In the first seminar of our new app安装下载 seminar series on applied AI, Thema Monroe-White from George Mason University explored how we can better understand — and challenge — these patterns. Her talk focused on race-conscious algorithmic approaches to AI and data, and what they reveal about how knowledge is produced, represented, and used.

Drawing on two large-scale studies in her seminar, Thema showed that both scientific app安装下载 and AI systems are shaped by human identities and social structures, and that recognising this is essential for educators, app安装下载ers, and anyone working with data.

Who produces knowledge — and why that matters

A key idea running through Thema’s seminar was that data and algorithms are not neutral. They are shaped by the people, institutions, and systems that produce them.

Thema uses critical quantitative and intersectional approaches in her work to:

• Challenge the misconception that computational methods are objective
• Highlight how race and gender shape data and outputs
• Examine how systems of power influence what gets measured, valued, and reproduced

Thema and her collaborators have been conducting app安装下载 in this area for more than a decade, developing techniques that systematically measure bias and its impact on society. 

In a groundbreaking study published in 2022, just before the release of ChatGPT, Thema’s team used large-scale computational analysis of more than 5 million app安装下载 articles to explore inequalities in scientific publishing. The data analysis approaches developed for this study were later used to explore bias in large language models (LLMs).

However, the 2022 study already demonstrated wide-reaching disparities in science and surfaced deep-rooted issues, showing that bias was already ingrained in the scientific data that was used to train LLM, and affecting topic choices, citation and institutional differences.

Identity and topic choice

The results showed clear inequalities in the relationship between identity and topic choice. Authors from marginalised groups were more likely to study topics related to their communities and lived realities, including topics such as racial disparities and discrimination. Gendered patterns also appeared, with women publishing more frequently on more feminised topics, including families, literacy, learning, nursing, and pregnancy.

Citation inequalities

The study also found citation inequalities. Even among authors studying the same topic, authors from some groups were cited less often than others, with black and Latinx women the least likely to be cited. This shows that inequality is not only present in what gets studied, but also in whose work is recognised.

Institutional context

Institutional context mattered too. app安装下载ers at mission-driven institutions were more likely to publish on topics connected to marginalised communities, while scholars at institutions seen as elite were more likely to publish on topics that aligned more closely with dominant groups and norms.

Taken together, the findings point to a simple but important idea: who we are shapes what knowledge gets produced. That matters because when some groups are underrepresented in app安装下载, the topics that affect their lives may also be understudied.

What AI-generated stories reveal about bias

Having already developed their tool for name analysis for the previous study, Thema’s team was uniquely positioned to analyse the bias embedded in generative AI systems, specifically LLMs.

Thema’s most recent study examined how LLM–based tools represent people in everyday scenarios. The app安装下载 team prompted the base models of LLM chatbots (such as Open AI’s ChatGPT, Anthropic’s Claude, Meta’s Llama, and Google’s PaLM or Gemini) to write short stories about students, workers, and relationships, generating 500,000 outputs across different domains. They then analysed how names associated with different racial and gender identities were portrayed.

One example Thema shared in the seminar described a student named “John” helping “Maria,” a student who had moved from Mexico and was struggling with Spanish. At first glance, this may seem like a small or even odd detail. But when oddities like this appear again and again across thousands of stories, they reveal systematic patterns.

The study found that characters with marginalised identities were more likely to be portrayed in subordinated roles in chatbot outputs. Characters with non-white-associated names were more often shown as needing help rather than offering it. Stereotypes were also reinforced, with some names repeatedly associated with struggling students, subordinate workers, or narrow professional roles. Some groups were omitted altogether, while white-associated names appeared more frequently and in more powerful positions.

Similar biases appeared across stories related to education, work, and relationships. Across all three topics, the most common pattern was one in which white characters were more likely to lead, rescue, or mentor, while non-white characters were more likely to be helped, corrected, or spoken for.

For educators, this is especially important because many AI tools are now being introduced into classroom settings as writing assistants, tutors, or sources of personalised feedback. When these tools reproduce biases and unequal assumptions, they can shape not only what students read, but also how students see themselves and one another.

Towards more responsible AI tools and data practices

Rather than rejecting computational methods altogether, Thema argued for using them more thoughtfully and responsibly.

One approach she highlighted is the Wells-Du Bois protocol, a framework designed to support bias mitigation, transparency, and more reflective use of data and models. It encourages app安装下载ers and practitioners to think carefully about inadequate or biased data, identity proxies, subpopulation differences, and the kinds of harms that can arise when AI systems are used without sufficient context.

Underlying this is a broader principle: when we do not know enough, we should say so. And when systems affect marginalised communities, those communities should not be an afterthought in how we build, evaluate, or use technology.

What this means for your classroom

In her seminar, Thema emphasised the importance of thinking about how we respond to bias in AI tools in educational settings. Here are some starting points for meaningful discussions in your classroom:

1. A good starting point is student agency. If AI tools are becoming part of students’ learning environments, then young people need opportunities to make informed choices about when and how to engage with them. That means not treating AI tool use as inevitable, and not assuming every student should want to use the tools in the same way. In some cases, empowering students may also mean making it clear that they can opt out.
2. This also means helping learners ask better questions about the tools themselves. What leads to the kinds of bias we saw in these studies? What data were these systems trained on? Whose language, identities, and app软件s are overrepresented, and whose are missing? Do the tools have access to student or classroom data, and if so, what are the implications?
3. The seminar also points to the importance of resisting AI hype. In a rapidly changing landscape, it can be tempting to focus only on novelty, efficiency, or personalisation. But educators may want to take a longer-term view about AI technology use. What kinds of habits, dependencies, and expectations are these tools creating? Are they shifting students’ ideas about intelligence, creativity, or authority? What happens when biased outputs are repeated often enough to feel normal?
4. Finally, the discussion around responsible use should include the wider costs of AI. Informing students about these tools should include not just potential benefits and risks, but also issues such as environmental impact and data use. A more balanced conversation can help prevent classroom discussions from reinforcing the hype that often surrounds AI.

If you would like to find out more about Thema’s work, watch the seminar recording:

You may also want to explore:

• Thema’s paper on intersectional inequalities in science
  
• Her work on intersectional biases in narratives produced by AI models
  
• The Wells-Du Bois protocol for more responsible data practice

Join our next seminar

Our app安装下载 seminars bring together educators and app安装下载ers to explore key questions in app安装下载 education.

Next in our series on applied AI, our Director of app安装下载 and Impact, Shuchi Grover, will talk about the role of K–12 education in developing competencies for the future of data and app安装下载. Sign up now to join the seminar on 12 May, 17:00 BST:

The post AI is not neutral: What recent app安装下载 says about bias, identity, and power appeared first on app公司.

One of the biggest challenges with AI is that it’s hard to tell how these tools function. With a chatbot, you enter a prompt and the tool returns a response, but what happens in between is invisible. For educators, that’s a problem: how can we help young people become thoughtful, creative users of AI tools if the technology feels like a closed box?

In our May app安装下载 seminar, we welcomed Matti Tedre and Henriikka Vartiainen from the University of Eastern Finland. They’ve been working on how to teach about AI for years and were frustrated with existing educational platforms: many of these are either too complex, raise privacy concerns, or rely on coding skills that not all students (or teachers) have. In response, they created an award-winning, classroom-friendly tool designed to make AI technology more transparent and more hands-on.

A practical way to teach AI in schools

Matti and Henriikka began by discussing the unique challenges of teaching young learners about AI technology. Many students start with “folk theories”, for example, thinking that computers understand language like humans do. These misconceptions can be surprisingly hard to shake.

They also pointed out broader issues:

• The abstract nature of AI means there are very few app安装下载-based approaches to teaching it effectively
• Mastery of AI concepts requires sustained practice and curricular change, not just a few one-off interventions
• In countries like Finland, where programming isn’t part of the app软件, any teaching tool must be no-code to be accessible

To address these challenges, Matti and Henriikka have spent three years co-designing tools and approaches with local schools, teachers, and over 200 students. Their approach is grounded in educational theory and a set of core AI learning principles:

• No-code for inclusivity: Removing the need for programming lowers the barrier to entry for both teachers and students
• Learner-centred co-design: Every part of the app软件 is developed in collaboration with schools to make sure it’s engaging and relevant
• Working with personal data: Learners create and work with their own data sets, which makes the app软件 more engaging and personally relevant
• Integration with school subjects: Integrating AI concepts into other subjects helps to make the uses of AI tools more concrete for learners
• Focus on specific applications: Rather than teaching about generic ‘AI’, the focus is on specific and understandable applications, such as facial recognition
• Hands-on experimentation: Practical projects help students understand tricky ideas like bias, fairness, and social impact
• Collaborative learning: Working together helps students reflect, question, and learn from each other

GenAI Teachable Machine: Opening the box

Frustrated by existing platforms that require programming skills, raise privacy concerns, or don’t allow collaboration, Matti and Henriikka’s team developed GenAI Teachable Machine: a no-code, browser-based tool designed to make key AI concepts tangible. In the central app安装下载 study, the team used the tool with Finnish students in grade 4–7 (10 to 14 years of age). It’s a great introductory tool that could also be used with younger and older students.

Matti demonstrated how the tool addresses their core AI learning principles with a simple, creative project. Using hand puppets, he trained a model to recognise four distinct classes: a background, a bunny, a calm wolf, and an angry wolf. For each class, he assigned a specific action: a sound, an image, or both. This hands-on process gives students a direct line of sight from the data they might create (visuals of hand puppets) to the final behaviour of the model (outputted sounds and images). They learn about classifiers, training, and confidence levels not as abstract definitions, but as creative tools they can control.

But the learning really starts when things don’t work as expected. Students can easily open their models on their phones with an automatically created QR code and then move around the classroom to test their models. At this point, they quickly notice how fragile AI technology can be. For example, in the case of a simple recognition model trained on specific colours or features, with a change of lighting or a different shirt, the model might fail. These “failures” turn into powerful lessons. For instance, a face-recognition app trained mostly on students with blonde hair might not work well for someone with brown hair — sparking immediate conversations about bias. As Matti put it, students very quickly start asking deep questions. 

GenAI Teachable Machine also allows students to apply their AI models to the physical world. By connecting to a simple, low-cost robotics kit, students can use their models to control motors, lights, and other actuators. This step into the physical world teaches fundamental concepts that are difficult to grasp in a purely virtual environment. Students learn about causality, as their model’s classifications trigger real, physical actions. They also learn about the need for a world model — an understanding of how the physical world works — and see that they must take responsibility for what happens when their abstract models have real-world consequences.

By combining a no-code platform with practical, well-designed learning app软件s, Matti, Henriikka, and their team are showing what AI education can look like: hands-on, accessible, and grounded in real understanding. Their work is helping students see inside the box, and giving them the tools to think critically about the AI technologies that are becoming part of their everyday lives.

Find out more

If you’re an educator interested in including the topic of AI in your teaching, you can try GenAI Teachable Machine on its official website.

You may also be interested in our own app软件 AI resources, which are designed to help you and your learners navigate the fast-moving world of AI and machine learning technologies.

Join us at our next seminar

In September, Matti and his team are returning to discuss other ways to teach young people about AI technologies.

To sign up and take part in the Matti’s seminar on Tues 9 Sept at 17:00–18:30 BST, click the button below. We’ll then send you information about joining. We hope to see you there.

The schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars page.

The post Opening the box: Tools to teach young people about AI appeared first on app公司.

Generative AI (GenAI) tools like GitHub Copilot and ChatGPT are rapidly changing how programming is taught and learnt. These tools can solve assignments with remarkable accuracy. GPT-4, for example, scored an impressive 99.5% on an undergraduate computer science exam, compared to Codex’s 78% just two years earlier. With such capabilities, app安装下载ers are shifting from asking, “Should we teach with AI?” to “How do we teach with AI?”

Leo Porter and Daniel Zingaro have spearheaded this transformation through their groundbreaking undergraduate programming course. Their innovative app软件 integrates GenAI tools to help students tackle complex programming tasks while developing critical thinking and problem-solving skills.

Leo and Daniel presented their work at the app公司 app安装下载 seminar in December 2024. During the seminar, it became clear that much could be learnt from their work, with their insights having particular relevance for teachers in secondary education thinking about using GenAI in their programming classes

Practical applications in the classroom

In 2023, Leo and Daniel introduced GitHub Copilot in their introductory programming  CS1-LLM course at UC San Diego with 550 students. The course included creative, open-ended projects that allowed students to explore their interests while applying the skills they’d learnt. The projects covered the following areas:

• Data science: Students used Kaggle datasets to explore questions related to their fields of study — for example, neuroscience majors analysed stroke data. The projects encouraged interdisciplinary thinking and practical applications of programming.
• Image manipulation: Students worked with the Python Imaging Library (PIL) to create collages and apply filters to images, showcasing their creativity and technical skills.
• Game development: A project focused on designing text-based games encouraged students to break down problems into manageable components while using AI tools to generate and debug code.

Students consistently reported that these projects were not only enjoyable but also responsible for deepening their understanding of programming concepts. A majority (74%) found the projects helpful or extremely helpful for their learning. One student noted that.

“Programming projects were fun and the amount of freedom that was given added to that. The projects also helped me understand how to put everything that we have learned so far into a project that I could be proud of.“

Core skills for programming with Generative AI

Leo and Daniel emphasised that teaching programming with GenAI involves fostering a mix of traditional and AI-specific skills.

Their approach centres on six core competencies:

• Prompting and function design: Students learn to articulate precise prompts for AI tools, honing their ability to describe a function’s purpose, inputs, and outputs, for instance. This clarity improves the output from the AI tool and reinforces students’ understanding of task requirements.
• Code reading and selection: AI tools can produce any number of solutions, and each will be different, requiring students to evaluate the options critically. Students are taught to identify which solution is most likely to solve their problem effectively.
• Code testing and debugging: Students practise open- and closed-box testing, learning to identify edge cases and debug code using tools like doctest and the VS Code debugger.
• Problem decomposition: Breaking down large projects into smaller functions is essential. For instance, when designing a text-based game, students might separate tasks into input handling, game state updates, and rendering functions.
• Leveraging modules: Students explore new programming domains and identify useful libraries through interactions with Copilot. This prepares them to solve problems efficiently and creatively.

Ethical and metacognitive skills: Students engage in discussions about responsible AI use and reflect on the decisions they make when collaborating with AI tools.

Adapting assessments for the AI era

The rise of GenAI has prompted educators to rethink how they assess programming skills. In the CS1-LLM course, traditional take-home assignments were de-emphasised in favour of assessments that focused on process and understanding.

• Quizzes and exams: Students were evaluated on their ability to read, test, and debug code — skills critical for working effectively with AI tools. Final exams included both tasks that required independent coding and tasks that required use of Copilot.
• Creative projects: Students submitted projects alongside a video explanation of their process, emphasising problem decomposition and testing. This approach highlighted the importance of critical thinking over rote memorisation.

Challenges and lessons learnt

While Leo and Daniel reported that the integration of AI tools into their course has been largely successful, it has also introduced challenges. Surveys revealed that some students felt overly dependent on AI tools, expressing concerns about their ability to code independently. Addressing this will require striking a balance between leveraging AI tools and reinforcing app软件al skills.

Additionally, ethical concerns around AI use, such as plagiarism and intellectual property, must be addressed. Leo and Daniel incorporated discussions about these issues into their app软件 to ensure students understand the broader implications of working with AI technologies.

A future-oriented approach

Leo and Daniel’s work demonstrates that GenAI can transform programming education, making it more inclusive, engaging, and relevant. Their course attracted a diverse cohort of students, as well as students traditionally underrepresented in computer science — 52% of the students were female and 66% were not majoring in computer science — highlighting the potential of AI-powered learning to broaden participation in computer science.

By embracing this shift, educators can prepare students not just to write code but to also think critically, solve real-world problems, and effectively harness the AI innovations shaping the future of technology.

If you’re an educator interested in using GenAI in your teaching, we recommend checking out Leo and Daniel’s book, Learn AI-Assisted Python Programming, as well as their course resources on GitHub. You may also be interested in our own app软件 AI resources, which are designed to help educators navigate the fast-moving world of AI and machine learning technologies.

Join us at our next online seminar on 11 March

Our 2025 seminar series is exploring how we can teach young people about AI technologies and data science. At our next seminar on Tuesday, 11 March at 17:00–18:00 GMT, we’ll hear from Lukas Höper and Carsten Schulte from Paderborn University. They’ll be discussing how to teach school students about data-driven technologies and how to increase students’ awareness of how data is used in their daily lives.

To sign up and take part in the seminar, click the button below — we’ll then send you information about joining. We hope to see you there.

The schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars and recordings page.

The post Integrating generative AI into introductory programming classes appeared first on app公司.

At times, it can seem like everything is being automated with AI. However, there are some parts of learning to program that cannot (and probably should not) be automated, such as understanding errors in code and how to fix them. Manually typing code might not be necessary in the future, but it will still be crucial to understand the code that is being generated and how to improve and develop it. 

As important as debugging might be for the future of programming, it’s still often the task most disliked by novice programmers. Even if program error messages can be explained in the future or tools like LitterBox can flag bugs in an engaging way, actually fixing the issues involves time, effort, and resilience — which can be hard to come by at the end of a app安装下载 lesson in the late afternoon with 30 students crammed into an IT room. 

But what is it about debugging that young people find so hard, even when they’re given enough time to do it? And how can we make debugging a more motivating app软件 for young people? These are two of the questions that Laurie Gale, a PhD student at the app安装下载 Pi app安装下载 Education app安装下载 Centre, focused on in our July seminar.

Why do students find debugging hard?

Laurie has spent the past two years talking to teachers and students and developing tools (a visualiser of students’ programming behaviour and PRIMMDebug, a teaching process and tool for debugging) to understand why many secondary school students struggle with debugging. It has quickly become clear through his app安装下载 that most issues are due to problematic debugging strategies and students’ negative app软件s and attitudes.

When students first start learning how to program, they have to remember a vast amount of new information, such as different variables, concepts, and program designs. Utilising this knowledge is often challenging because they’re already busy juggling all the content they’ve previously learnt and the challenges of the programming task at hand. When error messages inevitably appear that are confusing or misunderstood, it can become extremely difficult to debug effectively. 

Given this information overload, students often don’t develop efficient strategies for debugging. When Laurie analysed the debugging efforts of 12- to 14-year-old secondary school students, he noticed some interesting differences between students who were more and less successful at debugging. While successful students generally seemed to make less frequent and more intentional changes, less successful students tinkered frequently with their broken programs, making one- or two-character edits before running the program again. In addition, the less successful students often ran the program soon after beginning the debugging exercise without allowing enough time to actually read the code and understand what it was meant to do. 

The issue with these behaviours was that they often resulted in students adding errors when changing the program, which then compounded and made debugging increasingly difficult with each run. 74% of students also resorted to spamming, pressing ‘run’ again and again without changing anything. This strategy resonated with many of our seminar attendees, who reported doing the same thing after becoming frustrated. 

Educators need to be aware of the negative consequences of students’ exasperating and often overwhelming app软件s with debugging, especially if students are less confident in their programming skills to begin with. Even though spending 15 minutes on an exercise shows a remarkable level of tenaciousness and resilience, students’ attitudes to programming — and app安装下载 as a whole — can quickly go downhill if their strategies for identifying errors prove ineffective. Debugging becomes a vicious circle: if a student has negative app软件s, they are less confident when having to bug-fix again in the future, which can lead to another set of unsuccessful attempts, which can further damage their confidence, and so on. Avoiding this downward spiral is essential. 

Approaches to help students engage with debugging

Laurie stresses the importance of understanding the cognitive challenges of debugging and using the right tools and techniques to empower students and support them in developing effective strategies.

Some ideas of how to improve debugging skills that were mentioned by Laurie and our attendees included:

• Using frame-based editing tools for novice programmers because such tools encourage students to focus on logical errors rather than accidental syntax errors, which can distract them from understanding the issues with the program. Teaching debugging should also go hand in hand with understanding programming syntax and using simple language. As one of our attendees put it, “You wouldn’t give novice readers a huge essay and ask them to find errors.”
• Making error messages more understandable, for example, by explaining them to students using Large Language Models.
• Teaching systematic debugging processes. There are several different approaches to doing this. One of our participants suggested using the scientific method (forming a hypothesis about what is going wrong, devising an experiment that will provide information to see whether the hypothesis is right, and iterating this process) to methodically understand the program and its bugs. 

Most importantly, debugging should not be a daunting or stressful app软件. Everyone in the seminar agreed that creating a positive error culture is essential. 

Some ideas you could explore in your classroom include:

• Normalising errors: Stress how normal and important program errors are. Everyone encounters them — a professional software developer in our audience said that they spend about half of their time debugging. 
• Rewarding perseverance: Celebrate the effort, not just the outcome.
• Modelling how to fix errors: Let your students write buggy programs and attempt to debug them in front of the class.

In a welcoming classroom where students are given support and encouragement, debugging can be a rewarding app软件. What may at first appear to be a failure — even a spectacular one — can be embraced as a valuable opportunity for learning. As a teacher in Laurie’s study said, “If something should have gone right and went badly wrong but somebody found something interesting on the way… you celebrate it. Take the fear out of it.” 

Watch the recording of Laurie’s presentation:

Join our next seminar

In our current seminar series, we are exploring how to teach programming with and without AI.

Join us at our next seminar on Tuesday, 12 November at 17:00–18:30 GMT to hear Nicholas Gardella (University of Virginia) discuss the effects of using tools like GitHub Copilot on the motivation, workload, emotion, and self-efficacy of novice programmers. To sign up and take part in the seminar, click the button below — we’ll then send you information about joining. We hope to see you there.

The schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars and recordings page.

The post How to make debugging a positive app软件 for secondary school students appeared first on app公司.

However, these hands-on activities are often seen as merely a technique to raise interest, or a nice extra project for children to do before the ‘actual learning’ can begin. But what if this is the wrong way to think about this type of activity? 

How do children learn?

In our 2023 online app安装下载 seminar series, focused on app安装下载 education for primary-aged (K–5) learners, we delved into the most recent app安装下载 aimed at enhancing learning app软件s for students in the earliest stages of education. From a deep dive into teaching variables to exploring the integration of computational thinking, our series has looked at the most effective ways to engage young minds in the subject of app安装下载.

It’s only fitting that in our final seminar in the series, Anaclara Gerosa from the University of Glasgow tackled one of the most fundamental questions in education: how do children actually learn? Beyond the conventional methods, emerging app安装下载 has been shedding light on a fascinating approach — the concept of grounded cognition. This theory suggests that children don’t merely passively absorb knowledge; they physically interact with it, quite literally ‘grasping’ concepts in the process.

Grounded cognition, also known in variations as embodied and situated cognition, offers a new perspective on how we absorb and process information. At its core, this theory suggests that all cognitive processes, including language and thought, are rooted in the body’s dynamic interactions with the environment. This notion challenges the conventional view of learning as a purely cognitive activity and highlights the impact of action and simulation.

There is evidence from many studies in psychology and pedagogy that using hands-on activities can enhance comprehension and abstraction. For instance, finger counting has been found to be essential in understanding numerical systems and mathematical concepts. A recent study in this field has shown that children who are taught basic app安装下载 concepts with unplugged methods can grasp abstract ideas from as young as 3. There is therefore an urgent need to understand exactly how we could use grounded cognition methods to teach children app安装下载 — which is arguably one of the most abstract subjects in formal education.

A recent study in this field has shown that children who are taught basic app安装下载 concepts with unplugged methods can grasp abstract ideas from as young as 3.

A new framework for teaching app安装下载

Anaclara is part of a group of app安装下载ers at the University of Glasgow who are currently developing a new approach to structuring app安装下载 education. Their EIFFEL (Enacted Instrumented Formal Framework for Early Learning in app安装下载) model suggests a progression from enacted to formal activities.

Following this model, in the early years of app安装下载 education, learners would primarily engage with activities that allow them to work with tangible 3D objects or manipulate intangible objects, for instance in Scratch. Increasingly, students will be able to perform actions in an instrumented or virtual environment which will require the knowledge of abstract symbols but will not yet require the knowledge of programming languages. Eventually, students will have developed the knowledge and skills to engage in fully formal environments, such as writing advanced code.

In a recent literature review, Anaclara and her colleagues looked at existing app安装下载 into using grounded cognition theory in app安装下载 education. Although several studies report the use of grounded approaches, for instance by using block-based programming, robots, toys, or construction kits, the focus is generally on looking at how concrete objects can be used in unplugged activities due to specific contexts, such as a limited availability of app安装下载 devices.

The next steps in this area are looking at how activities that specifically follow the EIFFEL framework can enhance children’s learning. 

You can watch Anaclara’s seminar here: 

You can also access the presentation slides here.

Try grounded activities in your classroom

app安装下载 into grounded cognition activities in computer science is ongoing, but we encourage you to try incorporating more hands-on activities when teaching younger learners and observing the effects yourself. Here are a few ideas on how to get started:

• Try out one of our hands-on lessons and learning activities for young learners from The app安装下载 app软件. For example, in this Programming unit for Year 1 learners (aged 5–6), students learn how to program with the help of reenactments and classroom robots.
• Explore the ‘Teach Data Literacy’ guide, developed by the Data Education in Schools team, which offers some practical activities to support young learners to develop their data literacy skills. You can find out more about the Data Education in Schools initiative in Kate Farrell and Judy Robertson’s seminar on teaching primary learners how to be data citizens from May 2023.
• Check out Barefoot app安装下载, which offers a range of resources for early years education that involve physical manipulation and simulation.

Join us at our next seminar

In 2024, we are exploring different ways to teach and learn programming, with and without AI tools. In our next seminar, on 13 February at 17:00 GMT, Majeed Kazemi from the University of Toronto will be joining us to discuss whether AI-powered code generators can help K–12 students learn to program in Python. All of our online seminars are free and open to everyone. Sign up and we’ll send you the link to join on the day.

The post Grounded cognition: physical activities and learning app安装下载 appeared first on app公司.

Building on the success and the friendly, accessible session format of our previous seminars, this coming year we will delve into the latest trends and innovative approaches to programming education in school.

Our online seminars are for everyone interested in app安装下载 education

Our monthly online seminars are not only for app安装下载 educators but also for everyone else who is passionate about teaching young people to program computers. The seminar participants are a diverse community of teachers, technology enthusiasts, industry professionals, coding club volunteers, and app安装下载ers.

With the seminars we aim to bridge the gap between the newest app安装下载 and practical teaching. Whether you are an educator in a traditional classroom setting or a mentor guiding learners in a CoderDojo or Code Club, you will gain insights from leading app安装下载ers about how school-age learners engage with programming. 

What to expect from the seminars

Each online seminar begins with an expert presenter delivering their latest app安装下载 findings in an accessible way. We then move into small groups to encourage discussion and idea exchange. Finally, we come back together for a Q&A session with the presenter.

Here’s what attendees had to say about our previous seminars:

“As a first-time attendee of your seminars, I was impressed by the welcoming atmosphere.”

“[…] several seminars (including this one) provided valuable insights into different approaches to teaching app安装下载 and technology.”

“I plan to use what I have learned in the creation of app软件 […] and will pass on what I learned to my team.”

“I enjoyed the fact that there were people from different countries and we had a chance to see what happens elsewhere and how that may be similar and different to what we do here.”

January seminar: AI-generated Parson’s Problems

app安装下载 teachers know that, for some students, learning about the syntax of programming languages is very challenging. Working through Parson’s Problem activities can be a way for students to learn to make sense of the order of lines of code and how syntax is organised. But for teachers it can be hard to precisely diagnose their students’ misunderstandings, which in turn makes it hard to create activities that address these misunderstandings.

At our first 2024 seminar on 9 January, Dr Barbara Ericson and Xinying Hou (University of Michigan) will present a promising new approach to helping teachers solve this difficulty. In one of their studies, they combined Parsons Problems and generative AI to create targeted activities for students based on the errors students had made in previous tasks. Thus they were able to provide personalised activities that directly addressed gaps in the students’ learning.

Sign up now to join our seminars

All our seminars start at 17:00 UK time (18:00 CET / 12:00 noon ET / 9:00 PT) and are held online on Zoom. To ensure you don’t miss out, sign up now to receive calendar invitations, and access links for each seminar on the day.

If you sign up today, we’ll also invite you to our 12 December seminar with Anaclara Gerosa (University of Glasgow) about how to design and structure of app安装下载 activities for young learners, the final session in our 2023 series about primary (K-5) app安装下载 education.

The post Spotlight on teaching programming with and without AI in our 2024 seminar series appeared first on app公司.

In many countries, primary school teachers are holistic educators and often find themselves teaching app安装下载 despite having little or no app软件 in the field. In a recent seminar of our series on app安装下载 education for primary-aged children, Luisa Greifenstein told attendees that struggling with debugging and negative attitudes towards programming were among the top ten challenges mentioned by teachers.

Luisa is a app安装下载er at the University of Passau, Germany, and has been working closely with both teacher trainees and app软件d primary school teachers in Germany. She’s found that giving feedback to students can be difficult for primary school teachers, and especially for teacher trainees, as programming is still new to them. Luisa’s seminar introduced a tool to help.

A unique approach: Visualising debugging with LitterBox

To address this issue, the University of Passau has initiated the primary::programming project. One of its flagship tools, LitterBox, offers a unique solution to debugging and is specifically designed for Scratch, a beginners’ programming language widely used in primary schools.

LitterBox serves as a static code debugging tool that transforms code examination into an engaging app软件. With a nod to the Scratch cat, the tool visualises the debugging of Scratch code as checking the ‘litterbox’, categorising issues into ‘bugs’ and ‘smells’:

• Bugs represent code patterns that have gone wrong, such as missing loops or specific blocks
• Smells indicate that the code couldn’t be processed correctly because of duplications or unnecessary elements

What sets LitterBox apart is that it also rewards correct code by displaying ‘perfumes’. For instance, it will praise correct broadcasting or the use of custom blocks. For every identified problem or achievement, the tool provides short and direct feedback.

Luisa and her team conducted a study to gauge the effectiveness of LitterBox. In the study, teachers were given fictitious student code with bugs and were asked to first debug the code themselves and then explain in a manner appropriate to a student how to do the debugging.

The results were promising: teachers using LitterBox outperformed a control group with no access to the tool. However, the team also found that not all hints proved equally helpful. When hints lacked direct relevance to the code at hand, teachers found them confusing, which highlighted the importance of refining the tool’s feedback mechanisms.

Despite its limitations, LitterBox proved helpful in another important aspect of the teachers’ work: coding task creation. Novice students require structured tasks and help sheets when learning to code, and teachers often invest substantial time in developing these resources. While LitterBox does not guide educators in generating new tasks or adapting them to their students’ needs, in a second study conducted by Luisa’s team, teachers who had access to LitterBox not only received support in debugging their own code but also provided more scaffolding in task instructions they created for their students compared to teachers without LitterBox.

How to maximise the impact of new tools: use existing frameworks and materials

One important realisation that we had in the Q&A phase of Luisa’s seminar was that many different app安装下载 teams are working on solutions for similar challenges, and that the impact of this app安装下载 can be maximised by integrating new findings and resources. For instance, what the LitterBox tool cannot offer could be filled by:

• Pedagogical frameworks to enhance teachers’ lessons and feedback structures. Frameworks such as PRIMM (Predict, Run, Investigate, Modify, and Make) or TIPP&SEE for Scratch projects (Title, Instructions, Purpose, Play & Sprites, Events, Explore) can serve as valuable resources. These frameworks provide a structured approach to lesson design and teaching methodologies, making it easier for teachers to create engaging and effective programming tasks. Additionally, by adopting semantic waves in the feedback for teachers and students, a deeper understanding of programming concepts can be fostered. 

• Existing courses and materials to aid task creation and adaptation. Our expert educators at the app公司 have not only created free lesson plans and courses for teachers and educators, but also dedicated non-formal learning paths for Scratch, Python, Unity, web design, and physical app安装下载 that can serve as a starting point for classroom tasks.

Exploring innovative ideas in app安装下载 education

As we navigate the evolving landscape of programming education, it’s clear that innovative tools like LitterBox can make a significant difference in the journey of both educators and students. By equipping educators with effective debugging and task creation solutions, we can create a more positive and engaging learning app软件 for students.

If you’re an educator, consider exploring how such tools can enhance your teaching and empower your students in their coding endeavours.

You can watch the recording of Luisa’s seminar here:

Sign up now to join our next seminar

If you’re interested in the latest developments in app安装下载 education, join us at one of our free, monthly seminars. In these sessions, app安装下载ers from all over the world share their innovative ideas and are eager to discuss them with educators and students. In our December seminar, Anaclara Gerosa (University of Edinburgh) will share her findings about how to design and structure early-years app安装下载 activities.

This will be the final seminar in our series about primary app安装下载 education. Look out for news about the theme of our 2024 seminar series, which are coming soon.

The post Support for new app安装下载 teachers: A tool to find Scratch programming errors appeared first on app公司.

You could attend WiPSCE with all expenses paid

WiPSCE is where teachers and app安装下载ers discuss app安装下载 that’s relevant to teaching and learning in primary and secondary app安装下载 education, to teacher training, and to related topics. You can find more information about the conference, including the preliminary programme, at wipsce.org. 

As a teacher at the conference, you will:

• Engage with high-quality international app安装下载 in the field where you teach
• Learn ways to use that app安装下载 to develop your own classroom practice
• Find out how to become an advocate in your professional community for app安装下载-informed approaches to the teaching of app安装下载.

We are delighted to welcome Google as a sponsor of WiPSCE. Google believes that every student deserves the opportunity to access the benefits of a app安装下载 education to help shape their future. However, many students aren’t getting the education they need, and teachers don’t have sufficient resources to provide it. Google recognises the responsibility they have to support organisations, universities, and schools with deep expertise and a commitment to app安装下载 education, especially within communities that have been historically underserved.

With support from Google, we will offer free places to five UK app安装下载 teachers, covering:

• The registration fee
• Two nights’ accommodation at Robinson College
• Up to £500 supply costs paid to your school to cover your teaching
• Up to £100 travel costs

To apply, you just need to fill in a short form. The application deadline is Wednesday 19 July.

The application details

To be eligible to apply:

1. You need to be a currently practising, UK-based teacher of app安装下载 (England), app安装下载 Science (Scotland), ICT or Digital Technologies (N. Ireland), or Computer Science (Wales)
2. Your headteacher needs to be able to provide written confirmation that they are happy for you to attend WiPSCE
3. You need to be available to attend the whole conference from Wednesday lunchtime to Friday afternoon
4. You need to be willing to share what you learn from the conference with your colleagues at school and with your broader teaching community, including through writing an article about your app软件 and its relevance to your teaching for this blog or Hello World magazine

The application form will ask your for:

• Your name and contact details
• Demographic and school information
• Your teaching app软件
• A statement of up to 500 words on why you’re applying and how you think your teaching practice, your school and your colleagues will benefit from your attendance at WiPSCE (500 words is the maximum, feel free to be concise)

After the 19 July deadline, we’re aiming to inform you of the outcome of your application on Friday 21 July. 

Your application will be reviewed by the 2023 WiPSCE Chairs:

• Sue Sentance, Director, app安装下载 Pi app安装下载 Education app安装下载 Centre, Department of Computer Science and Technology, University of Cambridge, UK
• Mareen Grillenberger, Endowed Chair CS Education S1 (PHSZ, PHLU, HSLU), Switzerland

Sue and Mareen will:

• Use the information you share in your form, particularly in your statement
• Select applicants from a mix of primary and secondary schools, with a mix of years of app安装下载 teaching app软件, and from a mix of geographic areas

Join us in strengthening app安装下载-informed app安装下载 classroom practice

We’d be delighted to receive your application. Being able to facilitate teachers’ attendance at the conference is very much aligned with our approach to app安装下载. Both at the app软件 and the app安装下载 Pi app安装下载 Education app安装下载 Centre, we’re committed to conducting app安装下载 that’s directly relevant to schools and teachers, and to working in close collaboration with teachers.

We hope you are interested in attending WiPSCE and becoming an advocate for app安装下载-informed app安装下载 education practice. If your application is unsuccessful, we hope you consider coming along anyway. We’re looking forward to meeting you there. In the meantime, you can keep up with WiPSCE news on Twitter.

The post Apply for a free UK teacher’s place at the WiPSCE conference appeared first on app公司.

In the final seminar in our series on cross-disciplinary app安装下载, Dr Tracy Gardner and Rebecca Franks, who work here at the app软件, described the framework underpinning the app软件’s non-formal learning pathways. They also shared insights from our recently published literature review about the impact that non-formal app安装下载 education has on learners.

Tracy and Rebecca both have extensive app软件 in teaching app安装下载, and they are passionate about inspiring young learners and broadening access to app安装下载 education. In their work here, they create resources and content for learners in coding clubs and young people at home.

How non-formal learning creates opportunities for app安装下载 education

UNESCO defines non-formal learning as “institutionalised, intentional, and planned… an addition, alternative, and/or complement to formal education within the process of life-long learning of individuals”. In terms of app安装下载 education, this kind of learning happens in after-school programmes or children’s homes as they engage with materials that have been carefully designed by education providers.

At the app公司, we support two global networks of free, volunteer-led coding clubs where regular non-formal learning takes place: Code Club, teacher- and volunteer-led coding clubs for 9- to 13-year-olds taking place in schools in more than 160 countries; and CoderDojo, volunteer-led programming clubs for young people aged 7–17 taking place in community venues and offices in 100 countries. Through free learning resources and other support, we enable volunteers to run their club sessions, offering versatile opportunities and creative, inclusive spaces for young people to learn about app安装下载 outside of the school app软件. Volunteers who run Code Clubs or CoderDojos report that participating in the club sessions positively impacts participants’ programming skills and confidence.

Rebecca and Tracy are part of the team here that writes the learning resources young people in Code Clubs and CoderDojos (and beyond) use to learn to code and create technology. 

Helping learners make things that matter to them

Rebecca started the seminar by describing how the team reviewed existing app安装下载 pedagogy app安装下载 into non-formal learning, as well as large amounts of website visitor data and feedback from volunteers, to establish a new framework for designing and creating coding resources in the form of learning paths.

As Rebecca explained, non-formal learning paths should be designed to bridge the so-called ‘Turing tar-pit’: the gap between what learners want to do, and what they have the knowledge and resources to achieve.

To prevent learners from getting frustrated and ultimately losing interest in app安装下载, learning paths need to:

• Be beginner-friendly
• Include scaffolding
• Support learners’ design skills
• Relate to things that matter to learners

When Rebecca and Tracy’s team create new learning paths, they first focus on the things that learners want to make. Then they work backwards to bridge the gap between learners’ big ideas and the knowledge and skills needed to create them. To do this, they use the 3…2…1…Make! framework they’ve developed.

Learning paths designed according to the framework are made up of three different types of project in a 3-2-1 structure:

• Three Explore projects to introduce creators to a set of skills and provide step-by-step instructions to help them develop initial confidence
• Two Design projects to allow creators to practise the skills they learned in the previous Explore projects, and to express themselves creatively while they grow in independence
• One Invent project where creators use their skills to meet a project brief for a particular audience

You can learn more about the framework in this blog post and this guide for adults who run sessions with young people based on the learning paths. And you can explore the learning paths yourself too.

Rebecca and Tracy’s team have created several new learning pathways based on the 3…2…1…Make! framework and received much positive feedback on them. They are now looking to develop more tools and libraries to support learners, to increase the app开发 of the paths, and also to conduct app安装下载 into the impact of the framework. 

New literature review of non-formal app安装下载 education showcases its positive impact

In the second half of the seminar, Tracy shared what the app安装下载 literature says about the impact of non-formal learning. She and app安装下载ers at the app软件 particularly wanted to find out what the app安装下载 says about app安装下载 education for K–12 in non-formal settings. They systematically reviewed 421 papers, identifying 88 papers from the last seven years that related to empirical app安装下载 on non-formal app安装下载 education for young learners. Based on these 88 papers, they summarised the state of the field in a literature review.

So far, most studies of non-formal app安装下载 education have looked at knowledge and skill development in app安装下载, as well as affective factors such as interest and perception. The cognitive impact of non-formal education has been generally positive. The papers Tracy and the app安装下载 reviewed suggested that regular learning opportunities, such as weekly Code Clubs, were beneficial for learners’ knowledge development, and that active teaching of problem solving skills can lead to learners’ independence.

Non-formal app安装下载 education also seems to be beneficial in terms of affective factors (although it is unclear yet whether the benefits remain long-term, since most existing app安装下载 studies conducted have been short-term ones). For example, out-of-school programmes can lead to more positive perception and increased awareness of app安装下载 for learners, and also boost learners’ confidence and self-efficacy if they have had little prior app软件 of app安装下载. The social aspects of participating in coding clubs should not be underestimated, as learners can develop a sense of belonging and support as they work with their peers and mentors.

The literature review showed that non-formal app安装下载 complements formal in-school education in many ways. Not only can Code Clubs and CoderDojos be accessible and equitable spaces for all young people, because the people who run them can tailor learning to the individuals. Coding clubs such as these succeed in making app安装下载 fun and engaging by enabling a community to form and allowing learners to make things that are meaningful to them.

What existing studies in non-formal app安装下载 aren’t telling us

Another thing the literature review made obvious is that there are big gaps in the existing understanding of non-formal app安装下载 education that need to be app安装下载ed in more detail. For example, most of the studies the papers in the literature review described took place with female students in middle schools in the US.

That means the existing app安装下载 tells us little about non-formal learning:

• In other geographic locations
• In other educational settings, such as primary schools or after-school programmes
• For a wider spectrum of learners

We would also love to see studies that hone in on:

• The long-term impact of non-formal learning
• Which specific factors contribute to positive outcomes
• Non-formal learning about aspects of app安装下载 beyond programming

3…2…1…app安装下载!

We’re excited to continue collaborating within the app软件 so that our app安装下载ers and our team creating non-formal learning content can investigate the impact of the 3…2…1…Make! framework.

This collaboration connects two of our long-term strategic goals: to engage millions of young people in learning about app安装下载 and how to create with digital technologies outside of school, and to deepen our understanding of how young people learn about app安装下载 and how to create with digital technologies, and to use that knowledge to increase the impact of our work and advance the field of app安装下载 education. Based on our app安装下载, we will iterate and improve the framework, in order to enable even more young people to realise their full potential through the power of app安装下载 and digital technologies. 

Join our seminar series on primary app安装下载 education

From January, you can join our new monthly seminar series on primary (K–5) teaching and learning. In this series, we’ll hear insights into how our youngest learners develop their app安装下载 knowledge, so whether you’re a volunteer in a coding club, a teacher, a app安装下载er, or simply interested in the topic, we’d love to see you at one of these monthly online sessions.

The first seminar, on Tuesday 10 January at 5pm UK time, will feature app安装下载ers and educators Dr Katie Rich and Carla Strickland. They will share findings on how to teach children about variables, one of the most difficult aspects of app安装下载 for young learners. Sign up now, and we will send you notifications and joining links for each seminar session.

We look forward to seeing you soon, and to discussing with you how we can apply app安装下载 results to better support all our learners.

The post Combining app安装下载 and practice to evaluate and improve app安装下载 education in non-formal settings appeared first on app公司.

We are excited to announce our next free online seminars, running monthly from January 2023 and focusing on new app安装下载 about primary school (K–5) teaching and learning of app安装下载.

Our seminars, having covered various topics in app安装下载 education over the last three years, will now offer you a close look at current questions and app安装下载 in primary app安装下载 education for 5- to 11-year-olds. Through this series we want to connect app安装下载 and teaching practice, and further primary app安装下载 education across the globe.

Are these seminars for me?

Our upcoming seminars are for everyone interested in app安装下载 education, not just for primary school teachers — you are all cordially invited to join us. Previous seminars have been attended by a valuable mix of teachers, volunteers, tech industry professionals, and app安装下载ers, all keen to explore how app安装下载 education app安装下载 can be put into practice.

Whether you teach in a classroom, or support learners in a coding club, you will find out how our youngest learners develop their app安装下载 knowledge. You’ll also explore with us what this means for your learning context in practical terms.

What you can expect from the online seminars

Each seminar starts with a presenter explaining, in easy-to-understand terms, some recent app安装下载 they have done. The presentation is followed by a discussion in smaller groups. We then regroup for a Q&A session with the presenter.

Attendees of our previous seminars have said:

“The seminar will be useful in my practice when our coding club starts.”

“I love this initiative, your choice of speakers has been fantastic. You are creating a very valuable CPD resource for Computer Science teachers and educators all over the world. Thank you. 🙏”

“Just wanted to say a huge thank you for organising this. It was brilliant to hear the presentation but also the input from other educators in the breakout room. I currently teach in a department of one, which can be quite lonely, so to join other educators was brilliant and a real encouragement.” 

Learn from specialists to benefit your own learners

Computer science has been taught in universities for many years, and only more recently has the subject been introduced in schools. That means there isn’t a lot of app安装下载 about app安装下载 education for school-aged learners yet, and even less app安装下载 about how young children of primary school age learn about app安装下载. 

That’s why we are excited to invite you to learn with us as we hear from international primary app安装下载 app安装下载 teams who share their knowledge in our online seminars:

• Tuesday 10 January 2023: Kicking off our series are Dr Katie Rich and Carla Strickland from Chicago with a seminar on how they developed new instructional materials for teaching variables in primary school. They will specifically focus on how they combined app安装下载 with classroom realities, and share app软件s of using their new materials in class. 

• Tuesday 7 February 2023: Dr Jean Salac from the University of Washington is particularly interested in identifying and addressing inequities in the app安装下载 classroom, and will speak about a new learning strategy that has been found to improve students’ understanding of app安装下载 concepts and to increase equal access to app安装下载.

• Tuesday 7 March 2023: Our own Dr Bobby Whyte from the app公司 will share practical examples of how primary app安装下载 can be integrated into literacy education. He will specifically look at storytelling elements within app安装下载 education and discuss the benefits of combining competency areas.

• May 2023: Information coming soon

• Tuesday 6 June 2023: In a collaborative seminar, Aim Unahalekhaka from Tufts University in Massachusetts will first present her app安装下载 into how children learn coding through ScratchJr. Participants are encouraged to bring a tablet or device with ScratchJr to then look at practical project evaluations and teaching strategies that can help young learners create purposefully.

• Tuesday 12 September 2023: Joining us from the University of Passau in Germany, Luisa Greifenstein will speak about how to give children appropriate feedback that encourages positive attitudes towards app安装下载 education. In particular, she will be looking at the effects of different feedback strategies and present a new Scratch tool that offers automated feedback.

• October 2023: Information coming soon

• Tuesday 7 November 2023: We are delighted to be joined by Dr Aman Yadav from Michigan State University who will focus on computational thinking and its value for primary schooling. In his seminar, he will not only discuss the unique opportunities for computational thinking in primary school but also discuss findings from a recent project that focused on teachers’ perspectives. 

Sign up now to attend the seminars

All our seminars start at 17:00 UK time (18:00 CET / 12:00 noon ET / 9:00 PT) and take place in an online format. Sign up now to receive a calendar invitation and the link to join on the day of each seminar.

We look forward to seeing you soon, and to discussing with you how we can apply app安装下载 results to better support all our learners.

The post Spotlight on primary app安装下载 education in our 2023 seminar series appeared first on app公司.