R3 2.10 June 13, 2024 Do Students Choose Better Study Sequences When Learning Is a Matter of Life and Death?
A new article on interleaving suggests that raising the stakes significantly changes learner strategies - for the better.
In this issue, we’ll take a look at this new study: Some Fungi Are Not Edible More Than Once: The Impact of Motivation to Avoid Confusion on Learners’ Study Sequence Choices. The article’s sardonic title is what initially caught my eye, but once I got into reading it, I found an intriguing set of findings on what I think is one of the most interesting and frequently misunderstood phenomena in memory: the effect of interleaving.
Interleaving refers to how learners approach study tasks that require them to learn the differences between categories or groupings, so that they can identify new examples and discriminate them accurately even when categories are easily confused. Consider the case of a student learning to identify the work of artists from a particular style, say, Abstract Expressionist painters. They’ll need to be able to tell Pollock from Krasner from Rothko, all on the basis of the examples they’ve studied. In an interleaved study sequence, they’ll alternate between looking at works from different artists – a Pollock, a Krasner, then a Rothko, then back to Pollock, two Rothkos and so on. Interleaving has been shown to produce better category learning, especially in terms of being able to distinguish similar examples, compared to the alternative, which is termed a blocked sequence. Blocking means studying category examples in orderly groups – all the Rothkos, then all the Krasners, and so on.
That’s a complicated explanation, but interleaving itself is more complicated than most other applied-memory phenomena. It’s a topic that I tend to approach with caution when talking with faculty, as it’s easy to confuse with a slew of other factors and approaches: study breaks, switching topics, the spiral curriculum and any number of things that might look superficially similar to interleaving. Interleaving is also only relevant in a relatively narrow set of disciplines and learning tasks. Unlike, for example, retrieval practice, it isn’t something that is likely to work in pretty much any kind of course involving memory retention.
All the same, in situations where it is relevant, interleaving is a powerful way to accelerate learning. It’s something that can be built into quiz applications and other tools as well. Furthermore, it is not something that students are likely to spontaneously do on their own. There’s a long line of research showing that given the option, students prefer to group category examples or problem types together, blocking-style. This strategy may give the illusion of efficiency or may simply be easier to get through, but regardless of why they do it, students lose ground when they go for blocking.
Today’s article takes a new look at the well-established bias toward blocking over interleaving, asking whether there are circumstances that could override that bias, and if so, whether better category learning performance follows. To do this, the author designed a task which, if carried out in the real world, would involve real physical danger in case of category confusion.
Citation:
Abel, R. (2023). Some fungi are not edible more than once: The impact of motivation to avoid confusion on learners’ study sequence choices. Journal of Applied Research in Memory and Cognition, 13(1), 103–112.
DOI:
Paywall or Open:
Paywall
Summary:
Typically, students engaged in category learning choose blocked over interleaved study sequences, preferring to study category members grouped together despite the fact that the blocked approach is less effective. The present study sought to test whether learners are more likely to choose interleaving when the categories in question have high intrinsic value – such as when confusing two categories could lead to death. Participants designed study sequences to learn to tell poisonous from edible mushrooms. Results demonstrated that interleaving was more prevalent for the high intrinsic value discrimination versus a low-intrinsic-value discrimination (mushrooms preferring acidic over neutral or basic soil), and suggested that better overall performance on the high-value category discrimination task was partially due to the interleaving strategy.
Research Questions:
- Are learners more likely to choose interleaving over blocking as a study strategy when learning to discriminate high intrinsic value categories (e.g., poisonous vs. edible mushrooms)?
- Is the learning advantage associated with high intrinsic value category distinctions mediated by choosing interleaving as a study strategy? (In other words – are high intrinsic value distinctions better learned because of interleaving, or because of other reasons?)
Sample:
160 participants recruited via an online platform; slightly over half were university students. Overall, 30.6% of the sample had a university degree, and the mean age was 31.14 years. Participants were excluded if they were aware of the research on interleaving (11 total within the original sample).
Method/Design:
Participants were randomly assigned to either the high or low intrinsic value condition (i.e., poisonous/edible or acidic/neutral soil). Each group viewed an identical set of photographs of different mushrooms with equal numbers of poisonous/nonpoisonous or acidic/neutral species. Each mushroom in one group had a similar-appearing counterpart in the other group, termed “confusable mushroom doubles.” (These were accurate examples, with photos of actual specimens taken by mushroom experts used by permission.)
Participants created their own study sequence of 36 pictures that they would choose to study prior to the test. They completed their own self-created study sequence by viewing pictures in the order they had chosen, then engaged in distractor tasks prior to completing the final test. The test had two phases; in the first, images of mushrooms were classified according to category (edible/poisonous or acidic/neutral, depending on which condition the participant had been assigned to), and in the second, images were matched to their species names. Images used in the final test were new, never-before seen images of the same species that had been studied.
After the test, learners were asked about which study strategy they though was most effective: one type at a time (blocked) or alternating (interleaved). To assess actual sequencing preferences, researchers calculated an “interleaving index,” which took into account switches between confusable doubles specifically and different mushroom types generally.
Key Findings:
In general, learners preferred to construct blocked study sequences, replicating typical patterns in the literature on interleaving. Interleaving was significantly more likely in the high intrinsic value condition. Interleaved learning of confusable doubles was significantly correlated with categorization performance, and mediation analysis revealed that interleaving significantly mediated the relationship between intrinsic value and performance, although other factors were also at work (i.e., mediation was partial rather than full).
Intrinsic value did not improve learning of subordinate categories, i.e., the ability to correctly identify individual species (versus categorizing them). There were also no differences in stated preferences for blocked versus interleaved sequences, across intrinsic value conditions.
Researchers interpreted the findings as demonstrating that learners have a preference for blocking generally, yet have some awareness that alternating similar categories will help them detect differences. High levels of motivation to avoid confusion therefore can override the default bias toward blocking.
Choice Quote from the Article:
To be able to reliably distinguish between edible mushrooms and their looking alike poisonous doubles, learners need to study the mushrooms in an interleaved manner, that is, by switching and juxtaposing confusable exemplars. The results of the present research suggest that when faced with an imaginative survival threat (edible and poisonous mushrooms), learners make more study sequence choices toward interleaving as compared with a no surviving relevance condition (studying same mushrooms labeled as growing on acidic soil and growing on basic to neutral soil). Interleaved study sequence choices in turn enable learners to detect subtle differences and avoid confusion. We conclude that learners might be more or less aware of that interleaving supports the detection of differences. Nonetheless, learners usually stick to blocking because they might not consider finding differences an important learning objective.
Why it Matters:
I’ve long been interested in the differences between classroom learning and more applied, high-stakes learning, the kind we associate with using knowledge in the real world. In theory, there’s nothing inherently different about learning-for-class and learning-for-life. But this research uncovers one reason why these seem so different, and perhaps also helps explain the particularly heartbreaking (to a teacher) refrain from professionals in various fields that they didn’t really start learning anything useful until they were out in the working world. To me, it raises the question of what could happen if we brought more of these real-world, real-consequences stakes to classroom learning.
And besides adding something new to the study of interleaving, this work also revives a theme that was popular in memory research a bit more than a decade ago, and for which I still have a soft spot: survival processing or survival relevance. Under this idea, our minds retain special ways of handling information relating to threats that determined survival in our ancestral environments. I see it as part of a larger perspective on memory, what I’ve termed an adaptive view – the idea that memory isn’t just a system for holding whatever information we dump into it, but rather selects and retains what is likeliest to help us survive, thrive, and accomplish our goals. It’s something I wrote about in this article from 2011 and that continues to shape how I think about memory today.
The study also reopens, for me, some questions about what students know about effective study techniques, and what kinds of influences can nudge them in that direction. It took me right back to R3 1.1, which featured two other articles on what kinds of study schedules students voluntarily picked when given the choice, and how to not only inform, but also persuade them to pick different ones when their choices were sub-optimal. Lastly, I appreciated the distinction that the author drew between survival motivation and more general motivation to learn. One is, perhaps, a subset of the other, but this is a good reminder that just saying “this is important to know!” won’t sear information into anybody’s memory.
Most Relevant For:
Instructional designers; faculty teaching material that requires students to learn important distinctions between categories; researchers studying interleaving and related issues in applied memory research
Limitations, Caveats, and Nagging Questions:
The author discusses one particular limitation in some depth: the lack of “predictive features” in this study’s materials. Essentially, this means that there were no recognizable patterns that could, in themselves, distinguish edible from poisonous mushrooms (or in the control condition, acidic soil/neutral soil mushrooms). Each example simply had to be memorized on its own. This is different than many other kinds of categories, which gain structure from common features - such as stylistic flourishes that tie together one artist’s body of work, or characteristics that a class of animals might all share.
Within the research field of category learning, this is a big deal, but I don’t think it limits the applicability of this work to academic learning tasks. Other research in this area sometimes uses artificially contrived stimuli for this reason, so that specific features can be controlled and their impact examined. It would be interesting to see if you could get similar results for stimuli such as nonsense shapes if you told research volunteers that the shapes correspond to some kind of life or death decision – hostile versus friendly aliens, or symbols for poison in a fictional foreign language? Then, the common category features could be examined.
If you liked this article, you might also appreciate:
Eglington, L. G., & Kang, S. H. K. (2017). Interleaved presentation benefits science category learning. Journal of Applied Research in Memory and Cognition, 6(4), 475–485. https://doi.org/10.1016/j.jarmac.2017.07.005
Hartwig, M. K., Rohrer, D., & Dedrick, R. F. (2022). Scheduling math practice: Students’ underappreciation of spacing and interleaving. Journal of Experimental Psychology: Applied, 28(1), 100–113. https://doi.org/10.1037/xap0000391
Kang, S. H. K., & Pashler, H. (2014). Is the benefit of retrieval practice modulated by motivation? Journal of Applied Research in Memory and Cognition, 3(3), 183–188. https://doi.org/10.1016/j.jarmac.2014.05.006
Kang., S.H.K. (2023). Interleaved training and category learning. In C. E. Overson, C.M. Hakala, L.L. Kordonowy, & V.A. Benassi, (Eds.) In their own words: What scholars and teachers want you to know about why and how to apply the science of learning in your academic setting. Society for the Teaching of Psychology.
Karpicke, J. D., Butler, A. C., & Roediger, H. L. (2009). Metacognitive strategies in student learning: Do students practise retrieval when they study on their own? Memory, 17(4), 471–479. https://doi.org/10.1080/09658210802647009
McDaniel, M. A., Einstein, G. O., & Een, E. (2021). Training college students to use learning strategies: A framework and pilot course. Psychology Learning and Teaching, 20(3), 364–382. https://doi.org/10.1177/1475725721989489
Miller, M.D. (2009) What the science of cognition tells us about instructional technology. Change: The Magazine of Higher Learning, 41, 71-74.
Miller, M.D. (2011). What college teachers should know about memory: A perspective from cognitive psychology. College Teaching, 59, 117-122. https://doi.org/10.1080/87567555.2011.580636
Miller, M.D. (2014). Minds online: Teaching effectively with technology. Harvard University Press.
Yan, V. X., Bjork, E. L., & Bjork, R. A. (2016). On the difficulty of mending metacognitive illusions: A priori theories, fluency effects, and misattributions of the interleaving benefit. Journal of Experimental Psychology: General, 145(7). https://doi.org/10.1037/xge0000177
File under:
Study schedules; interleaving; category learning; metacognition; motivation