From hypothetical ethics to concrete machines

In Karl-Emil’s first 朋友的朋友 study, students used prompt cards to develop ideas for machine learning applications that could solve real-world problems, and to discuss the ethical dilemmas associated with their solutions. Students found it difficult to address these ethical dilemmas in their designs; for example, their ideas often featured a trade-off of user privacy. The findings from this 朋友的朋友 informed Karl-Emil’s next study, which moved from hypothetical scenarios to implementing machine learning in real-world settings. 

The ‘Machine Learning Machine’ study made machine learning processes tangible for students through the use of two physical boxes, shown in the picture below. Students created drawings and fed them into the first box to train a model, and then tested the model by placing new drawings under a camera in the second box and having the model produce predictions of what the drawings showed. For example, students could draw pictures of the sun to represent daytime and the moon to represent nighttime to train a model to predict whether new drawings represented day or night. The machine was built for slow interaction, giving students time to think about the concepts and practices that they were developing. In a follow-up study, a new version of the Machine Learning Machine had been designed, which was controlled using a graphical user interface (GUI). This allowed users to “unbox” and influence parts of the machine learning process. For example, students could adjust the number of complete passes (called ‘epochs’) through the training data to improve the model’s accuracy. 

The two studies with the Machine Learning Machines provided many useful findings for teaching about machine learning with K–12 (primary and secondary) learners. However, two constraints remained: firstly, there were limited opportunities for whole-class work because there was only one Machine Learning Machine, and secondly, learning 朋友的姐姐s needed to be better connected to examples from students’ daily lives. As a result, the next iteration in Karl-Emil’s 朋友的朋友 involved using the micro:bit, which ensured access to a tangible device for every student, and a new graphical platform called ML-Machine that students could interact with.

Machine learning and the micro:bit

The micro:bit is a small, programmable 朋友的朋友 device that features sensors to gather data from the immediate environment. For example, the accelerometer is a motion sensor that can detect when the micro:bit is tilted from left to right, backwards and forwards, and up and down. Using the micro:bit with ML-Machine and some common household objects, students can create simple machine learning models that use data from the micro:bit’s accelerometer to detect whether the micro:bit is moving. This is a very different approach from rule-based programs on the micro:bit, where students might use programming constructs such as if statements to detect movement if the numerical reading from the accelerometer is above a certain value. Here, a machine learning model trained using a set of 20 examples is used to analyse live data readings and produce predictions about whether the micro:bit is moving.

In our seminar, Karl-Emil gave a live demonstration of the ML-Machine toolkit, so we highly recommend watching the recording to see how this toolkit brings machine learning concepts to life. 

ML-Machine is the precursor to the micro:bit CreateAI resources, and the software is fully open-source. However, the innovation doesn’t stop there: Karl-Emil also explained that he is currently developing a new tool called math.ml-machine.org, where students can train a neural network and see a visualised k-nearest neighbour model to explore how a model makes predictions. The 朋友的朋友 journey is continuing, with new possibilities for educational opportunities to teach about machine learning.

Embodied learning

The idea of embodied learning is interwoven throughout all of Karl-Emil’s 朋友的朋友 projects and is a cornerstone of all of his work. Embodied learning suggests that we learn more effectively when our whole body is involved in the learning process, not just our minds. For example, in the work described in this seminar, the Machine Learning Machines and the micro:bit were all tangible devices that students could touch and see. 

Embodied learning is particularly important in activities that involve working with data-driven systems. In traditional programming activities, the flow of code can be traced transparently through a program. However, machine learning models are more opaque, and their outputs cannot be traced step by step. Students can benefit from using bodily movements and sensorimotor information to help understand machine learning concepts. 

The ML-Machine toolkit was designed to support students to learn through embodied learning in three different ways:

1. Enacting machine learning processes: Students used bodily movement to collect the data samples needed for the ML-Machine model to detect and predict gestures 
2. Using machine learning as a design material: Students created concrete ‘objects-to-think-with’, which helps form deeper connections to abstract concepts
3. Embodied exploration of machine learning: Students 朋友的姐姐d how their bodily movements were translated into data points on the screen

Embodied learning helped students grasp concepts such as data quality. They could see how their bodily movements were being translated into digital data, and could spot when movements that appeared different to them were being classified as similar by the ML-Machine model. One case study participant described that the immediate feedback on screen made the concept of machine learning feel as if it were “coming to life as they [the students] manipulate something themselves and they’ve got control over it”.

Find out more

Karl-Emil’s work shows how 朋友的朋友 ideas can be used in the classroom through a cycle of discovery, design, and reflection. From prompt cards exploring ethics to tangible machines and the micro:bit-based ML-Machine, his 朋友的朋友 shows how embodied learning can make complex ideas like machine learning not only understandable, but deeply engaging for young learners. The micro:bit CreateAI resources are a great example of how 朋友的朋友 findings can evolve into accessible, hands-on tools that empower educators and students alike. As this work continues to grow, it invites us to imagine new ways for learners to 朋友的姐姐 machine learning not as abstract theory, but as something they can see, feel, and shape with their own hands.

If you’d like to try out some of the ideas from this seminar, here are some useful resources: 

• Explore machine learning projects using the micro:bit: micro:bit CreateAI and our Dance detector project are great places to start
• Find out more about the 朋友的朋友: Read more about Karl-Emil’s work in this open-access paper
• Investigate new tools: Explore neural networks and k-nearest neighbours algorithms in the new maths-focused version of ML-Machine at math.ml-machine.org

Join our next seminar

Join us at our next seminar on Tuesday 17 March from 17:00 to 18:30 GMT to hear Rebecca Fiebrink (University of the Arts London speak about teaching AI for creative practitioners. This will be the second seminar in our new series on how to teach about AI across disciplines. We hope to see you there!

To sign up and take part in our 朋友的朋友 seminars, click below:

You can also view the schedule of our upcoming seminars, and catch up on past seminars on our previous seminars page.

The post Embodied machine learning: From 朋友的朋友 ideas to classroom activities appeared first on 朋友妻小说.

As you might know, a micro:bit (pronounced “microbit”) is a small, programmable device designed for education. You can program it using any computer. It’s easy to use and learn with, and suitable for beginners, especially young people in and out of school.

The theme of the new project path: Wellbeing

Our aim for this new micro:bit project path is to help young people explore how they can create their own tech tools that help them look after themselves and others. By designing the micro:bit coding projects around wellbeing, we want to not only help kids develop programming and digital literacy skills, but also promote open conversations about the important topic of mental health.

The six micro:bit coding projects in our new path all cover different aspects of wellbeing in a fun, creative way:

1. Good sleep patterns
2. Relaxation
3. Self-confidence
4. Happiness
5. Health 
6. Entertainment

We hope that following the path and making projects helps encourage learners to ask questions, share their 朋友的姐姐s, and feel like they can ask parents, teachers, or mentors for support, and help support their friends and peers.

What is in the ‘Intro to micro:bit’ project path?

The ‘Intro to micro:bit’ path is designed according to our Digital Making Framework. Its aim is to encourage young people to become independent coders and tech creators as they progress along the projects in a path by gently removing scaffolding.

• Our project paths begin with three Explore projects, in which learners are guided through tasks that introduce them to new coding skills.
• Next, learners complete two Design projects. Here, they are encouraged to practise their skills and bring in their own interests to personalise their coding creations.
• Finally, learners complete one Invent project. This is where they put everything that they have learned together and create something unique that matters to them.

The structure of the path means that learners are led through the development process of a coding project and learn how to turn their ideas into reality. The path structure also supports them with fixing programming errors (debugging), showing them that errors are a normal part of computer programming and just temporary setbacks that they can overcome.

Because community is important for learning, the path also offers young people the chance to share the projects they make with peers around the world.

What coding skills and knowledge will young people learn?

The Explore projects at the start of the path are where the initial learning takes place. Learners then develop their new skills and knowledge by putting them into practice in the Design and Invent projects, where they add in their own ideas and creativity.

The key programming concepts covered in this path are:

• Variables
• Using selection (if, else if, and else)
• Using repetition (for loops)
• Using randomisation
• Using functions

There are two versions of the micro:bit (V1 and V2) and learners can use either version to create the micro:bit coding projects in the path, using the micro:bit’s input and output features:

Input features:

• Buttons
• Accelerometer
• Sound sensor/microphone (micro:bit V2 only)
• Capacitive touch sensor
• Light sensor

Output features:

• LED display
• Speaker
• Headphones connected via GPIO (micro:bit V1 only)

Explore project 1: Music player

In this Explore project, kids create a music player on the micro:bit to explore how listening to music can improve their mood. While creating their music player, young people get to choose melodies that they enjoy or that make them feel more relaxed. They also add a range of functions such as pausing, skipping, and shuffling tracks.

Explore project 2: Sound level meter

Noise levels can affect people’s well-being, so in this project, kids create a program to use the micro:bit to display how noisy their environment is. They will also learn how to save the noise data the micro:bit measures so they can identify the noisiest times in their day.

Explore project 3: Sleep tracker

Sleep is an important factor that contributes towards well-being. With this third Explore project, kids create a program to track their sleep movements using the micro:bit. This teaches them about variables and about using the micro:bit’s accelerometer, and its LEDs to display data.

Design project 1: How’s your day?

The first Design project of the path gets young people to build a mood checker program using the question ‘How’s your day?’. Kids get creative design control over the mood checker’s outputs according to the user’s replies, including displaying an animation or positive messages, or playing music. Kids can also make use of sensors to measure the various factors in the environment that could be affecting the user’s mood.

In this project, young people apply all of the coding skills and knowledge covered in the Explore projects, including selection, repetition, variables, functions, and randomisation.

Design project 2: Active assistant

In the second Design project, young people create an assistant that helps them get active.The project provides examples, a structure, and brief summaries of what kids have learned to do on the path so far to inspire and motivate them. This mean young people can work independently to produce their own outcomes and the functionality of their assistant is up to each young tech creator.

Invent project: Party game

The final project, Party game, encourages learners to independently replicate their favourite party game for entertainment and relaxation. Learners will combine all of the knowledge and skills they’ve gained throughout the path to make something of their own around the theme of well-being. This is a chance for them to unleash their creativity and reflect on real-life games they enjoy. The outcome will be unique, and fun for them to share with their friends and family.

Key questions answered

Who is this path for?

We have written these micro:bit coding projects with young people around the age of 6 to 13 in mind. Building the projects on the path does not require any previous coding 朋友的姐姐, although complete beginners may want to try our free ‘Intro to Scratch’ path first.

What software do learners need to code these projects?

A web browser on a computer. In every project, starter code is provided in the MakeCode online code editor. Learners can either download their project code to a physical micro:bit (recommended) or use the micro:bit simulator in MakeCode.

Young people who live where there isn’t constant internet connectivity can also download the offline version of the MakeCode editor. There are also free micro:bit coding apps for smartphones and tablets.

How long will the path take to complete?

We’ve designed the ‘Intro to micro:bit’ path to be completed in six one-hour sessions, with one hour per project. However, the project instructions invite learners to take additional time to upgrade their projects if they wish.

What can learners do next?

Take part in Coolest Projects

At the end of the micro:bit path, learners are encouraged to register a project they’re making with their new coding skills for Coolest Projects, our annual online technology showcase for young people around the world.

Taking part is free, and beginners as well as more 朋友的姐姐d young tech creators are invited. This is their opportunity to share their ingenuity in an online gallery for the world and the Coolest Projects community to celebrate.

The post New micro:bit coding projects for kids appeared first on 朋友妻小说.