Encouraging learners to think first, prompt second: Using large language models to learn. Imagine this scenario: Alex, a teenaged learner, reads a homework assignment, ponders a little, and then opens an AI chatbot. A quick prompt produces a structured, well-written answer within seconds. Alex pastes the text into a document, tweaks a few words, and submits the work. For many young people, this is becoming the norm. Recent reports show that, in countries including the US and UK, over half of all teens use AI tools for homework, and 1 in 10 says they do most or all of their homework with chatbots. "I use it every day," stated one 17-year-old student in a recent study (Pew Research, 2026), and went on to say how she relies on chatbots for everything from homework to life decisions. In another study, a teenager openly admitted to using AI to cheat on assignments, essays, and book reports (Harvard GSE, 2024). This raises an important question: when AI technology does the work, what happens to the learning? Researchers are increasingly concerned that such uncritical use of AI tools may lead to cognitive offloading, where learners outsource their thinking, and the weakening of higher-order thinking skills in young people, such as problem-solving, critical thinking and creativity. To address these concerns, the Raspberry Pi Foundation and Google DeepMind have teamed up to create a new unit of research-informed lessons on large language models (LLMs) as part of Experience AI. Rather than focusing simply on how to use AI tools, the new unit helps learners understand how LLMs work, evaluate their outputs, and use them strategically to support their own learning. The unit, designed for 13- to 16-year-old learners, supports a learning-focused approach, drawing on metacognition, critical thinking, feedback literacy, and learning-centered prompt engineering. The five lessons in it support young people's cognitive development, strengthen their metacognitive skills, and bolster their ability to strategically use LLMs for their learning. They draw on extensive research within Google DeepMind's Learning team on how to scaffold around AI use to preserve 'productive struggle' and learner agency. Research-informed pedagogies. The new 'Using LLMs strategically for learning' unit is grounded in learning science research, including feedback literacy. Feedback literacy refers to the skill of actively interpreting, judging and using information when learning, instead of passively receiving information. In the unit, learners explore three types of information, also called 'feedback types': * Telling: When someone is given the answer straight away * Guiding: When someone is guided with hints * Challenging: When someone is asked questions that make them think harder Learners discover that deep learning requires a blend of all three feedback types. They also analyse LLM outputs and discover that LLMs default to providing the answer, usually in a 'tell' format. To help learners strategically use LLMs for their learning, they are provided with prompting strategies that elicit LLM outputs in 'guide' and 'challenge' formats. This helps learners engage more deeply with their own learning and develop higher-order thinking skills. Prompting techniques for learning, not just answers. To help young people strategically use LLMs for their learning, the lessons include learning-centred, platform-agnostic prompting techniques. These include strategies borrowed from research papers on the most effective prompting frameworks. To make sure that the prompting strategies in the lessons remain effective over time and can be translated into different languages when Raspberry Pi Ltd. expand the resources, Raspberry Pi Ltd. did not use acronyms, unlike most popular prompting frameworks. Building metacognition and future-ready skills. There are several industry reports highlighting the future-proof skills in the age of AI, such as problem solving, communication, critical thinking, collaboration and creativity skills. In the 'Large language models' unit, learners reflect on which skills they want to build and consider how their use of LLMs can support or hinder their development, helping them make responsible and intentional choices about using LLMs in ways that build their long-term capabilities rather than replace them. There are also activities in the lesson resources that help learners understand the long-term impacts of cognitive offloading and uncritical LLM use on the development of their future skills. The resources encourage learners to stay actively engaged in their learning and be reflective of their LLM use when learning. Uncovering LLM training data. Many young people (Pew Research, 2026) use LLMs as search engines, believing that LLMs produce outputs that are always accurate. To address that misconception, the lessons include activities that question where the training data comes from, and how accurate those sources of data are. For example, when young people discover that a portion of data that LLMs are trained on come from social media platforms like Reddit and Facebook, they are encouraged to question the quality and factuality of these sources through classroom-wide discussions. Through discussions and thinking exercises, learners are also encouraged to question whose voices, languages, cultures and perspectives are (and are not) represented in these AI models. Looking ahead. As AI tools become more integrated in young people's lives, many learners, like Alex, are tempted to turn to AI tools for quick answers, convenience, and support. The 'Using LLMs strategically for learning' unit equips young people with the skills to use LLMs effectively, critically and strategically, in ways that are most helpful to their learning. Through research-informed lessons, they explore how LLMs are created, why their outputs are not always accurate and how to evaluate AI-generated responses. Just as importantly, learners are encouraged to reflect on their own use of AI: when using an LLM supports their learning, when it does not, and how they can remain in control of their thinking, learning and skills development. With these resources, young people like Alex are not discouraged from using LLMs, but encouraged to pause, rewrite their prompts in ways that are more helpful to their learning, evaluate the outputs they receive, and stay actively involved in their own thinking. As Raspberry Pi Ltd. prepare young people for a future Raspberry Pi Ltd. do not yet know, the most important skill Raspberry Pi Ltd. can teach them is how to keep thinking. Who does the thinking, gets the learning. Acknowledgements. Raspberry Pi Ltd. would like to thank all the educators across South Africa, Nigeria, Kenya, the United Kingdom, India and beyond who piloted these resources and shared their thoughtful feedback. Their contributions helped shape and strengthen the unit. Raspberry Pi Ltd. is also grateful to Google DeepMind for their continued support in the development of this unit.

TikTok launches AI initiative literacy. 16.09.2026 11:34 TikTok has expanded its educational materials on artificial intelligence (AI) and launched guidance on the responsible use of AI-generated content. Kazakhstani content creators participated in the initiative, El.kz reports. Educational videos for users were produced by Gennady Zakharov and Asset Murzabayev. Zakharov explained how users can manage the amount of AI-generated content displayed in their recommendation feeds, while Murzabayev discussed how to identify such content and why it should be appropriately labelled. The platform has also developed guidance on the use of AI tools in cooperation with the National Association for Media Literacy Education (NAMLE) and expert Henry Ajder. In addition, TikTok is working with NoFiltr and the Raspberry Pi Foundation, organizations engaged in promoting digital literacy and developing educational resources on artificial intelligence. According to the company, educational content produced as part of the programme launched in November 2025 has generated more than 200 million views. TikTok has allocated more than 4 million dollars to support the initiative. At the same time, the platform is strengthening measures to address AI-generated spam. TikTok is testing systems designed to identify accounts that publish large volumes of generated content, including content concerning sensitive topics such as politics, financial advice and healthcare. In the first quarter of 2026, TikTok removed more than 86 million fake accounts worldwide. During the same period, the platform removed 1.28 million videos in Kazakhstan for violations of its Community Guidelines. A separate area of work focuses on the labelling of AI-generated content. According to TikTok, as of July 2026, more than 3 billion videos on the platform had received relevant labels through Content Credentials, creator disclosure tools and invisible digital watermarks. TikTok has also joined the steering committee of the Coalition for Content Provenance and Authenticity (C2PA), which develops standards for establishing the provenance and authenticity of digital content. In parallel, the company is developing the Smart Split and AI Outline tools and testing the Manage Topics feature, which enables users to regulate the proportion of AI-generated content in their recommendation feeds.

Raspberry Pi OS September update adds new Dock, revamped desktop controls. Raspberry Pi OS September 2026 update adds a new dock, revamped desktop controls, a new screenshot tool, and Linux kernel 6.18.50 LTS. Raspberry Pi has released a new Raspberry Pi OS update for September 2026, refreshing the desktop experience with a new dock, reorganized Control Centre options, a new screenshot tool, changes to the file manager, and Linux kernel 6.18.50 LTS. One of the biggest additions is dock support in wf-panel-pi, Raspberry Pi OS's desktop panel for Wayland environments. Alongside it, two new plugins have been introduced: an icon menu for launching applications and an icon-based task list for displaying open windows. The 64-bit Trixie image ships with wf-panel-pi 1.31, while the new wfplug-imenu and wfplug-wlist plugins are included as versions 0.9 and 0.8, respectively. Raspberry Pi has also added several dock-based layouts users can switch between in the Defaults section of Control Centre. In addition, a new preset for very large displays has also been added, as both wf-panel-pi and the X11-oriented lxpanel-pi now support larger 96x96-pixel icons. In Control Centre, a new Dock panel handles dock configuration, while a Widgets panel now controls dock and taskbar settings previously managed through a dialog inside wf-panel-pi. Notifications have been moved to their own Control Centre panel, replacing the previous wf-panel-pi dialog. Plus, a new Shortcuts panel lets users view and configure system keyboard shortcuts. Moreover, the Taskbar panel now offers options to hide the taskbar automatically and prevent it from overlapping maximized windows. The Desktop panel adds an option to use swaybg instead of PCManFM for drawing the desktop background. Another visible addition is a new screenshot utility. It lets users choose the default action after taking a screenshot, such as opening the image or copying it to the clipboard. Raspberry Pi OS's file management stack has changed as well. A new monolithic build called pcmanfm-pi combines PCManFM and libfm into a single application. Version 1.6 is included in the September image. For external-drive handling, you can now enable or disable automatic mounting through the ejecter panel plugin. Importantly, PCManFM no longer mounts external drives automatically by default. Under the hood, Raspberry Pi reworked the wf-panel-pi plugin architecture so plugins no longer require XML metadata files for default values. The plugin source structure was also reorganized to make behavior more consistent between lxpanel-pi and wf-panel-pi. As Raspberry Pi continues consolidating its desktop around Labwc, support for the older Wayfire compositor has now been removed from the Screens, Mouse, and Keyboard panels in Control Centre. The Wayland stack has also been updated; the release notes say both Labwc and wlroots have moved to the 0.20 series. Lastly, the update moves Raspberry Pi OS to Linux kernel 6.18.50 LTS. The image includes dedicated 6.18.50 kernel packages for both the Raspberry Pi 2712 and ARMv8 configurations. For more details, see the changelog. You can download the latest version of Raspberry Pi OS from the project's website. It continues to support a wide range of devices, including the Raspberry Pi 3B, 3B+, 3A+, 4B, 400, 5, 500, 500+, CM3, CM3+, CM4, CM4S, CM5, and the Zero 2 W. Users can update an existing Raspberry Pi OS installation from the terminal by running sudo apt update, followed by sudo apt upgrade. However, Raspberry Pi recommends using sudo apt full-upgrade for system updates because it handles dependency changes that a regular upgrade may not apply. Tell others: Bobby borisov. Bobby, an editor-in-chief at Linuxiac, is a Linux professional with over 20 years of experience. With a strong focus on Linux and open-source software, he has worked as a Senior Linux System Administrator, Software Developer, and DevOps Engineer for small and large multinational companies.