The study I briefly discuss here is closely related to one I wrote up on interleaving just a few months ago (no surprise, since the two studies share an author). You can find a free link to the article referenced in that post here.
In the latest research, the authors found that a blocked schedule (presenting examples from one category at a time) outperformed an interleaved schedule (interspersing examples from all the categories) for category learning when the examples to be classified were more highly discriminable. This result was consistent across the two experiments in the study (p = 0.055 and p = 0.04). Importantly, however, although interleaving was a better strategy for learning categories of lower discriminability, the effects across the experiments were much weaker (p = 0.2 and p = 0.08). Blocking had either a significant or close to significant effect, whereas interleaving didn't get nearly as close (if you like p-values, anyway).
The participants in the first experiment of the study (we'll only focus on that one here) were quite a bit older than I'm used to reading about in education studies: between 19 and 57 years old, with a mean age of 30. (This is similar to the previous study.) Subjects were divided into two groups, one of which was presented with images like these:
These images represent the four presented categories: long, steep; long, flat; short, steep; and short, flat. One subset of participants in this group was exposed to 64 of these images in a blocked schedule (16 from each category at a time) while the other was presented with the images in an interleaved schedule. Each example was appropriately labeled with a category letter (A, B, C, or D). After this initial exposure, subjects were then given a test on the same set of 64 images, randomly ordered, requiring them to assign the image to the appropriate category.
The other group of participants was presented with similar images (line segments) and in blocked or interleaved subsets. However, for this group the images were rotated 45 degrees. According to the researchers, this created a distinction between the groups in which the first was learning verbalizable, highly discriminable categories ("long and flat," etc.) whereas the second was learning categories difficult to express in words—categories of low discriminability.
Discussion, Questions, Connections
As mentioned above, the blocked arrangement of the examples produced a learning benefit for categories of higher discriminability when compared with interleaving. The same cannot be said for interleaving examples in the low-discriminability sequences, although the benefits for interleaving in these sequences were headed in the positive direction. So we are left to wonder about the positive effects of blocking here.
The authors suggest an answer by mentioning some data they are collecting in a separate pilot study: blocking makes it easier for learners to disregard irrelevant information.
We compared learning under a third study schedule (n = 26) in which the relevant dimensions were interleaved, but the irrelevant ones were blocked (i.e., this schedule was blocked-by-irrelevant-dimensions, as opposed to blocked-by-category), which was designed to draw learners’ attention to noticing what dimensions were relevant or irrelevant. On both the classification test and a test in which participants had to identify the relevant and irrelevant dimensions, this new blocked-by-irrelevant-dimensions condition yielded performance at a level comparable to the blocked condition and marginally better compared to the interleaved condition.
Therefore, although we initially hypothesized that participants, when studying one category at a time, are better able to compare exemplars from the same category and to generate and test their hypotheses as to the dimensions [that] define category membership (and this may still be true, particularly for Experiment 1), these pilot data suggest that with the addition of irrelevant dimensions . . . the blocking benefit is perhaps more likely driven by the fact that it allows participants to more easily identify and disregard the irrelevant dimensions.
This strikes me as making a good deal of sense. And it points to something that I may have previously confused: interleaving study examples is different from interleaving initial learning examples. When students are first learning something, blocking may be better; after acquisition, interleaving may benefit learners more.
We have a tendency, in my opinion, to ignore acquisition in learning. I'm not sure where this comes from. Perhaps it is believed that if we are justified in rejecting tabula rasa, we are safe to assume there are absolutely no rasas on any kid's tabula. At any rate, it's worth being clear about where in the learning process interleaving is beneficial—and where it may not be.
Postscript: It’s not unusual to believe, about a child’s cognitive subjectivity, that it is like a large glop of amorphous dough and that instruction or experience acts like a cookie cutter, shaping the child’s mind according to pre-made patterns and discarding the bits that don't fit.
But these results could suggest something different—that prior to learning, the world is a hundred trillion things that must be connected together, not a stew of sensation that must be partitioned into socially valuable units.
This may be why blocking could work well for newly learned categories and for so-called highly discriminable categories: because what is new to us is highly discriminable—separate, without precedent, meaningless.
Image credit: Danny Nicholson
Noh, S., Yan, V., Bjork, R., & Maddox, W. (2016). Optimal sequencing during category learning: Testing a dual-learning systems perspective Cognition, 155, 23-29 DOI: 10.1016/j.cognition.2016.06.007