3. Spaced practice
We often tell our students that cramming “doesn’t work”. That is good advice–but is not entirely true. As many students have discovered, “cramming”–an intense study period that occurs shortly before one’s memory is to be tested–sometimes does work. Cramming often produces adequate performance on an imminent exam (Roediger & Karpicke, 2006); unless the cramming is done instead of sleep, in which case the sleep deprivation outweighs any gains from cramming (Gillen‐O’Neel, Huynh, & Fuligni, 2013). The information learned through cramming, however, will subsequently be rapidly forgotten (Bjork & Bjork, 2011). In order for information to be retained more sustainably and over longer periods of time, it needs to be revisited on multiple occasions spaced out over time. This is known as distributed practice, or the spacing effect, which has been in the literature since Ebbinghaus first discovered it in the late 19th century (Ebbinghaus, 1885/1913). Despite much converging evidence over the past 100 years (see Cepeda, Pashler, Vul, Wixted, & Rohrer, 2006), this practice has not made its way into mainstream education (Kang, 2016).
In the cognitive literature, a distinction is made between spacing and interleaving, i.e., switching back and forth between different topics or question types within a topic (Rohrer & Taylor, 2007). That is, Storm, Bjork, and Storm (2010) showed that interleaving produces benefits that cannot entirely be accounted for by spacing. However, in practice, it is hard to imagine an educationally relevant situation in which spacing and interleaving would be dissociated. We propose, then, that the theoretical distinction between spacing and interleaving may not be critical in terms of practical applications. Instead, teachers can focus more generally on trying to provide students with opportunities to space their studying.
One implementation issue is that spacing hurts performance in the short-term, which makes it less appealing. Students typically feel overconfident when they cram, while spacing out learning leads them to feel relatively less confident (Bjork, 1999); but this is a “desirable difficulty”, which helps learning in the long-term (Bjork, 1994). When making predictions about future performance based on different study schedules, students tend to underestimate the benefits of spacing (Logan, Castel, Haber, & Viehman, 2012). Another reason why spacing might not be used by students as often as we’d like was recently suggested by Kang (2016): this strategy may require more advance planning than simply studying one topic until a saturation point is reached. More research is necessary to fine-tune implementation of spaced study schedules, and would preferably involve teachers in classrooms.
4. Frequent quizzing
The use of retrieval practice to aid learning has been a major focus of the applied cognitive literature in the past decade. As with spacing, the finding that testing strengthens memory is not new (Gates, 1917). However, the message that testing helps learning is somewhat politically charged and often lost when teachers hear the word “testing” because this activates ideas related to high-stakes standardized testing. It’s important to note that frequent testing does not have to be presented as a formal quiz; any activity that promotes retrieval of target information should help (e.g., Karpicke, Blunt, Smith, & Karpicke, 2014).
Although the mechanisms behind the retrieval practice effect are not yet fully understood, the findings are quite clear: when preparing for a test, practicing retrieving information from memory is a much more effective strategy that restudying that information (Roediger & Karpicke, 2006). This is true even when there is no opportunity to receive feedback on the quiz (Smith, Roediger, & Karpicke, 2013), as long as performance on the practice quiz is not too low (Kang, McDermott, & Roediger, 2007). The only notable exception to the retrieval practice effect is when the final test is occurring immediately after study, in which case restudying can sometimes be more effective than testing (Smith et al., 2013). However, unless students are reviewing their notes before walking into the exam room, in general it is quite rare for students to be anticipating an immediate test situation while studying. Thus, in regular exam preparation situations, a strong recommendation can be made from the literature: students ought to practice retrieval.
A good way to integrate quizzes into regular teaching is to provide opportunities for retrieval practice during learning; quiz questions interspersed during learning produce the same benefit to long-term retention as quiz questions presented at the end of a learning episode such as a lecture (Weinstein, Nunes, & Karpicke, 2016). In addition to providing retrieval practice, this method also boosts learning by maintaining test expectancy throughout the learning experience (Weinstein, Gilmore, Szpunar, & McDermott, 2014). A combined benefit of retrieval practice and spacing can be gained from engaging in retrieval practice multiple times. Creating the specific spacing schedule for a particular educational situation is tricky because it depends how strong the original memory is, and how quickly forgetting is going to happen for that information (Cepeda, Vul, Rohrer, & Wixted, 2008). Without the use of sophisticated software to schedule spacing, a more practical suggestion may be for teachers to include quiz questions from previous topics throughout the semester, in order to facilitate a reasonable amount of spaced practice.
There is an unending supply of suggestions on how students can learn information more effectively. Here we draw from established cognitive psychology research and distill four simple strategies to enhance classroom learning. These four strategies are: (1) providing visual examples, (2) teaching students to explain and to do, (3) spaced practice, and (4) frequent quizzing. More specifically: (1) Try to present information with both text and pictures; (2) Get students to explain the information they are learning, or if possible, have them act things out; (3) Create opportunities to revisit information over the course of a semester; and (4) Include low-stakes quizzes throughout learning to provide retrieval practice. Critically, each of these strategies is strongly supported by extant research and can be readily implemented in the classroom.
Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe and A. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 185–205). Cambridge, MA: MIT Press.
Bjork, R. A. (1999). Assessing our own competence: Heuristics and illusions. In D. Gopher and A. Koriat (Eds.), Attention and Performance XVII. Cognitive regulation of performance: Interaction of theory and application (pp. 435-459). Cambridge, MA: MIT Press.
Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In M. A. Gernsbacher, R. W. Pew, L. M. Hough, & J. R. Pomerantz (Eds.), Psychology and the real world: Essays illustrating fundamental contributions to society (pp. 56-64). New York: Worth Publishers.
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132, 354-380. doi: 10.1037/0033-2909.132.3.354
Chi, M. T., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145-182. doi: 10.1207/s15516709cog1302_1
Chi, M. T., De Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439-477. doi: 10.1016/0364-0213(94)90016-7
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. London: Learning & Skills Research Centre.
Cohen, R. L. (1981). On the generality of some memory laws. Scandinavian Journal of Psychology, 22, 267–281.
Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11, 671–684.
Dunlosky, J., Rawson, K. A., Marsh, E. L., 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, 4-58. doi: 10.1177/1529100612453266
Ebbinghaus, H. E. (1885/1913). Memory: A contribution to experimental psychology. New York: Teachers College, Columbia University.
Engelkamp, J., & Cohen, R. L. (1991). Current issues in memory of action events. Psychological Research, 53, 175-182. doi: 10.1007/BF00941384
Engelkamp, J., & Zimmer, H. D. (1984). Motor programme information as a separable memory unit. Psychological Research, 46, 283–299. doi: 10.1007/BF00308889
Gates, A. I. (1917). Recitation as a factor in memorizing. New York: The Science Press
Gillen-O’Neel, C., Huynh, V. W., & Fuligni, A. J. (2013). To study or to sleep? The academic costs of extra studying at the expense of sleep. Child Development, 84, 133-142. doi: 10.1111/j.1467-8624.2012.01834.x
Hattie, J., & Yates, G. (2014). Visible learning and the science of how we learn. New York: Routledge.
James, W. (1899). Talks to teachers on psychology: And to students on some of life's ideals. New York: Henry Holt and Company. Accessible from https://ebooks.adelaide.edu.au/j/james/william/talks/.
Kahl, B., & Woloshyn, V. E. (1994). Using elaborative interrogation to facilitate acquisition of factual information in cooperative learning settings: One good strategy deserves another. Applied Cognitive Psychology, 8, 465-478. doi: 10.1002/acp.2350080505
Kang, S. H. (2016). Spaced repetition promotes efficient and effective learning policy implications for instruction. Policy Insights from the Behavioral and Brain Sciences, 3, 12-19. doi: 10.1177/2372732215624708.
Kang, S. H., McDermott, K. B., & Roediger III, H. L. (2007). Test format and corrective feedback modify the effect of testing on long-term retention. European Journal of Cognitive Psychology, 19, 528-558. doi: 10.1080/09541440601056620
Karpicke, J. D., Blunt, J. R., Smith, M. A., & Karpicke, S. S. (2014). Retrieval-based learning: The need for guided retrieval in elementary school children. Journal of Applied Research in Memory and Cognition, 3, 198-206. doi:10.1016/j.jarmac.2014.07.008
Kirschner, P. A., & van Merriënboer, J. J. (2013). Do learners really know best? Urban legends in education. Educational Psychologist, 48, 169-183. doi: 10.1080/00461520.2013.804395
Lockhart, R. S., & Craik, F. I. M. (1990). Levels of processing: A retrospective commentary on a framework for memory research. Canadian Journal of Psychology, 44, 87–112. doi: 10.1037/h0084237
Logan, J. M., Castel, A. D., Haber, S., & Viehman, E. J. (2012). Metacognition and the spacing effect: the role of repetition, feedback, and instruction on judgments of learning for massed and spaced rehearsal. Metacognition and Learning, 7, 175-195. doi: 10.1007/s11409-012-9090-3
Madan, C. R., Glaholt, M. G., & Caplan, J. B. (2010). The influence of item properties on association-memory. Journal of Memory and Language, 63, 46-63. doi:10.1016/j.jml.2010.03.001
Madan, C. R., & Singhal, A. (2012). Using actions to enhance memory: Effects of enactment, gestures, and exercise on human memory. Frontiers in Psychology, 3, 507. doi:10.3389/fpsyg.2012.00507
Moscovitch, & H. L. Roediger (Eds.), Perspectives on human memory and cognitive aging: Essays in honour of Fergus I. M. Craik (pp. 28-47). Philadelphia: Psychology Press.
Paivio, A. (1986). Mental representations: A dual coding approach. New York: Oxford University Press.
Paivio, A., & Csapo, K. (1969). Concrete image and verbal memory codes. Journal of Experimental Psychology, 80, 279-285. doi: 10.1037/h0027273
Paivio, A., & Csapo, K. (1973). Picture superiority in free recall: Imagery or dual coding? Cognitive Psychology, 5, 176-206. doi: 10.1016/0010-0285(73)90032-7
Pashler, H., Bain, P. M., Bottge, B. A., Graesser, A., Koedinger, K., McDaniel, M., & Metcalfe, J. (2007). Organizing instruction and study to improve student learning (NCER 2007-2004). Washington, DC: National Center for Education Research, Institute of Education Sciences, U.S. Department of Education. Retrieved from http://ncer.ed.gov.
Pomerance, L., Greenberg, J., and Walsh, K. (January 2016). Learning About Learning: What Every New Teacher Needs to Know. Washington, D.C.: National Council on Teacher Quality. Retrieved from http://www.nctq.org/dmsView/Learning_About_Learning_Report.
Pressley, M., McDaniel, M. A., Turnure, J. E., Wood, E., & Ahmad, M. (1987). Generation and precision of elaboration: Effects on intentional and incidental learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13(2), 291-300. doi: 10.1037/0278-73220.127.116.111
Roediger, H. L. (2013). Applying cognitive psychology to education: Translational educational science. Psychological Science in the Public Interest, 14,1-3. doi: 10.1177/1529100612454415
Roediger, H. L., & Gallo, D. A. (2002). Levels of processing: Some unanswered questions. In M. Naveh-Benjamin, M. Moscovitch, & H. L. Roediger (Eds.), Perspectives on human memory and cognitive aging: Essays in honour of Fergus I. M. Craik (pp. 28-47). Philadelphia: Psychology Press.
Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17, 249-255. doi: 10.1111/j.1467-9280.2006.01693.x
Smith, B. L., Holliday, W. G., & Austin, H. W. (2010). Students' comprehension of science textbooks using a question‐based reading strategy. Journal of Research in Science Teaching, 47, 363-379. doi: 10.1002/tea.20378
Smith, M. A., Roediger, H. L., & Karpicke, J. D. (2013). Covert retrieval practice benefits retention as much as overt retrieval practice. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 1712-1725. doi: 10.1037/a0033569
Storm, B. C., Bjork, R. A., & Storm, J. C. (2010). Optimizing retrieval as a learning event: When and why expanding retrieval practice enhances long-term retention. Memory & Cognition, 38, 244-253. doi: 10.3758/MC.38.2.244
Rohrer, D., & Pashler, H. (2012). Learning styles: Where's the evidence? Medical Education, 46, 34-35. doi: 10.1111/j.1365-2923.2012.04273.x
Rohrer, D., & Taylor, K. (2007). The shuffling of mathematics practice problems improves learning. Instructional Science, 35, 481-498. doi: 10.1007/s11251-007-9015-8
Thomas, P. L., & Goering, C. Z. (2016, March). Review of learning about learning: What every new teacher needs to know. Retrieved from http://nepc.colorado.edu/thinktank/review-teacher-education
Wammes, J. D., Meade, M. E., & Fernandes, M. A. (2015). The drawing effect: Evidence for reliable and robust memory benefits in free recall. Quarterly Journal of Experimental Psychology, 69, 1752-1776. doi: 10.1080/17470218.2015.1094494
Weinstein, Y., Gilmore, A. W., Szpunar, K. K., & McDermott, K. B. (2014). The role of test expectancy in the build-up of proactive interference in long-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40, 1039-1048. doi: 10.1037/a0036164
Weinstein, Y., Nunes, L. D., & Karpicke, J. D. (2016). On the placement of practice questions during study. Journal of Experimental Psychology: Applied, 22, 72-84. doi: 10.1037/xap0000071
Megan Smith is an Assistant Professor at Rhode Island College. She received her Master’s in Experimental Psychology at Washington University in St. Louis and her PhD in Cognitive Psychology from Purdue University. Megan’s area of expertise is in human learning and memory, and applying the science of learning in educational contexts. Megan is passionate about bridging the gap between research and practice in education. In an effort to promote more conversations between researchers and practitioners, she co-founded The Learning Scientists (www.learningscientists.org). Her research program focuses on retrieval-based learning strategies, and the way activities promoting retrieval can improve meaningful learning in the classroom. Megan addresses empirical questions such as: What retrieval practice formats promote student learning? What retrieval practice activities work well for different types of learners? And, why does retrieval increase learning?
Christopher Madan is a Postdoctoral Fellow at Boston College. He received his PhD in Psychology from the University of Alberta. Chris’ area of expertise is in human memory and decision making, particularly in factors that can make some information more memorable. He studies the role of factors intrinsic to the to-be-remembered information, such as emotion and reward, as well as mnemonic strategies, particularly the Method of Loci. His research program is particularly interested in how biases in memory encoding and retrieval can manifest in other cognitive domains. Chris uses a variety of methodological approaches, including cognitive psychology, neuroimaging, and computational modeling to investigate ‘what makes memories last’.
Yana Weinstein is an Assistant Professor at University of Massachusetts, Lowell. She received her PhD in Psychology from University College London and had 4 years of postdoctoral training at Washington University in St. Louis. The broad goal of her research is to help students make the most of their academic experience. Yana's research interests lie in improving the accuracy of memory performance and the judgments students make about their cognitive functions. Yana tries to pose questions that have direct applied relevance, such as: How can we help students choose optimal study strategies? Why are test scores sometimes so surprising to students? And how does retrieval practice help students learn? She recently co-founded The Learning Scientists (www.learningscientists.org) with Megan Smith.