By: Nathan Foster, Ph.D., The College of Wooster
Professors, educators, and graduate students just beginning their teaching careers are familiar with this scene: A student comes to office hours a day before an exam asking for help and clarification on topics that were introduced weeks prior. The meeting reveals the student is just now starting to study and learn the content. Why is the student electing to learn all the content at the last minute? Furthermore, the student is organizing their studying by reviewing material of similar topics and mastering this material in a block before moving to a new topic, despite research showing the opposite behavior, interleaving different topics, is most likely better for learning (Dunlosky et al., 2013). Do students intentionally select poor study strategies knowing these strategies are ineffective, or do they simply not understand that their strategies of choice lead to poor learning outcomes?
The extent to which students misunderstand the consequences of their study behaviors may come from the disconnect between what students know and what they think they know. For example, we found that students were overconfident in their performance when asked to predict their success on an upcoming exam (Foster et al., 2016). Upon receiving immediate feedback on the exam, these students persisted in their overconfidence by aiming high on a prediction for their next exam. Surprisingly, this pattern of blind overconfidence continued across thirteen weekly exams during the semester—students could not boost their scores to meet their aspirations, nor would they lower their aspirations to be consistent with their scores.
In addition to overconfidence, students may be unaware of the benefits of certain study strategies. Overwhelming evidence has demonstrated the benefits of spaced practice over mass practice on memory (see Cepeda et al., 2006, for a review). Similarly, in what is known as the interleaving effect, mixing retrieval of different volume formulas, compared to retrieving formulas in blocks, produced better memory for these formulas later on (Rohrer & Taylor, 2007). When given a choice in a laboratory learning experiment, participants decided to mass their study of items judged as more difficult when they should have engaged in spaced practice of these items (Son, 2004). Furthermore, Yan, Bjork, and Bjork (2016) had participants study paintings from different artists and later asked them to imagine they were art teachers and to recommend a study schedule to their students of either blocked practice (where example paintings from each artist were studied separately in blocks) or interleaved practice (where example paintings from different artists were studied together). Results indicated that participants were more likely to recommend blocked practice than interleaved practice. Even when interleaved practice had benefited their own performance, participants were hesitant to recommend interleaved practice and instead split their recommendations for the two strategies approximately 50/50. People don’t seem to know what study strategies are best for learning even when they themselves have benefited from these strategies.
One possibility for why students may be reluctant to adopt study strategies like spacing and interleaved practice may come from the ambiguity of these strategies. For example, interleaved practice itself may boost learning because problems from different categories are studied back-to-back, forcing the learner to contrast the concepts. Here, the defining characteristic of a concept is more likely to be highlighted when that concept is contrasted with a similar concept (e.g. ABABAB) compared to when the concepts are blocked (e.g., AAABBB). Alternatively, interleaving can benefit learning compared to blocking simply because concepts are spaced in an interleaved practice schedule. According to this view, learning concept A will benefit equally when A is interleaved with concept B (e.g., ABABAB) and when A is interleaved with an unrelated concept, X (e.g., AXAXAX). In both examples, A receives the same “amount” of spaced practice, and learning is benefitted because of this spacing, not because of any conceptual enhancement gained from contrasting A to B, versus contrasting A to X.
Fortunately, recent research evaluated whether the contrast mechanism or the spacing mechanism is what produces benefits in interleaved practice. Foster et al. (2019) had participants study four volume formulas, borrowed from Rohrer and Taylor (2007) (see Figure 1). Participants practiced according to an interleaved or a blocked schedule. Interleaving involved successively practicing a single wedge, spheroid, spherical cone, and half cone problem, and then repeating that interleaved sequence three more times. By contrast, blocking involved practicing four wedge problems successively, followed by four spheroid problems, etc. Importantly, two additional “remote” practice groups were included. In remote-interleaving, wedge problems were interleaved with non-volume problems like adding fractions and dividing exponents. In remote-blocking, four wedge problems were practiced in a block before practicing the other non-volume problems. Results indicated that wedge performance on a week-delayed final test of formula retrieval was better for interleaved than blocked practice. But, critically, an equivalent boost in learning was observed for remote-interleaving compared to remote-blocking (see Figure 2). These results support the notion that interleaving helps because of spacing, not contrast. However, to the extent that interleaving benefits learning because of contrast may be highly dependent on what is being learned (e.g., contrasting may benefit highly confusable concepts like bird species or artists’ paintings more than math formulas).
If students understood that managing their study time to allow for spaced practice is the critical ingredient for learning, they may be more inclined to adopt spaced practice as a study behavior. Indeed, interleaved practice necessarily spaces out target content, but it does this while simultaneously swapping in practice of other materials, which students may perceive as an unappealing strategy. Future efforts to understand student learning should focus on both the metacognitive beliefs about study behaviors and techniques as well as the underlying mechanisms of the strategies themselves.
Figure 1. Materials from Rohrer & Taylor (2007)
Figure 2. Experiment 2 Results from Foster, Mueller, Was, Rawson, & Dunlosky, (2019)
Cepeda, N., J., Pashler, H., Vul, E., Wixted, J. T., Rohrer, D. (2008). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132, 354-380.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4-59.
Foster, N. L., Mueller, M. L., Was, C. A., Rawson, K. A., Dunlosky, J. (2019). Why does interleaving improve math learning? The contributions of discriminative contrast and distributed practice. Memory & Cognition, 47, 188-1101. https://doi.org/10.3758/s13421-019-00918-4
Foster, N. L., & Was, C. A., Dunlosky, J., & Isaacson, R. M. (2016). Even after thirteen exams, students are still overconfident: The role of memory for past exam performance in student predictions. Metacognition and Learning, 12, 1-19. http://doi.org/10.1007/s11409-016-9158-6
Rohrer, D., & Taylor, K. (2007). The shuffling of mathematics problems improves learning. Instructional Science, 35, 481-498.
Son, L. K. (2004). Spacing one’s study: Evidence for a metacognitive control strategy. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 601-604.
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, 918-933.
Nathan Foster is an Assistant Professor of Psychology at The College of Wooster. He teaches courses on memory, cognition, and statistics in psychology. His research program investigates the cognitive processes of human memory with a focus on metacognition, concept learning, and the intentional forgetting of unwanted information.