NEW! ⚡NOW LbE Reporting
The new ⚡|NOW reporting allows a user to view work from the standard that is of a similar standard to their own, as well as work that is of a quality that is a little higher and a little lower.
Blog
Featured articles
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Newsletter October 2026
Despite being only a few weeks since our last Newsletter, we have plenty to share in this update, the highlight being the extension of RM Compare | ⚡NOW onto non-mobile devices.
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Stripping Back to the Song: Why RM Compare | ⚡NOW Does Less, on Purpose
When you build a mobile experience for comparative judgement, the temptation is to start with the desktop application and ask: how can we fit everything onto a smaller screen? With RM Compare |⚡NOW, we asked a different question: what does someone need to make a useful comparison, right now?
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New! RM Compare | ⚡NOW - now available on any device
Hot on the heels of the 'mobile first' release of RM Compare | ⚡NOW. we are pleased to make it accessible on any* device.
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Welcoming the New Direction: RM Compare at the Heart of Skills-Based Assessment
The announcement today that the 50% university participation target will be scrapped marks a major turning point in English education policy. As the focus shifts from traditional academic pathways to a broader, skills-driven vision, opportunities open up for learners, educators, and providers to rethink what success truly means in a rapidly changing world.
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New! Transformational assessment service for schools and school groups
The Merrick-Ed Creative Assessment Success Package marks the end of reductive assessment practices that take the joy out of teaching and learning.
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'Cognitive Offloading', 'Lazy Brain Syndrome' and 'Lazy Thinking' - unintended consequences in the age of AI
Generative AI and LLMs are everywhere in 2025 classrooms, making teaching and learning faster than ever. But as research in the Science of Learning shows, letting technology do too much of the thinking for us—“cognitive offloading”—weakens the very skills education aims to build.
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ACJ in Action: What Recent (2025) Research Reveals About Reliable Writing Assessment
Recent research (Gurel et.al 2025) dives into how adaptive comparative judgement (ACJ) performs when used to assess writing—and confirms that this approach is both robust and practical for organisations looking for fairer, more insightful assessment methods. What’s really important about these findings, and how do they connect to using ACJ tools like RM Compare?
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Update from the most comprehensive analysis of Adaptive Comparative Judgement ever undertaken
The National Science Foundation (NSF) “Learning by Evaluating” (LbE) study (Award #2101235) is the most comprehensive analysis of Adaptive Comparative Judgement (ACJ) ever undertaken—an investment of $1.257 million over five years, spanning world-class universities and K-12 settings.
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Using Google Drive shared folders as an 'aggregation' facility for multiple Item Contributors
Session Creators may want to create a single session with multiple contributors without using the Multi-Centre approach. One way of doing this is to use a shared Google Drive folder. To prevent chaos when collecting Items from teachers for example for an RM Compare session via a shared Google folder, clear and consistent guidance is essential.
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Race to Understanding: Your Item’s “Official Rating” in RM Compare
Ever wanted a single, fair number to sum up how good something is? RM Compare gives each item a Parameter Value—for this blog, think of it as its Official Rating, just like a racehorse at the track.
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How does the RM Compare AI 'Learn' - New Interactive demo
Learning for a machine is not the same as it is for a human - conflating the two is problematic but all too common. The same is true for Intelligence. With our new Interactive report you can now see how the RM Compare Machine learns.
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Where's the beef? Learning, Performance, and the Slow AI Revolution
If you’re old enough to remember the classic Wendy’s commercial, you’ll recall the irreverent demand: “Where’s the beef?” In education technology today, with all the sizzle around AI-powered assessment and automation, the same question applies. Are we seeing deeper learning—or just more output with less substance?