New Research Validates RM Compare Ranks as Effective On-Demand Rulers

In the ever-evolving landscape of educational assessment, Adaptive Comparative Judgement (ACJ) continues to prove its worth as a powerful and flexible tool. A recent study by Jeffrey Buckley, published in the Assessment in Education: Principles, Policy & Practice journal, provides compelling evidence that further validates the effectiveness of ACJ ranks, particularly those generated by systems like RM Compare, as on-demand rulers for assessment purposes.

Key Findings

Buckley's research, titled "Modelling approaches to combining and comparing independent adaptive comparative judgement ranks," delves into the intricacies of ACJ and offers several important insights:

  1. Consistency Across Independent Sessions: The study demonstrates that independent ACJ sessions, when properly conducted, produce remarkably consistent rank orders. This finding supports the reliability of ACJ as an assessment method and reinforces the validity of using RM Compare ranks as measurement tools.
  2. Effective Combination of Ranks: Buckley's research explores various methods for combining ranks from independent ACJ sessions. The results indicate that these combined ranks maintain high levels of consistency, further solidifying the robustness of ACJ-derived measurements.
  3. Validation of On-Demand Rulers: Perhaps most significantly for RM Compare users, the study provides strong evidence supporting the use of ACJ ranks as on-demand rulers. This means that the rank orders generated through RM Compare can be confidently used as reliable measurement scales for assessing student work or other items

Implications for RM Compare Users

These findings have several important implications for educators, researchers, and assessment professionals using RM Compare:

  1. Enhanced Confidence: Users can have increased confidence in the reliability and validity of the rank orders produced by RM Compare sessions.
  2. Flexible Assessment Options: The validation of ranks as on-demand rulers opens up new possibilities for flexible and efficient assessment practices.
  3. Scalability: The ability to combine ranks from independent sessions suggests that RM Compare can be effectively used for larger-scale assessments without compromising reliability.
  4. Continuous Improvement: This research provides a solid foundation for further refinement and development of ACJ methodologies within RM Compare.

Looking Ahead

As we continue to develop and enhance RM Compare, research like Buckley's plays a crucial role in guiding our efforts. The validation of ACJ ranks as effective on-demand rulers reinforces the value of our platform in supporting fair, reliable, and efficient assessment practices.

We're excited about the possibilities this research opens up and are committed to incorporating these insights into future updates and features for RM Compare. Stay tuned for more developments as we work to provide you with the most advanced and reliable ACJ tools available.

For those interested in diving deeper into the research, we encourage you to read Buckley's full paper, which offers a wealth of detailed analysis and insights into the world of Adaptive Comparative Judgement.

As always, we welcome your thoughts and feedback on how these findings might impact your use of RM Compare. Let's continue to push the boundaries of what's possible in educational assessment together!


Buckley, J. (2024). Modelling approaches to combining and comparing independent adaptive comparative judgement ranks. Assessment in Education: Principles, Policy & Practice.