Cherry Picking? Or Making Better Trees?

Everyone knows that cherry picking is bad. Bad, bad, bad, bad, bad, bad, bad. Cherry picking means showing non-representative examples to give a false impression of the quality of a product, an argument, or a scientific finding. In educational research, for example, cherry picking might mean a publisher or software developer showing off a school using their product that is getting great results, without saying anything about all the other schools using their product that are getting mediocre results, or worse. Very bad, and very common. The existence of cherry picking is one major reason that educational leaders should always look at valid research involving many schools to evaluate the likely impact of a program. The existence of cherry picking also explains why preregistration of experiments is so important, to make it difficult for developers to do many experiments and then publicize only the ones that got the best results, ignoring the others.

However, something that looks a bit like cherry picking can be entirely appropriate, and is in fact an important way to improve educational programs and outcomes. This is when there are variations in outcomes among various programs of a given type. The average across all programs of that type is unimpressive, but some individual programs have done very well, and have replicated their findings in multiple studies.

As an analogy, let’s move from cherries to apples. The first delicious apple was grown by a farmer in Iowa in 1880. He happened to notice that fruit from one particular branch or one tree had a beautiful shape and a terrific flavor. The Stark Seed Company was looking for new apple varieties, and they bought his tree They grafted the branch on an ordinary rootstock, and (as apples are wont to do), every apple on the grafted tree looked and tasted like the ones from that one unusual branch.

blog_4-16-20_applepicking_333x500 Had the farmer been hoping to sell his whole orchard, and had he taken potential buyers to see this one tree, and offered potential buyers picked apples from this particular branch, then that would be gross cherry-picking. However, he knew (and the Stark Seed Company knew) all about grafting, so instead of using his exceptional branch to fool anyone (note that I am resisting the urge to mention “graft and corruption”), the farmer and Stark could replicate that amazing branch. The key here is the word “replicate.” If it were impossible to replicate the amazing branch, the farmer would have had a local curiosity at most, or perhaps just a delicious occasional snack. But with replication, this one branch transformed the eating apple for a century.

Now let’s get back to education. Imagine that there were a category of educational programs that generally had mediocre results in rigorous experiments. There is always variation in educational outcomes, so the developers of each program would know of individual schools using their program and getting fantastic results. This would be useful for marketing, but if the program developers are honest, they would make all studies of their program available, rather than claiming that the unusual super-duper schools represent what an average school that adopts their program is likely to obtain.

However, imagine that there is a program that resembles others in its category in most ways, yet time and again gets results far beyond those obtained by similar programs of the same type. Perhaps there is a “secret sauce,” some specific factor that explains the exceptional outcomes, or perhaps the organization that created and/or disseminates the program is exceptionally capable. Either way, any potential user would be missing something if they selected a program based on the mediocre average achievement outcomes for its category. If the outcomes for one or more programs are outstanding (and assuming costs and implementation characteristics are similar), then the average achievement effects for the category should no longer be particularly relevant, because any educator who cares about evidence should be looking for the most effective programs, since no one would want to implement an entire category.

I was thinking about apples and cherries because of our group’s work reviewing research on various tutoring programs (Neitzel et al., 2020). As is typical of reviews, we were computing average effect sizes for achievement impacts of categories. Yet these average impacts were much less than the replicated impacts for particular programs. For example, the mean effect size for one-to-small group tutoring was +0.20. Yet various individual programs had mean effect sizes of +0.31, +0.39, +0.42, +0.43, +0.46, and +0.64. In light of these findings, is the practical impact of small group tutoring truly +0.20, or is it somewhere in the range of +0.31 to +0.64? If educators chose programs based on evidence, they would be looking a lot harder at the programs with the larger impacts, not at the mean of all small-group tutoring approaches

Educational programs cannot be replicated (grafted) as easily as apple trees can. But just as the value to the Stark Seed Company of the Iowa farmer’s orchard could not be determined by averaging ratings of a sampling of all of his apples, the value of a category of educational programs cannot be determined by its average effects on achievement. Rather, the value of the category should depend on the effectiveness of its best, replicated, and replicable examples.

At least, you have to admit it’s a delicious idea!

References

Neitzel, A., Lake, C., Pellegrini, M., & Slavin, R. (2020). A synthesis of quantitative research on programs for struggling readers in elementary schools. Available at www.bestevidence.org. Manuscript submitted for publication.

 

This blog was developed with support from the Laura and John Arnold Foundation. The views expressed here do not necessarily reflect those of the Foundation.

Note: If you would like to subscribe to Robert Slavin’s weekly blogs, just send your email address to thebee@bestevidence.org

 

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