Emma is an 8th grader who loves horses. For a school project on animal behavior, she learned all about their intelligence and complex social dynamics—and then, with her teacher’s guidance, designed an experiment to see whether horses were smart enough to learn how to read. More specifically, she showed horses one board painted with a circle and another board painted with a rectangle to try to teach them to choose the circle in order to get a treat.
This is personalized learning at its best: Students learn what they need to learn (how to design a science experiment) while getting to choose how to go about it based on their interests (horses) and curiosity (are they smart enough to read?). But, asks McREL’s Bryan Goodwin in his latest Research Matters column in Educational Leadership, how effective is this kind of learning? Does it work for everyone? What does it take to implement it well?
Goodwin points to some promising studies that show benefits, particularly for low-achieving students. A 2015 RAND Corp. study, for example, compared achievement levels of 11,000 low-income and minority students in personalized learning environments with that of similar peers nationwide and found positive effect sizes for both mathematics (0.27) and reading (0.19). Perhaps most impressive was the fact that students who started off below average on national assessments were scoring above average just three years later.