructed currently looks like this:
Diagram 3: The complete architecture
Through this approach, Maryville’s two-person team has moved key data into position for use in a variety of workloads. The data in S3 is now readily accessible for ad hoc interactive SQL workloads in Athena, ETL jobs in Glue, and ultimately for machine learning workloads running in EC2, Lambda or Amazon Sagemaker. In addition, the S3 storage layer is easy to expand without interrupting prior workloads. At the time of this writing, the Maryville team is both beginning to use this environment for machine learning models described earlier as well as adding other data sources into the S3 layer.
Acknowledgements
The solution described in this post resulted from the collaborative effort of Christine McQuie, Data Engineer, and Josh Tepen, Cloud Engineer, at Maryville University, with guidance from Travis Berkley and Craig Jordan, AWS Solutions Architects.
The Bebras Challenge is a great way for your students to practise their computational thinking skills while solving exciting, accessible, and puzzling questions. Usually this 40-minute challenge would take place in the classroom. However, this year for the first time, your students can participate from home too!
If your students haven’t entered before, now is a great opportunity for them to get involved: they don’t need any prior knowledge.
Do you have any students who are up for tackling the Bebras Challenge? Then register your school today!
What you need to know about the Bebras Challenge
It’s a great whole-school activity open to students aged 6 to 18, in different age group categories.
It’s completely free!
The closing date for registering your school is 30 October.
Let your students complete the challenge between 2 and 13 November 2020.
The challenge is made of a set of short tasks, and completing it takes 40 minutes.
The challenge tasks focus on logical thinking and do not require any prior knowledge of computer science.
There are practice questions to help your students prepare for the challenge.
This year, students can take part at home (please note they must still be entered through their school).
All the marking is done for you! The results will be sent to you the week after the challenge ends, along with the answers, so that you can go through them with your students.
“Thank you for another super challenge. It’s one of the highlights of my year as a teacher. Really, really appreciate the high-quality materials, website, challenge, and communication. Thank you again!”
– A UK-based teacher
Support your students to develop their computational thinking skills with Bebras materials
Bebras is an international challenge that started in Lithuania in 2004 and has grown into an international event. The UK became involved in Bebras for the first time in 2013, and the number of participating students has increased from 21,000 in the first year to more than 260,000 last year! Internationally, nearly 3 million learners took part in 2019.
Bebras is a great way to engage your students of all ages in problem-solving and give them a taste of what computing is all about. In the challenge results, computing principles are highlighted, so Bebras can be educational for you as a teacher too.
The annual Bebras Challenge is only one part of the equation: questions from previous years are available as a resource that you can use to create self-marking quizzes for your classes. You can use these materials throughout the year to help you to deliver the computational thinking part of your curriculum!
Since 2017 we’ve been training Computing educators in England and around the world through our suite of free online courses on FutureLearn. Thanks to support from Google and the National Centre for Computing Education (NCCE), all of these courses are free for anyone to take, whether you are a teacher or not!
We’re excited that Computer Science educators at all stages in their computing journey have embraced our courses — from teachers just moving into the field to experienced educators looking for a refresher so that they can better support their colleagues.
Hear from two teachers about their experience of training with our courses and how they are benefitting!
Moving from Languages to IT to Computing
Rebecca Connell started out as a Modern Foreign Languages teacher, but now she is Head of Computing at The Cowplain School, a 11–16 secondary school in Hampshire.
Computing teacher Rebecca finds our courses “really useful in building confidence and taking [her] skills further”.
Although she had plenty of experience with Microsoft Office and was happy teaching IT, at first she was daunted by the technical nature of Computing:
“The biggest challenge for me has been the move away from an IT to a Computing curriculum. To say this has been a steep learning curve is an understatement!”
However, Rebecca has worked with our courses to improve her coding knowledge, especially in Python:
“Initially, I undertook some one-day programming courses in Python. Recently, I have found the Raspberry Pi courses to be really useful in building confidence and taking my skills further. So far, I have completed Programming 101 — great for revision and teaching ideas — and am now into Programming 102.”
GCSE Computing is more than just programming, and our courses are helping Rebecca develop the rest of her Computing knowledge too:
“I am now taking some online Raspberry Pi courses on computer systems and networks to firm up my knowledge — my greatest fear is saying something that’s not strictly accurate! These courses have some good ideas to help explain complex concepts to students.”
“I really like the new resources and supporting materials from Raspberry Pi — these have really helped me to look again at our curriculum. They are easy to follow and include everything you need to take students forward, including lesson plans.”
And Rebecca’s not the only one in her department who is benefitting from our courses and resources:
“Our department is supported by an excellent PE teacher who delivers lessons in Years 7, 8, and 9. She has enjoyed completing some of the Raspberry Pi courses to help her to deliver the new curriculum and is also enjoying her learning journey.”
Refreshing and sharing your knowledge
Julie Price, a CAS Master Teacher and NCCE Computer Science Champion, has been “engaging with the NCCE’s Computer Science Accelerator programme, [to] be in a better position to appreciate and help to resolve any issues raised by fellow participants.”
Computer science teacher Julie Price says she is “becoming addicted” to our online courses!
“I have encountered new learning for myself and also expressions of very familiar content which I have found to be seriously impressive and, in some cases, just amazing. I must say that I am becoming addicted to the Raspberry Pi Foundation’s online courses!”
She’s been appreciating the open nature of the courses, as we make all of the materials free to use under the Open Government Licence:
“Already I have made very good use of a wide range of the videos, animations, images, and ideas from the Foundation’s courses.”
With 29 courses to choose from (and more on the way!), from Introduction to Web Development to Robotics with Raspberry Pi, we have something for everyone — whether you’re a complete beginner or an experienced computer science teacher. All of our courses are free to take, so find one that inspires you, and let us support you on your computing journey, along with Google and the NCCE.
In the brand-new issue of Hello World magazine, Shuchi Grover tells us about the limits of constructionism, the value of formative assessment, and why programming can be a source of both joy and angst.
How much open-ended exploration should there be in computing lessons?
This is a question at the heart of computer science education and one which Shuchi Grover is delicately diplomatic about in the preface to her new book, Computer Science in K-12: An A-to-Z Handbook on Teaching Programming. The book’s chapters are written by 40 teachers and researchers in computing pedagogy, and Grover openly acknowledges the varying views around discovery-based learning among her diverse range of international authors.
“I wonder if I want to wade there,” she laughs. “The act of creating a program is in itself an act of creation. So there is hands-on learning quite naturally in the computer science classroom, and mistakes are made quite naturally. There are some things that are so great about computer science education. It lends itself so easily to being hands-on and to celebrating mistakes; debugging is par for the course, and that’s not the way it is in other subjects. The kids can actually develop some very nice mindsets that they can take to other classrooms.”
Grover is a software engineer by training, turned researcher in computer science education. She holds a PhD in learning sciences and technology design from Stanford University, where she remains a visiting scholar. She explains how the beginning of her research career coincided with the advent of the block-based programming language Scratch, now widely used as an introductory programming language for children.
“Almost two decades ago, I went to Harvard to study for a master’s called technology innovation and education, and it was around that time that I volunteered for robotics workshops at the MIT Media Lab and MIT Museum. Those were pretty transformative for me: I started after-school clubs and facilitated robotics and digital storytelling clubs. In the early 2000s, I was an educational technology consultant, working with teachers on integrating technology. Then Scratch came out, and I started working with teachers on integrating Scratch into languages, arts, and science, all the things that we are doing today.”
Student Joyce codes in Scratch at her Code Club in Nunavut
Do her formative experiences at MIT, the birthplace of constructionist theory of student-centred, discovery-based learning, lead her to lean one way or another in the tinkering versus direct instruction debate? “The learning in informal spaces is, of course, very interest-driven. There is no measurement. Children are invited to a space to spend some time after school and do whatever they feel like. There would be kids who would be chatting away while a couple of them designed a robot, and then they would hand over the robot to some others and say, ‘OK, now you go ahead and program it,’ and there were some kids who would just like to hang about.
“When it comes to formal education, there needs to be more accountability, you want to do right by every child. You have to be more intentional. I do feel that while tinkering and constructionism was a great way to introduce interest-driven projects for informal learning, and there’s a lot to learn from there and bring to the formal learning context, I don’t think it can only be tinkering.”
“There needs to be more accountability to do right by every child.”
“Everybody knows that engagement is very important for learning — and this is something that we are learning more about: it’s not just interest, it’s also culture, communities, and backgrounds — but all of this is to say that there is a personal element to the learning process and so engagement is necessary, but it’s not a sufficient condition. You have to go beyond engagement, to also make sure that they are also engaging with the concepts. You want at some point for students to engage with the concept in a way that reveals what their misconceptions might be, and then they end up learning and understanding these things more deeply.
“You want a robust foundation — after all, our goal for teaching children anything at school is to build a foundation on which they build their college education and career and anything beyond that. If we take programming as a skill, you want them to have a good understanding of it, and so the personal connections are important, but so is the scaffolding.
“How much scaffolding needs to be done varies from context to context. Even in the same classroom, children may need different levels of scaffolding. It’s a sweet spot; within a classroom a teacher has to juggle so much. And therein lies the challenge of teaching: 30 kids at a time, and every child is different and every child is unique.
“It’s an equity issue. Some children don’t have the prior experience that sets them up to tinker constructively. After all, tinkering is meant to be purposeful exploration. And so it becomes an issue of who are you privileging with the pedagogy.”
She points out that each chapter in her book that comes from a more constructionist viewpoint clearly speaks of the need for scaffolding. And conversely, the chapters that take a more structured approach to computing education include elements of student engagement and children creating their own programs. “Frameworks such as Use-Modify-Create and PRIMM just push that open-ended creation a little farther down, making sure that the initial experiences have more guide rails.”
Approaches to assessment
Grover is a senior research scientist at Looking Glass Ventures, which in 2018 received a National Science Foundation grant to create Edfinity, a tool to enable affordable access to high-quality assessments for schools and universities.
In her book, she argues that asking students to write programs as a means of formative assessment has several pitfalls. It is time-consuming for both students and teachers, scoring is subjective, and it’s difficult to get a picture of how much understanding a student has of their code. Did they get their program to work through trial and error? Did they lift code from another student?
“Formative assessments that give quick feedback are much better. They focus on aspects of the conceptual learning that you want children to have. Multiple-choice questions on code force both the teachers and the children to experience code reading and code comprehension, which are just so important. Just giving children a snippet of code and saying: ‘What does this do? What will be the value of the variable? How many times will this be executed?’ — it goes down to the idea of code tracing and program comprehension.
“Research has also shown that anything you do in a classroom, the children take as a signal. Going back to the constructionist thing, when you foreground personal interest, there’s a different kind of environment in the classroom, where they’re able to have a voice, they have agency. That’s one of the good things about constructionism.
“Formative assessment signals to the student what it is that you’re valuing in the learning process. They don’t always understand what it is that they’re expected to learn in programming. Is the goal creating a program that runs? Or is it something else? And so when you administer these little check-ins, they bring more alignment between a teacher’s goals for the learners and the learners’ understanding of those goals. That alignment is important and it can get lost.”
The title of Grover’s book, which could be thought to imply that computer science education consists solely of teaching students to program, may cause some raised eyebrows.
What about building robots or devices that interact with the world, computing topics like binary, or the societal impacts of technology? “I completely agree with the statement and the belief that computer science is not just about programming. I myself have been a proponent of this. But in this book I wanted to focus on programming for a couple of reasons. Programming is a central part of the computer science curriculum, at least here in the US, and it is also the part that teachers struggle with the most.
“I want to show where children struggle and how to help them.”
“As topics go, programming carries a lot of joy and angst. There is joy in computing, joy when you get it. But when a teacher is encountering this topic for the first time there is a lot of angst, because they themselves may not be understanding things, and they don’t know what it is that the children are not understanding. And there is this entire body of research on novice programming. There are the concepts, the practices, the pedagogies, and the issues of assessment. So I wanted to give the teachers all of that: everything we know about children and programming, the topics to be learnt, where they struggle, how to help them.”
Hello World is our magazine about all things computing education. It is free to download in PDF format, or you can subscribe and we will send you each new issue straight to your home.
In issue 14 of Hello World, we have gathered some inspiring stories to help your learners connect with nature. From counting penguins in Antarctica to orienteering with a GPS twist, great things can happen when young people get creative with technology outdoors. You’ll find all this and more in the new issue!
How do you get internet over three miles up the Himalayas? That’s what the 17000 ft Foundation and Sujata Sahu had to figure out. Rob Zwetsloot reports in the latest issue of the MagPi magazine, out now.
Living in more urban areas of the UK, it can be easy to take for granted decent internet and mobile phone signal. In more remote areas of the country, internet can be a bit spotty but it’s nothing compared with living up in a mountain.
Tablet computers are provided that connect to a Raspberry Pi-powered network
“17000 ft Foundation is a not-for-profit organisation in India, set up to improve the lives of people settled in very remote mountainous hamlets, in areas that are inaccessible and isolated due to reasons of harsh mountainous terrain,” explains its founder, Sujata Sahu. “17000 ft has its roots in high-altitude Ladakh, a region in the desolate cold desert of the Himalayan mountain region of India. Situated in altitudes upwards of 9300 ft and with temperatures dropping to -50°C in inhabited areas, this area is home to indigenous tribal communities settled across hundreds of tiny, scattered hamlets. These villages are remote, isolated, and suffer from bare minimum infrastructure and a centuries-old civilisation unwilling but driven to migrate to faraway cities in search of a better life. Ladakh has a population of just under 300,000 people living across 60,000 km2 of harsh mountain terrain, whose sustenance and growth depends on the infrastructure, resources, and support provided by the government.”
A huge number of students have already benefited from the program
The local governments have built schools. However, they don’t have enough resources or qualified teachers to be truly effective, resulting in a problem with students dropping out or having to be sent off to cities. 17000 ft’s mission is to transform the education in these communities.
High-altitude Raspberry Pi
“The Foundation today works in over 200 remote government schools to upgrade school infrastructure, build the capacity of teachers, provide better resources for learning, thereby improving the quality of education for its children,” says Sujata. “17000 ft Foundation has designed and implemented a unique solar-powered offline digital learning solution called the DigiLab, using Raspberry Pi, which brings the power of digital learning to areas which are truly off-grid and have neither electricity nor mobile connectivity, helping children to learn better, while also enabling the local administration to monitor performance remotely.”
Each school is provided with solar power, Raspberry Pi computers to act as a local internet for the school, and tablets to connect to it. It serves as a ‘last mile connectivity’ from a remote school in the cloud, with an app on a teacher’s phone that will download data when it can and then update the installed Raspberry Pi in their school.
Remote success
“The solution has now been implemented in 120 remote schools of Ladakh and is being considered to be implemented at scale to cover the entire region,” adds Sujata. “It has now run successfully across three winters of Ladakh, withstanding even the harshest of -50°C temperatures with no failure. In the first year of its implementation alone, 5000 students were enrolled, with over 93% being active. The system has now delivered over 60,000 hours of learning to students in remote villages and improved learning outcomes.”
Not all children stay in the villages year round
It’s already helping to change education in the area during the winter. Many villages (and schools) can shut down for up to six months, and families who can’t move away are usually left without a functioning school. 17000 ft has changed this.
“In the winter of 2018 and 2019, for the first time in a few decades, parents and community members from many of these hamlets decided to take advantage of their DigiLabs and opened them up for their children to learn despite the harsh winters and lack of teachers,” Sujata explains. “Parents pooled in to provide basic heating facilities (a Bukhari – a wood- or dung-based stove with a long pipe chimney) to bring in some warmth and scheduled classes for the senior children, allowing them to learn at their own pace, with student data continuing to be recorded in Raspberry Pi and available for the teachers to assess when they got back. The DigiLab Program, which has been made possible due to the presence of the Raspberry Pi Server, has solved a major problem that the Ladakhis have been facing for years!”
Some of the village schools go unused in the winter
How can people help?
Sujata says, “17000 ft Foundation is a non-profit organisation and is dependent on donations and support from individuals and companies alike. This solution was developed by the organisation in a limited budget and was implemented successfully across over a hundred hamlets. Raspberry Pi has been a boon for this project, with its low cost and its computing capabilities which helped create this solution for such a remote area. However, the potential of Raspberry Pi is as yet untapped and the solution still needs upgrades to be able to scale to cover more schools and deliver enhanced functionality within the school. 17000 ft is very eager to help take this to other similar regions and cover more schools in Ladakh that still remain ignored. What we really need is funds and technical support to be able to reach the good of this solution to more children who are still out of the reach of Ed Tech and learning. We welcome contributions of any size to help us in this project.”
Learning computing is fun, creative, and exploratory. It also involves understanding some powerful ideas about how computers work and gaining key skills for solving problems using computers. These ideas and skills are collected under the umbrella term ‘computational thinking’.
When we create our online learning projects for young people, we think as much about how to get across these powerful computational thinking concepts as we do about making the projects fun and engaging. To help us do this, we have put together a computational thinking framework, which you can read right now.
What is computational thinking? A brief summary
Computational thinking is a set of ideas and skills that people can use to design systems that can be run on a computer. In our view, computational thinking comprises:
Decomposition
Algorithms
Patterns and generalisations
Abstraction
Evaluation
Data
All of these aspects are underpinned by logical thinking, the foundation of computational thinking.
What does computational thinking look like in practice?
In principle, the processes a computer performs can also be carried out by people. (To demonstrate this, computing educators have created a lot of ‘unplugged’ activities in which learners enact processes like computers do.) However, when we implement processes so that they can be run on a computer, we benefit from the huge processing power that computers can marshall to do certain types of activities.
Computers need instructions that are designed in very particular ways. Computational thinking includes the set of skills we use to design instructions computers can carry out. This skill set represents the ways we can logically approach problem solving; as computers can only solve problems using logical processes, to write programs that run on a computer, we need to use logical thinking approaches. For example, writing a computer program often requires the task the program revolves around to be broken down into smaller tasks that a computer can work through sequentially or in parallel. This approach, called decomposition, can also help people to think more clearly about computing problems: breaking down a problem into its constituent parts helps us understand the problem better.
Understanding computational thinking supports people to take advantage of the way computers work to solve problems. Computers can run processes repeatedly and at amazing speeds. They can perform repetitive tasks that take a long time, or they can monitor states until conditions are met before performing a task. While computers sometimes appear to make decisions, they can only select from a range of pre-defined options. Designing systems that involve repetition and selection is another way of using computational thinking in practice.
Our computational thinking framework
Our team has been thinking about our approach to computational thinking for some time, and we have just published the framework we have developed to help us with this. It sets out the key areas of computational thinking, and then breaks these down into themes and learning objectives, which we build into our online projects and learning resources.
To develop this computational thinking framework, we worked with a group of academics and educators to make sure it is robust and useful for teaching and learning. The framework was also influenced by work from organisations such as Computing At School (CAS) in the UK, and the Computer Science Teachers’ Association (CSTA) in the USA.
We’ve been using the computational thinking framework to help us make sure we are building opportunities to learn about computational thinking into our learning resources. This framework is a first iteration, which we will review and revise based on experience and feedback.
We’re always keen to hear feedback from you in the community about how we shape our learning resources, so do let us know what you think about them and the framework in the comments.
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