YouTube has announced a new educational partnership with former NASA engineer and science creator Mark Rober, aimed at expanding access to hands-on science learning for students in the United States.
The initiative, developed in collaboration with Rober’s education platform CrunchLabs, will introduce a new programme called Class CrunchLabs, designed specifically for students in grades three to eight. The curriculum will feature hands-on science challenges supported by a large library of video content based on Rober’s popular experiment-style formats.
According to YouTube, the programme—developed in partnership with the National Science Teaching Association (NSTA)—will include hundreds of interactive challenges and more than 1,000 educational videos, designed to make science learning more engaging and accessible in classroom environments.
YouTube noted that all video content will be available in 34 languages via a dedicated Class CrunchLabs YouTube channel, with rollout planned ahead of the back-to-school 2026 season. The platform described the initiative as part of its broader effort to position YouTube as a key destination for high-quality educational content.
The partnership builds on YouTube’s ongoing push into education-focused tools, including its “Player for Education” initiative, which aims to support classroom learning through curated video experiences. The platform has also highlighted strong adoption of video-based learning, noting that a large share of students and teachers already use YouTube content as part of their educational activities.
Through this collaboration, YouTube and CrunchLabs aim to refine and expand science learning content over time, using engaging, experiment-driven formats to inspire greater interest in STEM education among younger students.
Clear Messaging Helps Brands Improve AI Optimization
A new report from Semrush highlights how the rise of artificial intelligence chatbots is reshaping online discovery, pushing brands to rethink how they build awareness and visibility in the AI era.
The study, which analyzed 126 million AI prompts, examines how different AI systems source and reference information, offering insights into emerging AI Engine Optimization (AEO) and Generative Engine Optimization (GEO) strategies.
According to Semrush’s findings, AI platforms do not rely uniformly on sources. Instead, each system tends to reference different types of content providers, making it important for brands to understand how their information is surfaced across various AI tools.
The research also found that AI chatbots are more likely to cite specialized, topic-focused sources rather than generalist websites. This suggests that depth and relevance of content play a stronger role than broad content volume in influencing AI-generated responses.
Semrush notes that brands most consistently featured in AI outputs are those that maintain clear, focused, and consistent messaging across both owned and third-party platforms, helping AI systems form a coherent understanding of their identity and expertise.
As the report explains, brands that “publish the right content on the right surfaces” are more likely to be accurately represented in AI responses, as these systems increasingly rely on consistent signals to determine authority and relevance.
The findings suggest that in an AI-driven discovery landscape, clarity of messaging and strategic content placement are becoming critical factors in how brands are understood and surfaced by generative AI systems.
YouTube Partners with Science Creator Mark Rober
