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The assumption that the rate at which students learn varies drives many common grouping, instructional, and grading practices. It may seem obvious that some students learn at a faster pace while other students need more time to make a similar amount of progress. But what if this assumption is wrong? 

What if, in fact, most learners actually learn at the same rate? A major peer-reviewed study conducted at Carnegie Mellon University set out to discover why and how some learners learn faster than others. The study included more than 7000 youth and adult learners from a variety of backgrounds, learning histories, and geographic areas, as well as 1.3 million observations, and 27 datasets. Participants were given a variety of learning tasks in math, science, and language, and their progress was closely monitored.  

To the surprise of the researchers, the data showed that there was very little variance in the pace of learning across populations. They discovered that the determinative factor is the amount of background knowledge learners bring to the learning challenge. Those labeled as “fast learners” possessed more background knowledge to apply to their learning efforts, not special skills or talents. Of course, elements such as level of motivation and strength of memory can impact the amount of persistence and length of learning retention, but these factors only complement learning efforts. 

To use a baseball metaphor, some students come to learning tasks with academic background knowledge that already places them on second or third base, while other students may have so little background knowledge that they are barely at first base. Of course, students on all three bases may be capable of reaching home and “scoring,” but the students on first base have a much longer distance to travel to be successful. In this context, it is not difficult to understand why students with limited background knowledge are less likely to “score” consistently. Yet, most grading systems are weighted heavily toward those who “cross home plate,” not how far they have come.  

This research calls into question several common assumptions about learning and traditional grading practices. As we reflect on the implications of the Carnegie Mellon study, there are several aspects of common practice worthy of debate. Here seven questions to start the discussion: 

  1. Should grades reflect what students know at the end of a teaching and learning cycle, or should grades reflect what they have learned during that cycle? 
  1. If learning success is heavily dependent on background knowledge, should more time be spent building and activating background knowledge to better “level the playing field” before engaging in new instruction? 
  1. Should students be assessed prior to instruction to facilitate the documentation of what they learn? 
  1. Does a student who initially lacked background knowledge deserve to call “foul” if another student who learned less than that student receives a higher grade? 
  1. Would giving students a grade based on what they learn regardless of their initial background knowledge be comparable to giving a prize for effort? Why or why not? 
  1. Since academic background knowledge is highly correlated with race and socioeconomic status, is grading solely on what students know at the end of a teaching and learning cycle inequitable? 
  1. Should students receive two grades: one grade for what they know and one for what they have learned during a teaching and learning cycle? 

This study raises important questions about how we engage learners and document learning. Now is a good time to reexamine our assumptions about the rate and nature of learning. We also need to revisit traditional grading practices to ensure that we are not placing too much emphasis on what students know at the expense of what they have learned.  

Reference:

Koedinger, K. R., Carvalho, P. F., Liu, R., and McLaughlin, E. A. (2023). An astonishing regularity in student learning rate. Proceedings of the National Academy of Sciences in the United States of America, 120(13). https://doi.org/10.1073/pnas.2221311120 

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