Memory & Cognition

, Volume 42, Issue 8, pp 1211–1224 | Cite as

Deconstructing the effect of self-directed study on episodic memory

  • Douglas Markant
  • Sarah DuBrow
  • Lila Davachi
  • Todd M. Gureckis
Article

Abstract

Self-directed learning is often associated with better long-term memory retention; however, the mechanisms that underlie this advantage remain poorly understood. This series of experiments was designed to “deconstruct” the notion of self-directed learning, in order to better identify the factors most responsible for these improvements to memory. In particular, we isolated the memory advantage that comes from controlling the content of study episodes from the advantage that comes from controlling the timing of those episodes. Across four experiments, self-directed learning significantly enhanced recognition memory, relative to passive observation. However, the advantage for self-directed learning was found to be present even under extremely minimal conditions of volitional control (simply pressing a button when a participant was ready to advance to the next item). Our results suggest that improvements to memory following self-directed encoding may be related to the ability to coordinate stimulus presentation with the learner’s current preparatory or attentional state, and they highlight the need to consider the range of cognitive control processes involved in and influenced by self-directed study.

Keywords

Memory Metacognition Self-directed learning Self-regulated learning Volitional control Decision making Metamemory Object recognition Spatial cognition 

References

  1. Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417–444. doi:10.1146/annurev-psych-113011-143823 PubMedCrossRefGoogle Scholar
  2. Botvinick, M. M. (2008). Hierarchical models of behavior and prefrontal function. Trends in Cognitive Sciences, 12, 201–208. doi:10.1016/j.tics.2008.02.009 PubMedCrossRefPubMedCentralGoogle Scholar
  3. Carrasco, M. (2011). Visual attention: The past 25 years. Vision Research, 51, 1484–1525. doi:10.1016/j.visres.2011.04.012 PubMedCrossRefPubMedCentralGoogle Scholar
  4. Chrastil, E. R., & Warren, W. H. (2012). Active and passive contributions to spatial learning. Psychonomic Bulletin & Review, 19, 1–23. doi:10.3758/s13423-011-0182-x CrossRefGoogle Scholar
  5. Chun, M. M., & Turk-Browne, N. B. (2007). Interactions between attention and memory. Current Opinion in Neurobiology, 17, 177–184. doi:10.1016/j.conb.2007.03.005 PubMedCrossRefGoogle Scholar
  6. Craddock, M., Martinovic, J., & Lawson, R. (2011). An advantage for active versus passive aperture-viewing in visual object recognition. Perception, 40, 1154–1163. doi:10.1068/p6974 PubMedCrossRefGoogle Scholar
  7. Dempster, F. N. (1988). The spacing effect: A case study in the failure to apply the results of psychological research. American Psychologist, 43, 627–634. doi:10.1037/0003-066X.43.8.627 CrossRefGoogle Scholar
  8. Doeller, C., Barry, C., & Burgess, N. (2010). Evidence for grid cells in a human memory network. Nature, 463, 657–661. doi:10.1038/nature08704 PubMedCrossRefPubMedCentralGoogle Scholar
  9. Doeller, C., & Burgess, N. (2008). Distinct error-correcting and incidental learning of location relative to landmarks and boundaries. Proceedings of the National Academy of Sciences, 105, 5909–5914. doi:10.1073/pnas.0711433105 CrossRefGoogle Scholar
  10. Ellen, P., Parko, E., Wages, C., Doherty, D., & Herrmann, T. (1982). Spatial problems solving by rats: Exploration and cognitive maps. Learning and Motivation, 13, 81–94. doi:10.1016/0023-969090030-3 CrossRefGoogle Scholar
  11. Gruber, M., & Otten, L. (2010). Voluntary control over prestimulus activity related to encoding. Journal of Neuroscience, 30, 9793–9800. doi:10.1523/JNEUROSCI.0915-10.2010 PubMedCrossRefPubMedCentralGoogle Scholar
  12. Guderian, S., Schott, B., Richardson-Klavehn, A., & Düzel, E. (2009). Medial temporal theta state before an event predicts episodic encoding success in humans. Proceedings of the National Academy of Sciences, 106, 5365. doi:10.1073/pnas.0900289106 CrossRefGoogle Scholar
  13. Gureckis, T. M., & Markant, D. B. (2012). Self-directed learning: A cognitive and computational perspective. Perspectives on Psychological Science, 7, 464–481. doi:10.1177/1745691612454304 CrossRefGoogle Scholar
  14. Harman, K. L., Humphrey, G. K., & Goodale, M. A. (1999). Active manual control of object views facilitates visual recognition. Current Biology, 9, 1315–1318. doi:10.1016/S0960-9822(00)80053-6 PubMedCrossRefGoogle Scholar
  15. Kornell, N., & Bjork, R. A. (2007). The promise and perils of self-regulated study. Psychonomic Bulletin & Review, 14, 219–224. doi:10.3758/BF03194055 CrossRefGoogle Scholar
  16. Kornell, N., & Metcalfe, J. (2006). Study efficacy and the region of proximal learning framework. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 609–622. doi:10.1037/0278-7393.32.3.609 PubMedGoogle Scholar
  17. Liu, C. H., Ward, J., & Markall, H. (2007). The role of active exploration of 3D face stimuli on recognition memory of facial information. Journal of Experimental Psychology: Human Perception and Performance, 33, 895. doi:10.1037/0096-1523.33.4.895 PubMedGoogle Scholar
  18. Luursema, J. M., & Verwey, W. B. (2011). The contribution of dynamic exploration to virtual anatomical learning. Advances in Human–Computer Interaction, 2011, 1–6. doi:10.1155/2011/965342 CrossRefGoogle Scholar
  19. Markant, D., & Gureckis, T. M. (2014). Is it better to select or to receive? Learning via active and passive hypothesis testing. Journal of Experimental Psychology: General, 143, 94–122. doi:10.1037/a0032108 CrossRefGoogle Scholar
  20. Meijer, F., & Van der Lubbe, R. H. (2011). Active exploration improves perceptual sensitivity for virtual 3D objects in visual memory. Vision Research, 51, 2431–2439. doi:10.1016/j.visres.2011.09.013 PubMedCrossRefGoogle Scholar
  21. Metcalfe, J. (2002). Is study time allocated selectively to a region of proximal learning? Journal of Experimental Psychology: General, 131, 349–363. doi:10.1037/0096-3445.131.3.349 CrossRefGoogle Scholar
  22. Metcalfe, J. (2009). Metacognitive judgments and control of study. Current Directions in Psychological Science, 18, 159–163. doi:10.1111/j.1467-8721.2009.01628.x PubMedCrossRefPubMedCentralGoogle Scholar
  23. Metcalfe, J., & Finn, B. (2008). Evidence that judgments of learning are causally related to study choice. Psychonomic Bulletin & Review, 15, 174–179. doi:10.3758/PBR.15.1.174 CrossRefGoogle Scholar
  24. Metcalfe, J., & Kornell, N. (2003). The dynamics of learning and allocation of study time to a region of proximal learning. Journal of Experimental Psychology: General, 132, 530–542. doi:10.1037/0096-3445.132.4.530 CrossRefGoogle Scholar
  25. Nelson, T. O., & Narens, L. (1994). Why investigate metacognition? In J. Metcalfe & A. P. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 1–25). Cambridge: MIT Press.Google Scholar
  26. O’Keefe, J., & Nadel, L. (1978). The hippocampus as a cognitive map. Oxford: Oxford University Press.Google Scholar
  27. Otten, L. J., Quayle, A. H., Akram, S., Ditewig, T. A., & Rugg, M. D. (2006). Brain activity before an event predicts later recollection. Nature Neuroscience, 9, 489–491. doi:10.1038/nn1663 PubMedCrossRefGoogle Scholar
  28. Plancher, G., Barra, J., Orriols, E., & Piolino, P. (2013). The influence of action on episodic memory: A virtual reality study. Quarterly Journal of Experimental Psychology, 66, 895–909. doi:10.1080/17470218.2012.722657 CrossRefGoogle Scholar
  29. Posner, M. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3–25. doi:10.1080/00335558008248231 PubMedCrossRefGoogle Scholar
  30. Renner, M. (1990). Neglected aspects of exploratory and investigatory behavior. Psychobiology, 18, 16–22. doi:10.3758/BF03327209 Google Scholar
  31. Save, E., Buhot, M., Foreman, N., & Thinus-Blanc, C. (1992). Exploratory activity and response to a spatial change in rats with hippocampal or posterior parietal cortical lesions. Behavioural Brain Research, 47, 113–127. doi:10.1016/S0166-4328(05)80118-4 PubMedCrossRefGoogle Scholar
  32. Simon, D., & Bjork, R. (2001). Metacognition in motor learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27, 907–912. doi:10.1037/0278-7393.27.4.907 PubMedGoogle Scholar
  33. Son, L. K., & Metcalfe, J. (2000). Metacognitive and control strategies in study-time allocation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 204–221. doi:10.1037/0278-7393.26.1.204 PubMedGoogle Scholar
  34. Voss, J., Galvan, A., & Gonsalves, B. (2011a). Cortical regions recruited for complex active-learning strategies and action planning exhibit rapid reactivation during memory retrieval. Neuropsychologia, 49, 3956–3966. doi:10.1016/j.neuropsychologia.2011.10.012 PubMedCrossRefPubMedCentralGoogle Scholar
  35. Voss, J., Gonsalves, B., Federmeier, K., Tranel, D., & Cohen, N. (2011b). Hippocampal brain-network coordination during volitional exploratory behavior enhances learning. Nature Neuroscience, 14, 115–120. doi:10.1038/nn.2693 PubMedCrossRefPubMedCentralGoogle Scholar
  36. Voss, J., Warren, D., Gonsalves, B., Federmeier, K., Tranel, D., & Cohen, N. (2011c). Spontaneous revisitation during visual exploration as a link among strategic behavior, learning, and the hippocampus. Proceedings of the National Academy of Sciences, 108, E402–E409. doi:10.1073/pnas.1100225108 CrossRefGoogle Scholar
  37. Yoo, J. J., Hinds, O., Ofen, N., Thompson, T. W., Whitfield-Gabrieli, S., Triantafyllou, C., & Gabrieli, J. D. E. (2011). When the brain is prepared to learn: Enhancing human learning using real-time fMRI. NeuroImage, 59, 846–852. doi:10.1016/j.neuroimage.2011.07.063 PubMedCrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2014

Authors and Affiliations

  • Douglas Markant
    • 1
  • Sarah DuBrow
    • 2
  • Lila Davachi
    • 2
    • 3
  • Todd M. Gureckis
    • 2
  1. 1.Center for Adaptive Rationality, Max Planck Institute for Human DevelopmentBerlinGermany
  2. 2.Department of PsychologyNew York UniversityNew YorkUSA
  3. 3.Center for Neural ScienceNew York UniversityNew YorkUSA

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