Abstract
Flashcards are a popular study tool, however learner decisions can lower their effectiveness. One such decision is whether or not to drop a concept from study. Using objective mastery criteria that adaptively determine when to add or drop an item from study based on performance may improve learning outcomes in flashcard-based tasks. The effectiveness of adaptive flashcard-based learning may also vary based on the cognitive ability of the learner. The current study examined the impact of adaptive mastery instructional strategies on learning butterfly species and whether or not the impact of adaptive mastery varies by cognitive ability. Three learning conditions were compared: a No Add/Drop group (all items remain in the deck throughout study), a Mastery Drop group (start with all items, then drop after an item is mastered), and a Mastery Add group (start with three items, add items once mastered). A pre-post-transfer test design was used both immediately after training and one week later. Participants also completed the symmetry span task and a change detection task to evaluate cognitive ability. Results show the worst overall immediate pre-post learning gains in the Mastery Drop condition compared to the Mastery Add and No Add/Drop conditions which showed similar learning gains. This pattern went away when looking at delayed pre-post learning gains. Cognitive ability did not have any impact on learning performance, suggesting that similar strategies work equally well across all levels of cognitive ability. These results suggest adaptively adding cards is better than dropping them, though if there are no time constraints, leaving all concepts in the deck leads to the best overall learning in the short term.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Golding, J.M., Wasarhaley, N.E., Fletcher, B.: The use of flashcards in an introduction to psychology class. Teach. Psychol. 39, 199–202 (2012). https://doi.org/10.1177/0098628312450436
Hartwig, M.K., Dunlosky, J.: Study strategies of college students: are self-testing and scheduling related to achievement? Psychon. Bull. Rev. 19, 126–134 (2012). https://doi.org/10.3758/s13423-011-0181-y
Karpicke, J.D., Butler, A.C., Roediger, H.L.: Metacognitive strategies in student learning: do students practise retrieval when they study on their own? Memory 17, 471–479 (2009). https://doi.org/10.1080/09658210802647009
Kornell, N., Bjork, R.A.: The promise and perils of self-regulated study. Psychon. Bull. Rev. 14, 219–224 (2007). https://doi.org/10.3758/bf03194055
Whitmer, D.E., Johnson, C.I., Marraffino, M.D., Pharmer, R.L., Blalock, L.D.: A Mastery Approach to Flashcard-Based Adaptive Training. In: Sottilare, R.A., Schwarz, J. (eds.) HCII 2020. LNCS, vol. 12214, pp. 555–568. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50788-6_41
Bjork, R.A., Dunlosky, J., Kornell, N.: Self-regulated learning: beliefs, techniques, and illusions. Annu. Rev. Psychol. 64, 417–444 (2013). https://doi.org/10.1146/annurev-psych-113011-143823
Kornell, N., Bjork, R.A.: Learning concepts and categories: is spacing the “enemy of induction”? Psychol. Sci. 19, 585–592 (2008). https://doi.org/10.1111/j.1467-9280.2008.02127.x
Senzaki, S., Hackathorn, J., Appleby, D.C., Gurung, R.A.R.: Reinventing flashcards to increase student learning. Psychol. Learn. Teach. 16, 353–368 (2017). https://doi.org/10.1177/1475725717719771
Karpicke, J.D.: Metacognitive control and strategy selection: deciding to practice retrieval during learning. J. Exp. Psychol. Gen. 138, 469–486 (2009)
Miyatsu, T., Nguyen, K., McDaniel, M.A.: Five popular study strategies: their pitfalls and optimal implementations. Perspect. Psychol. Sci. 13, 390–407 (2018). https://doi.org/10.1177/1745691617710510
Cepeda, N.J., Pashler, H., Vul, E., Wixted, J.T., Rohrer, D.: Distributed practice in verbal recall tasks: a review and quantitative synthesis. Psychol. Bull. 132, 354–380 (2006). https://doi.org/10.1037/0033-2909.132.3.354
Roediger, H.L., Karpicke, J.D.: The power of testing memory: basic research and implications for educational practice. Perspect. Psychol. Sci. 1, 181–210 (2006). https://doi.org/10.1111/j.1745-6916.2006.00012.x
Cepeda, N.J., Coburn, N., Rohrer, D., Wixted, J.T., Mozer, M.C., Pashler, H.: Optimizing distributed practice: theoretical analysis and practical implications. Exp. Psychol. 56, 236–246 (2009). https://doi.org/10.1027/1618-3169.56.4.236
Janiszewski, C., Noel, H., Sawyer, A.G.: A meta-analysis of the spacing effect in verbal learning: implications for research on advertising repetition and consumer memory. J. Consum. Res. 30, 138–149 (2003). https://doi.org/10.1086/374692
Johnson, C.I., Mayer, R.E.: A testing effect with multimedia learning. J. Educ. Psychol. 101, 621–629 (2009). https://doi.org/10.1037/a0015183
Karpicke, J.D., Roediger, H.L.: Repeated retrieval during learning is the key to long-term retention. J. Mem. Lang. 57, 151–162 (2007). https://doi.org/10.1016/j.jml.2006.09.004
Rowland, C.A.: The effect of testing versus study on retention: a meta-analytic review of the testing effect. Psychol. Bull. 140, 1432–1463 (2014). https://doi.org/10.1037/a0037559
Roediger, H.L., Karpicke, J.D.: Test-enhanced learning: taking memory tests improves long-term retention. Psychol. Sci. 17, 249–255 (2006). https://doi.org/10.1111/j.1467-9280.2006.01693.x
Kornell, N.: Optimising learning using flashcards: spacing is more effective than cramming. Appl. Cog. Psychol. 23, 1297–1317 (2009). https://doi.org/10.1002/acp.1537
Kornell, N., Bjork, R.A.: Optimising self-regulated study: the benefits—and costs—of dropping flashcards. Memory 16, 125–136 (2008). https://doi.org/10.1080/09658210701763899
Wissman, K.T., Rawson, K.A., Pyc, M.A.: How and when do students use flashcards? Memory 20, 568–579 (2012). https://doi.org/10.1080/09658211.2012.687052
Pyc, M.A., Rawson, K.A., Aschenbrenner, A.J.: Metacognitive monitoring during criterion learning: when and why are judgments accurate? Mem. Cognit. 42(6), 886–897 (2014). https://doi.org/10.3758/s13421-014-0403-4
Pyc, M.A., Rawson, K.A.: Examining the efficiency of schedules of distributed retrieval practice. Mem. Cogn. 35, 1917–1927 (2007). https://doi.org/10.3758/bf03192925
Pyc, M.A., Rawson, K.A.: Testing the retrieval effort hypothesis: does greater difficulty correctly recalling information lead to higher levels of memory? J. Mem. Lang. 60, 437–447 (2009). https://doi.org/10.1016/j.jml.2009.01.004
Pyc, M.A., Rawson, K.A.: Costs and benefits of dropout schedules of test–restudy practice: implications for student learning. Appl. Cog. Psychol. 25, 87–95 (2011). https://doi.org/10.1002/acp.1646
Van Merriënboer, J.J.G., Kester, L., Paas, F.: Teaching complex rather than simple tasks: balancing intrinsic and germane load to enhance transfer of learning. Appl. Cog. Psychol. 20, 343–352 (2006). https://doi.org/10.1002/acp.1250
Sweller, J.: Cognitive load theory, learning difficulty and instructional design. Learn. Instr. 4, 295–312 (1994). https://doi.org/10.1016/0959-4752(94)90003-5
Sweller, J.: Element interactivity and intrinsic, extraneous and germane cognitive load. Educ. Psychol. Rev. 22, 123–138 (2010). https://doi.org/10.1007/s10648-010-9128-5
Yan, V.X., Bjork, E.L., Bjork, R.A.: On the difficulty of mending metacognitive illusions: a priori theories, fluency effects, and misattributions of the interleaving benefit. J. Exp. Psychol. Gen. 145, 918–933 (2016). https://doi.org/10.1037/xge0000177
Durlach, P.J., Ray, J.M.: Designing Adaptive Instructional Environments: Insights from Empirical Evidence. Technical Report, U.S. Army Research Institute for the Behavioral and Social Sciences (2011)
Landsberg, C.R., Astwood, R.S., Jr., Van Buskirk, W.L., Townsend, L.N., Steinhauser, N.B., Mercado, A.D.: Review of adaptive training system techniques. Mil. Psychol. 24, 96–113 (2012). https://doi.org/10.1080/08995605.2012.672903
Mettler, E., Burke, T., Massey, C.M., Kellman, P.J.: Comparing adaptive and random spacing schedules during learning to mastery criteria. In: Proceedings of the 42nd Annual Conference of the Cognitive Science Society, pp. 773–779. Cognitive Sciences Society, Virtual (2020)
Mettler, E., Kellman, P.J.: Adaptive response-time-based category sequencing in perceptual learning. Vision. Res. 99, 111–123 (2014). https://doi.org/10.1016/j.visres.2013.12.009
Bjork, E.L., Bjork, R.A.: Making things hard on yourself, but in a good way: creating desirable difficulties to enhance learning. In: Gernsbacher, M.A., Pew, R.W., Hough, L.M., Pomerantz, J.R. (eds.) Psychology And the Real World: Essays Illustrating Fundamental Contributions to Society, pp. 56–64. Worth Publishers, New York (2011)
Bjork, R.A.: Memory and metamemory considerations in the training of human beings. In: Metcalfe, J., Shimamura, A. (eds.) Metacognition: Knowing About Knowing, pp. 185–205. MIT Press, Cambridge (1994)
Baddeley, A.D., Hitch, G.: Working memory. In: Psychology of Learning and Motivation, vol. 8, pp. 47–89. Academic Press (1974)
Conway, A.R.A., Kane, M.J., Bunting, M.F., Hambrick, D.Z., Wilhelm, O., Engle, R.W.: Working memory span tasks: a methodological review and user’s guide. Psychon. Bull. Rev. 12, 769–786 (2005). https://doi.org/10.3758/bf03196772
Engle, R.W.: Working memory capacity as executive attention. Curr. Dir. Psychol. Sci. 11, 19–23 (2002). https://doi.org/10.1111/1467-8721.00160
Engle, R.W.: Working memory and executive attention: a revisit. Perspect. Psychol. Sci. 13, 190–193 (2018). https://doi.org/10.1177/1745691617720478
Kane, M., Hambrick, Z., Tuholski, S., Wilhelm, O., Payne, T., Engle, R.: The generality of working memory capacity: a latent-variable approach to verbal and visuospatial memory span and reasoning. J. Exp. Psychol. Gen. 133, 189–217 (2004). https://doi.org/10.1037/0096-3445.133.2.189
Engle, R.W., Laughlin, J.E., Tuholski, S.W., Conway, A.R.A.: Working memory, short-term memory, and general fluid intelligence: a latent-variable approach. J. Exp. Psychol. Gen. 128, 309–331 (1999)
Kane, M.J., Bleckley, M.K., Conway, A.R., Engle, R.W.: A controlled-attention view of working-memory capacity. J. Exp. Psychol. Gen. 130, 169–183 (2001)
Klein, K., Boals, A.: The relationship of life event stress and working memory capacity. Appl. Cognit. Psychol. 15, 565–579 (2001). https://doi.org/10.1002/acp.727
Agarwal, P.K., Finley, J.R., Rose, N.S., Roediger, H.L.: Benefits from retrieval practice are greater for students with lower working memory capacity. Memory 25, 764–771 (2017). https://doi.org/10.1080/09658211.2016.1220579
Wang, J., Liu, Z., Xing, Q., Seger, C.A.: The benefit of interleaved presentation in category learning is independent of working memory. Memory 28, 285–292 (2020). https://doi.org/10.1080/09658211.2019.1705490
Cowan, N.: The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav. Brain Sci. 24, 87–114 (2001). https://doi.org/10.1017/S0140525X01003922
Luck, S.J., Vogel, E.K.: Visual working memory capacity: from psychophysics and neurobiology to individual differences. Trends Cogn. Sci. 17, 391–400 (2013). https://doi.org/10.1016/j.tics.2013.06.006
Rouder, J.N., Morey, R.D., Morey, C.C., Cowan, N.: How to measure working memory capacity in the change detection paradigm. Psychon. Bull. Rev. 18(2), 324–330 (2011). https://doi.org/10.3758/s13423-011-0055-3
Hollingworth, A., Richard, A.M., Luck, S.L.: Understanding the function of visual short-term memory: transsaccadic memory, object correspondence, and gaze correction. J. Exp. Psychol. Gen. 137, 163–181 (2008). https://doi.org/10.1037/0096-3445.137.1.163
Hollingworth, A., Matsukura, M., Luck, S.J.: Visual working memory modulates rapid eye movements to simple onset targets. Psychol. Sci. 24, 790–796 (2013). https://doi.org/10.1177/0956797612459767
Alloway, T.P., Alloway, R.G.: Investigating the predictive roles of working memory and IQ in academic attainment. J. Exp. Child Psychol. 106, 20–29 (2010). https://doi.org/10.1016/j.jecp.2009.11.003
Fukuda, K., Vogel, E., Mayr, U., Awh, E.: Quantity, not quality: the relationship between fluid intelligence and working memory capacity. Psychon. Bull. Rev. 17(5), 673–679 (2010). https://doi.org/10.3758/17.5.673
Redick, T.S., et al.: Measuring working memory capacity with automated complex span tasks. Eur. J. Psychol. Assess. 28, 164–171 (2012). https://doi.org/10.1027/1015-5759/a000123
Inquisit 6 Automated Symmetry Span Task (ASSPAN) [computer software]. https://www.millisecond.com (2020)
Luck, S.J., Vogel, E.K.: The capacity of visual working memory for features and conjunctions. Nature 390, 279–281 (1997). https://doi.org/10.1038/36846
Inquisit 6: https://www.millisecond.com (2021)
Inquisit 6: Solving Anagrams. https://www.millisecond.com (2019)
Acknowledgments
Many thanks to Sean Chancellor, Morgan Kelley, and Crystal Meyer for their assistance with data collection and to Sadan Yagci for his assistance with programming.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Blalock, L.D. (2022). Adaptively Adding Cards to a Flashcard Deck Improves Learning Compared to Adaptively Dropping Cards Regardless of Cognitive Ability. In: Sottilare, R.A., Schwarz, J. (eds) Adaptive Instructional Systems. HCII 2022. Lecture Notes in Computer Science, vol 13332. Springer, Cham. https://doi.org/10.1007/978-3-031-05887-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-05887-5_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-05886-8
Online ISBN: 978-3-031-05887-5
eBook Packages: Computer ScienceComputer Science (R0)