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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Suggested Citation:"DISCUSSION." National Research Council. 1988. Enhancing Human Performance: Background Papers, Learning During Sleep. Washington, DC: The National Academies Press. doi: 10.17226/780.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please DISCUSSION 35 DISCUSSION Whether it is possible and practical for people to learn while they sleep is a question to which Western and Eastern researchers have given different answers. Little, if any, learning has been revealed in most Western studies, wherein novel verbal material is presented to unselected subjects during a single session of EEG-defined sleep. Whatever learning that has materialized in these studies has frequently been found to be correlated with both the duration and level of EEG wakefulness patterns that coincide with or closely follow presentation of the learning material. In contrast, evidence of substantial sleep learning has emerged in numerous Eastern studies, wherein familiar material is presented to “suggestible” subjects who have a strong presleep set to learn, and who are willing to participate in a lengthy training regimen. No attempt is made in these studies to input information during deep stages of sleep; instead, presentations are timed to correspond with sleep onset, initial sleep, and early morning sleep--periods in which significant EEG activations are likely to occur. Any improvements in performance obtained under these conditions would thus appear to reflect a compostite of wake and sleep experience, and not pure, unadulterated “sleep learning.” While it appears clear that information whose presentation, during sleep, is not accompanied by EEG activation is not retained unpon awakening, it would be most interesting to know, for theoretical as well as for applied reasons, use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please DISCUSSION 36 whether there is any substance to to Soviet claim that substantial improvements in learning can be achieved by way of a systematic program of combined wake/sleep instruction. It would also be informative to discover whether such improvements are dependent upon the learners’ age, their health, their capacity to acquire knowledge in the waking state, their susceptibility to hypnosis, and their motivation or set to learn; on the nature of the learning materials (e.g., whether they are affectively intoned or personally insignificant) and the methods of material presentation (e.g., air- v. bone-conducted transmission); and on the means by which memory for the material is measured (e.g., whether the test of retention administered does or does not require awareness of remembering). These are among the many issues that remain to be settled in future research aimed at investigating both the possibility and the practicality of learning during sleep. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 37 REFERENCES Aarons, L. 1976 Sleep-assisted instruction. Psychological Bulletin 83: 1-40. Adams, J. A. 1980 Learning and Memory : An Introduction . Homewood IL: Dorsey Press. Arkin, A. M., and Antrobus, J. S. 1978 The effects of external stimuli applied prior to and during sleep on sleep experiences. Pp. 351-391 in A. M. Arkin, J. S. Antrobus, and S. J. Ellman, eds., The Mind in Sleep : Psychology and Psychophysiology . Hillsdale NJ: Erlbaum. Baddeley, A. D. 1976 The Psychology of Memory . New York: Basic Books. Balkhasov, I. 1968 The rapid teaching of a foreign language by lessons heard during sleep. Pp. 160-163 in F. Rubin, ed., Current Research in Hypnopaedia . New York: American Elsevier. (Originally published in 1965.) Bartlett, J. C., and Santrock, J. W. 1979 Affect-dependent episodic memory in young children. Child Development 50: 513-518. Bartlett, J. C., Burleson, G., and Santrock, J. W. 1982 Emotional mood and memory in young children. Journal of Experimental Child Psychology 34: 59-76. Belicki, K., and Bowers, P. 1982 The role of demand characteristics and hypnotic ability in dream change following a presleep instruction. Journal of Abnormal Psychology 91: 426-432. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 38 Bliznitchemko, L. 1968 Hypnopaedia and its practice in the USSR. Pp. 202-209 in F. Rubin, ed., Current Research in Hypnopaedia . New York: American Elsevier. Breger, L., Hunter, I., and Lane, R. W. 1971 The Effect of Stress on Dreams . New York: International Universities Press. Bruce, D. J., Evans, C. R., Fenwick, P. B. C., and Spencer, V. 1970 Effects of presenting novel verbal material during slow-wave sleep. Nature 225: 873-874. Dement, W. C., and Kleitman, N. 1957 The relation of eye movements during sleep to dream activity: An objective method for the study of dreaming. Journal of Experimental Psychology 53: 339-346. Eich, E. 1977 State-dependent retrieval of information in human episodic memory. Pp. 141-157 in I. M. Birnbaum and E. S. Parker, eds., Alcohol and human memory . Hillsdale NJ: Erlbaum. 1980 The cue-dependent nature of state-dependent retrieval. Memory & Cognition 8: 157-173. 1984 Memory for unattended events: Remembering with and without awareness. Memory & Cognition 12: 105-111. 1985 Context, memory, and integrated item/context imagery. Journal of Experimental Psychology : Learning , Memory , and Cognition 11: 764-770. 1986 Epilepsy and state specific memory. Acta Neurologica Scandinavica 74: 15-21. Elliott, C. R. 1968 Extracts from an experimental study of the retention of auditory material presented during sleep. Pp. 6-27 in F. Rubin, ed., Current Research in Hypnopaedia . New York: American Elsevier. (Unpublished MA thesis dated 1947.) use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 39 Emmons, W. H., and Simon, C. W. 1956 The non-recall of material presented during sleep. American Journal of Psychology 69: 76-81. Evans, F. J. 1972 Hypnosis and sleep: Techniques for exploring cognitive activity during sleep. Pp. 43-83 in E. Fromm and R. E. Shor, eds., Hypnosis : Research Developments and Perspectives . Chicago: Aldine/Atherton. Evans, F. J., Gustafson, L. A., O’Connell, D. N., Orne, M. T., and Shor, R. E. 1966 Response during sleep with intervening amnesia. Science 152: 666-667, 1969 Sleep-induced behavioral response: Relationship to susceptibility to hypnosis and laboratory sleep patterns. Journal of Nervous and Mental Disease 148: 467-476. 1970 Verbally induced behavioral responses during sleep. Journal of Nervous and Mental Disease 150: 171-187. Firth, H. 1973 Habituation during sleep. Psychophysiology 10: 43-51. Foulkes, D. 1966 The Psychology of Sleep . New York: Scribers and Sons. Fox, B. H., and Robbins, J. S. 1952 The retention of material presented during sleep. Journal of Experimental Psychology 43: 75-79. Freud, S. 1953 The Interpretation of Dreams. Vols. 4-5 in J. Strachey, ed., The Standard Edition of the Complete Psychological Works of Sigmund Freud . London: Hogarth Press. (Originally published in 1900.) use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 40 Goodenough, D. R. 1978 Dream recall: History and current status of the field. Pp. 113-140 in A. M. Arkin, J. S. Antrobus, and S. J. Ellman, eds., The Mind in Sleep : Psychology and Psychophysiology . Hillsdale NJ: Erlbaum. Goodwin, D. W., Powell, B., Bremer, D., Hoine, H., and Stern, J. 1969 Alcohol and recall: State dependent effects in man. Science 163: 1358-1360. Hallahan, D. P., Kauffman, J. M., and Ball, D. W. 1974 Developmental treands in recall of central and incidental auditory material. Journal of Experimental Child Psychology 17: 409-421. Hebb, D. O. 1949 The Organization of Behavior : A Neuropsychological Theory . New York: Wiley. Hilgard, E. R. 1979 Divided consciousness in hypnosis: The implications of the hidden observer. In E. Fromm and R. Shor, eds., Hypnosis : Developments in Research and New Perspectives . New York: Aldine. Hoskovec, J. 1966 Hypnopaedia in the Soviet Union: A critical review of recent major experiments. International Journal of Clinical and Experimental Hypnosis 14: 308-315. Hutt, S. J., Hutt, C., Lenard, H. G., Bernuth, H., and Muntjewerff, W. J. 1968 Auditory responsivity in the human neonate. Nature 218: 888-890. Itil, T. M., Menon, G. N., Bozak, M., and Sangor, A. 1982 The effects of oxiracetam (ISF 2522) in patients with organic brain syndrome. Drug Development Research 2: 447-461. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 41 Jacobson, A., Kales, A., Lehmann, D., and Zweizig, J. 1965 Somnambulism: All night electroencephalographic studies. Science 148: 975-977. Jacoby, L. L. 1982 Knowing and remembering: Some parallels in the behavior of Korsakoff patients and controls. In L. S. Cermak, ed., Memory and Amnesia . Hillsdale NJ: Erlbaum. Jacoby, L. L., and Dallas, M. 1981 On the relationship between autobiographical memory and perceptual learning. Journal of Experimental Psychology : General 110: 306-340. Jacoby, L. L., and Witherspoon, D. 1982 Remembering with and without awareness. Canadian Journal of Psychology 36: 300-324. Johns, M. W., Gay, T. J. A., Goodyear, M. D. E., and Masterton, J. P. 1971 Sleep habits of health young adults: Use of sleep questionnaire. British Journal of Preventitive and Social Medicine 25: 236-241. Johnson, M. K., Kahan, T. L., and Raye, C. L. 1984 Dreams and reality monitoring. Journal of Experimental Psychology : General 113: 329-344. Jus, K., and Jus, A. 1972 Experimental studies on memory disturbances in pathological and physiological conditions. International Journal of Psychobiology 2: 205-208. Kintsch, W. 1970 Models of free recall and recognition. Pp. 331-373 in D. A. Norman, ed., Models of Human Memory . New York: Academic Press. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 42 Koukkou, M., and Lehmann, D. 1968 EEG and memory storage in sleep experiments with humans. Electroencephalography and Clinical Neurophysiology 25: 455-462. 1983 Dreaming: The functional state-shift hypothesis. British Journal of Psychiatry 142: 221-231. Koulack, D., and Goodenough, D. R. 1976 Dream recall and dream recall failure: An arousal-retrieval model. Psychological Bulletin 83: 975-984. Kulikov, V. N. 1968 The question of hypnopaedia. Pp. 132-144 in F. Rubin, ed., Current Research in Hypnopaedia . New York: International Universities Press. (Originally published in 1964.) Lehmann, D., and Koukkou, M. 1974 Computer analysis of EEG wakefulness-sleep patterns during learning of novel and familiar sentences. Electroencephalography and Clinical Neurophysiology 37: 73-84. Leuba, C., and Bateman, D. 1952 Learning during sleep. American Journal of Psychology 65: 301-302. Levy, C. M., Collidge, F. L., and Stabb, L. V. 1972 Paired associate learning during EEG-defined sleep: A preliminary study. Australian Journal of Psychology 24: 219-225. Minard, J., Loiselle, R., Ingledue, E., and Duatlich, D. 1968 Discriminative electro-oculogram deflections (EGDs) and heart rate (HR) pauses elicited during maintained sleep by stimulus significance. Psychophysiology 5: 232. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 43 Moscovitch, M. 1982 Multiple dissociations of function in amnesia. In L. S. Cermak, ed., Memory and Amnesia . Hillsdale NJ: Erlbaum. Okuma, T., Nakamura, K., Hayashi, A., & Fujimori, M. 1966 Psycho-physiological study on the depth of sleep in normal human subjects. Electroencephalography and Clinical Neurophysiology 21: 140-147. Oltman, P. K., Goodenough, D. R., Koulack, D., Maclin, E., Schroeder, H. R., and Flanagan, M. J. 1977 Short-term memory during Stage-2 sleep. Psychophysiology 14: 439-444. Oswald, I., Taylor, A. M., and Treisman, M. 1960 Discriminative responses to stimulation during human sleep. Brain 83: 440-453. Overton, D. A. 1973 State dependent retention of learned responses produced by drugs. In W. P. Koella and P. Levin, eds., Sleep . Basel: Karger. 1982 Memory retrieval failures produced by changes in drug state. Pp. 113-139 in R. L. Isaacson & N. E. Spear, eds., The Expression of Knowledge . New York: Plenum Press. Peters, R., and McGee, R. 1982 Cigarette smoking and state-dependent memory. Psychopharmacology 76: 232-235. Prince, M. 1910 The mechanism and interpretation of dreams. Journal of Abnormal Psychology 19: 137-195. Rubin, F. 1968 Current Research in Hypnopaedia . New York: American Elsevier. 1970 Learning and sleep. Nature 226: 477. 1971 Learning and Sleep . Bristol: John Wright and Sons. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please REFERENCES 44 Schacter, D. L., and Tulving, E. 1982 Memory, amnesia, and the episodic/semantic distinction. In R. L. Isaacson and N. E. Spear, eds., The Expression of Knowledge . New York: Plenum Press. Sheldrake, P., and Cormack, M. 1974 Dream recall and the menstrual cycle. Journal of Psychosomatic Research 18: 347-350. Simon, C. W., and Emmons, W. H. 1955 Learning during sleep? Psychological Bulletin 52: 328-342. 1956 Responses to material presented during various levels of sleep. Journal of Experimental Psychology 51: 89-97. Svyadoshch, A. M. 1968 The assimilation and memorisation of speech during natural sleep. Pp. 91-117 in F. Rubin, ed., Current Research in Hypnopaedia . New York: American Elsevier. >(Originally published in 1962.) Tilley, A. J. 1979 Sleep learning during Stage 2 and REM sleep. Biological Psychology 9: 155-161. Tulving, E., Schacter, D. L., and Stark, H. A. 1982 Priming effects in word-fragment completion are independent of recognition memory. Journal of Experimental Psychology : Learning , Memory , and Cognition 8: 336-342. Watkins, M. J. 1979 Engrams as cuegrams and forgetting as cue overload: A cueing approach to the structure of memory. In C. R. Puff, ed., Memory Organization and Structure . New York: Academic Press. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. REFERENCES ed., Current Research in Hypnopaedia . New York: American Elsevier. (Originally published in 1965.) ed., Current Research in Hypnopaedia . New York: American Elsevier. (Originally published in 1964.) Zukhar’, V. P., Kaplan, Y. Y., Maksimov, Y. A., and Pushkina, I. P. 1968 A collective experiment on hypnopaedia. Pp. 152-159 in F. Rubin, 45 Zavalova, N. D., Zukhar’, V. P., and Petrov, Y. A. 1968 The question of hypnopaedia (preliminary communication). Pp. 145-151 in F. Rubin,

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. REFERENCES 46

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. ACCELERATED LEARNING Robert E. Slavin Accelerated Learning Johns Hopkins University 47

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. ACCELERATED LEARNING 48

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 49 Over the past fifteen years there have been extraordinary gains made in our understanding of the elements that constitute effective instruction. One important source of information has been research on teaching, which has studied the behaviors characteristic of teachers whose students make outstanding learning gains (see, for example, Brophy & Good, 1986; Rosenshine & Stevens, 1986). Another has been fundamental advances in psychology of learning (e.g., Anderson, Spiro, & Montagne, 1977). A third source of new information and perspectives has been experimental research on such instructional methods as mastery learning (Bloom, 1976), cooperative learning (Slavin, 1983a, b), computer-assisted instruction (Kulik, Bangert, & Williams, 1983), and Suggestive Accelerative Learning Techniques (Schuster & Gritton, 1985). This paper represents an effort to summarize the current status of research on effective instruction. It presents a model of effective instruction, discusses research on each of the elements of this model, and uses the model to discuss research on specific instructional techniques. The research discussed was almost all conducted in elementary and secondary schools, but the implications of the review for military training are examined at the end of the paper. Elements of Effective Instruction In recent years, research on teaching has made significant strides in identifying teaching behaviors associated with high student achievement (Brophy & Good, 1986; Rosenshine & Stevens, 1986). For example, research on the presentation of lessons has examined such issues as type and level of questionning (e.g., Winne, 1979; Redfield & Rousseau, 1981), lesson organi use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 50 zation (e.g., Belgard, Rosenshine, & Gage, 1971), and transitions between ideas (e.g., Smith & Cotton, 1980). However, effective instruction is not just good teaching. If it were, we could probably find the best lecturers, make video tapes of their lessons, and show them to students. Consider why the video teacher would be ineffective. First, the video teacher would have no idea what students already knew. A particular lesson might be too advanced for a particular group of students, or it may be that some students already know the material being taught. Some students may be learning the lesson quite well, while others are missing key concepts and falling behind because they lack prerequisite skills for new learning. The video teacher would have no way to know who needed additional help, and would have no way to provide it in any case. There would be no way to question students to find out if they were getting the main points and then to reteach any concepts students were failing to grasp. Second, the video teacher would have no way to motivate students to pay attention to the lesson or to really try to learn it. If students were failing to pay attention, the video teacher would have no way to do anything about it. Finally, the video teacher would never know at the end of the lesson whether or not students actually learned the main concepts or skills. The case of the video teacher illustrates the point that teachers must be concerned with many elements of instruction in addition to the lesson itself. Teachers must attend to ways of adapting instruction to students’ levels of knowledge, motivating students to learn, managing student behavior, grouping students for instruction, and testing and evaluating students. These are elements of classroom organization that are at least as important use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 51 as the quality of teachers’ lessons. A Model of School Learning One of the most influential articles ever published in the field of educational psychology was a paper by John Carroll entitled “A Model of School Learning” (1963). In it, Carroll describes teaching in terms of the management of time, resources, and activities to ensure student learning. The model proposes five elements that contribute to the effectiveness of instruction: Aptitude, ability to understand instruction, perseverance, opportunity (time), and quality of instruction. Carroll discusses these elements in terms of time needed to learn and time available for learning . The higher are students’ aptitudes, the better their abilities to understand instruction, and the greater their perseverance, the less time it will take to teach them a skill or concept. The higher the quality of instruction, the less time will be needed. On the other side of the balance sheet is opportunity; there must be adequate time to teach a lesson. Carroll’s model mixes two kinds of elements: Those that are directly under the control of the teacher, and those that are characteristics of students, which are difficult to change in the short run. Quality of instruction and opportunity (time) are directly under the control of the teacher or the school. Aptitude is mostly a characteristic of students over which teachers can have little control in the short run. Ability to understand instruction and perseverance are partly under the control of the teacher, but partly characteristic of students. For example, ability to understand instruction is partly a product of student ability, but is also a product of what teachers do to make sure that students have all the prerequisite skills and information they will need to successfully learn a new lesson. Persev use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 52 erance results both from the motivation to learn that a student brings to school and from specific strategies a teacher or school might use to motivate students to do their best. I have proposed elsewhere (Slavin, 1984; in press) a model of effective instruction which focuses on the alterable elements of Carroll’s model, those which teachers and schools can directly change. The components of this model of alterable elements of effective instruction are as follows: 1. Quality of Instruction. The degree to which information or skills are presented so that students can easily learn them. Quality of instruction is largely a product of the quality of the curriculum and of the lesson presentation itself. 2. Appropriate Levels of Instruction : The degree to which the teacher makes sure that students are ready to learn a new lesson (that is, they have the necessary skills and knowledge to learn it) but have not already learned the lesson. In other words, the level of instruction is appropriate when a lesson is neither too difficult nor too easy for students. 3. Incentive: The degree to which the teacher makes sure that students are motivated to work on instructional tasks and to learn the material being presented. 4. Time: The degree to which students are given enough time to learn the material being taught. The four elements of this QAIT (Quality, Appropriateness, Incentive, Time) model have one important characteristic: All four must be adequate for instruction to be effective. Again, effective instruction is not just good teaching. No matter how high the quality of instruction, students will use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 53 not learn a lesson if they lack the necessary prior skills or information, if they lack the motivation, or if they lack the time they need to learn the lesson. On the other hand, if the quality of instruction is low, then it makes no difference how much students know, how motivated they are, or how much time they have. Each of the elements of the QAIT model is like a link in a chain, and the chain is only as strong as its weakest link. Toward a Theory of Effective Classroom Organization Most of the advances in recent research on teaching have come about as a result of correlational process- product research, in which the practices of instructionally effective teachers have been contrasted with those of less effective teachers, controlling for student inputs. In recent years, the findings of these process-product studies have been incorporated into coherent instructional programs and evaluated in field experiments. Other coherent instructional methods not based on the process-product findings, such as mastery learning, cooperative learning, and individualized instruction methods, have al so been evaluated in field experiments. Each of these instructional methods is based on its own psychological or educational theories. However, it is the purpose of this paper to propose a theory to encompass all potential forms of classroom organization. Given a relatively fixed set of resources, every innovation in classroom organization solves some problems but also creates new problems which must themselves be solved. Tradeoffs are always involved. Understanding the terms of these tradeoffs is critical for an understanding of how to build effective models of classroom organization. The QAIT model proposed above is designed primarily to clarify the tradeoffs involved in alternative forms of classroom organization. This paper use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 54 presents a perspective on what is known now about each of the QAIT elements, explores the theoretical and practical ramifications of the interdependence of these elements for the design of effective instructional methods, and applies the QAIT formulation to a discussion of effective models for classroom instruction. Quality of Instruction Quality of instruction refers to the activities we think of first when we think of teaching: Lecturing, discussing, calling on students, and so on. When instruction is high in quality, the information being presented makes sense to students, is interesting to them, is easy to remember and apply. The most important aspect of instructional quality is the degree to which the lesson makes sense to students. For example, teachers must present information in an organized, orderly way (Belgard, Rosenshine, & Gage, 1971), note transitions to new topics (Smith & Cotton, 1980), use many vivid images and examples (Anderson & Hidde, 1971), and frequently restate essential principles (Maddox & Hoole, 1975). Lessons should be related to students’ background knowledge, using such devices as advance organizers (Ausubel, 1960) or simply reminding students of previously learned material at relevant points in the lesson. Enthusiasm (Abrami, Leventhal, & Perry, 1982) and humor (Kaplan & Pascoe, 1977) can also contribute to quality of instruction. Clear specification of lesson objectives to students (Dalis, 1970) and a substantial correlation between what is taught and what is assessed (Cooley & Leinhardt, 1980) contribute to instructional quality, as does frequent use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 55 formal or informal assessment to see that students are mastering what is being taught (Dunkin & Biddle, 1974: Peckham & Roe, 1977) and immediate feedback to students on the correctness of their performances (Barringer & Gholson, 1979). Instructional pace is partly an issue of quality of instruction and partly of appropriate levels of instruction. In general, content coverage is strongly related to student achievement (Dunkin, 1978; Barr & Dreeben, 1983), so a rapid pace of instruction may contribute to instructional quality. However, there is obviously such a thing as too rapid an instructional pace. Frequent assessment of student learning is critical for teachers to establish the most rapid instructional pace consistent with the preparedness and learning rate of all students. Appropriate Levels of Instruction Perhaps the most difficult problem of school and classroom organization is accommodating instruction to the needs of students with different levels of prior knowledge and different learning rates. If a teacher presents a lesson on equations in two variables to a heterogeneous class, some students may fail to learn it because they have not mastered such prerequisite skills as solving equations in one variable. At the same time, there may be some students who know how to solve two-variable equations before the lesson begins, or learn to do so very rapidly. If the teacher sets a pace of instruction appropriate to the needs of the students lacking prerequisite skills, then the rapid learners’ time will be largely wasted. If the instructional pace is too rapid, the students lacking prerequisite skills will be left behind. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 56 There are many common means of attempting to accomodate instruction to students’ diverse needs, but each method has drawbacks that may make the method counterproductive. Various forms of ability grouping seek to reduce the heterogeneity of instructional groups. Between-class ability grouping plans, such as tracking, can create low-ability classes for which teachers have low expectations, maintain a slow pace of instruction, and dislike to teach (Good & Marshall, 1984; Rowan & Miracle, 1983; Slavin, 1986a). However, forms of ability grouping in which students are regrouped across grade lines and instructional level is based on performance level rather than age can be instructionally effective (Slavin, 1986a). Mastery learning and individualized instruction are two widely used means of accommodating instruction to students’ needs. These are discussed later in this paper. Incentive Thomas Edison once wrote that “genius is one percent inspiration and ninety-nine percent perspiration.” The same could probably be said for learning. Learning is work. This is not to say that learning must be drudgery, but it is certainly the case that students must exert themselves to pay attention, to study, and to conscientiously perform the tasks assigned to them, and they must somehow be motivated to do these things. This motivation may come from the intrinsic interest value of the material being learned, or may be created through the use of extrinsic incentives, such as praise, grades, special privileges, and so on. If students want to know something, they will be more likely to exert the necessary effort to learn it. This is why there are students who can rattle use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 57 off the names, batting averages, and other statistics relating to every player on the Chicago Cubs, but do not know their multiplication facts. Teachers can create intrinsic interest in material to be taught by arousing student curiosity, for example by using surprising demonstrations, by relating topics to students’ personal lives, or by allowing students to discover information for themselves (Gregory, 1975; Berlyne, 1965). However, not every subject can be made intrinsically interesting to every student at all times. Most students need some sort of extrinsic incentive to exert an adequate level of effort. For example, studies of graded versus pass-fail college courses find substantially higher achievement in classes that give grades (Gold, Reilly, Silberman, & Lehr, 1971; Hales, Bain, & Rand, 1971). One critical principle of effective use of classroom incentives is that students should be held accountable for everything they do. For example, homework that is checked has been found to contribute more to student achievement than homework that is assigned but not checked (Austin, 1978). Also, questioning strategies that communicate high expectations for students, such as waiting for them to respond (Rowe, 1974) and following up with students who do not initially give full responses (Brophy & Evertson, 1974) have been found to be associated with high achievement. Several methods of providing formal incentives for learning have been found to be instructionally effective. Among these are strategies based on behavioral learning theories which provide praise, tokens, or other rewards contingent on students’ classroom behavior (O’Leary & O’Leary, 1972). One practical and effective method of rewarding students for appropriate, learning-oriented behavior is home-based reinforcement (Barth, 1979), provision of daily or weekly reports to parents on student behavior. Another is group use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 58 contingencies (Litow & Pumroy, 1975; Hayes, 1976), in which the entire class or groups within the class are rewarded on the basis of the behavior of the entire group. Cooperative learning methods (Slavin, 1983a, b), which involve students working in small learning groups to master academic material, are instructionally effective forms of group contingencies discussed later in this paper. Rewarding students based on improvement over their own past performance has also been found to be an effective incentive system (Natriello, in press; Slavin, 1980). In addition to being a product of specific strategies designed to increase student motivation, incentive is also influenced by quality of instruction and appropriate levels of instruction. Students will be more motivated to learn about a topic that is presented in an interesting way, that makes sense to them, and that they feel capable of learning. Further, students’ motivations to exert maximum effort will be influenced by their perception of the difference between their probability of success if they do exert themselves and their probability of success if they do not (Atkinson & Birch, 1978; Slavin, 1977, 1986b). That is, if a student feels sure of success or, alternatively, of failure, regardless of his or her efforts, then incentive will be very low. This is likely to be the case if a lesson is presented at a level much too easy or too difficult for the student, respectively. Incentive is high when the level of instruction is appropriate for a student. If the student perceives that with effort the material can be mastered, the payoff for effort will be perceived to be great. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 59 Time Instruction takes time. More time spent teaching a subject does not always translate into additional learning, but if instructional quality, appropriateness of instruction, and incentives for learning are all high, then more time on instruction is likely to pay off in greater learning. The amount of time available for learning depends largely on two factors: Allocated time and engaged time . Allocated time is the time scheduled by the teacher for a particular lesson or subject and then actually used for instructional activities. Allocated time is mostly under the direct control of the school and teacher. In contrast, engaged time, the time students actually engage in learning tasks, is not under the direct control of the school or teacher. Engaged time, or time-on-task, is largely a product of quality of instruction, student motivation, and allocated time. Thus, allocated time is an alterable element of instruction (like quality, appropriateness, and incentive), but engaged time is a mediating variable linking alterable variables with student achievement. While allocated time must be an essential element in any model of classroom organization, research on this variable has found few consistent effects on student achievement. For example, research on hours in the school day and days in the school year has found few relationships between these time variables and student achievement (Frederick & Walberg, 1980; Karweit, 1976, 1981). The Beginning Teacher Evaluation Study found no effect of allocated time in specific subjects on student achievement in those subjects when time was measured at the class level (Marliave, Fisher, & Dishaw, 1978). On the other hand, research on engaged time generally finds positive relationships between of time students are on task and their use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 60 achievement, but even with this variable results are inconsistent (see Karweit, 1981). Studies of means of increasing student time on task generally go under the heading of classroom management research. Process-product studies (see, for example, Brophy, 1979) have established that teachers’ use of effective management strategies is associated with high student achievement. Research on classroom management methods based on behavioral learning theory has established that such methods as token economies, group contingencies, and home-based reinforcement can increase student time-on-task and (in many cases) thereby increase student achievement (O’Leary & O’Leary, 1972). A Model of Alterable Elements of Instruction and Student Achievement As noted earlier, Carroll’s (1963) model of school learning discusses five elements in terms of their effects on time needed to learn and time available to learning. The QAIT model, whose elements were described in the previous sections, can also be conceptualized in terms of intermediate effects on time-related variables. Figure 1 depicts a model of how alterable elements of instruction might affect student achievement. Figure 1 Here In Figure 1, two types of independent variables are presented: Student inputs and alterable variables. Student inputs refer to factors over which the school has little control in the short run: Student ability and those aspects of motivation to learn that students bring from home (as distinct use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 61 from the motivation created by classroom practices). The alterable variables are the QAIT elements discussed earlier. Of course, student inputs are not immutable, but can be affected by classroom practices. For example, student aptitude to learn a specific lesson may be strongly influenced by background knowledge resulting from earlier instruction, by specific training in thinking, problem solving, or study skills, or by general intellectual stimulation or learning skills provided by the school. Student motivation to learn is also largely a product of past experiences in school. However, in the context of any given lesson, the student inputs can be considered fixed, while the alterable variables can be directly manipulated by the school or teacher. The effects of the alterable variables on student achievement are held to be mediated by two time-related variables: Instructional efficiency and engaged time , or time-on-task. Instructional efficiency can be conceptualized as the amount of learning per unit time. For example, students will learn more in a ten-minute lesson high in instructional efficiency than in a lesson of similar length low in instructional efficiency. Engaged time is the amount of time students are actually participating in relevant learning activities, such as paying attention to lectures and doing assignments. Instructional efficiency is simply the inverse of Carroll’s “time needed to learn,” and engaged time is essentially his “time available for learning.” Instructional efficiency and engaged time are multiplicatively related to student achievement; obviously, if either is zero, then learning is zero. The QAIT model can be easily related to instructional efficiency and engaged time. Instructional efficiency is a product of the quality of instruction (e.g., organization and presentation quality of the lesson), use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 62 appropriate levels of instruction (students have prerequisite skills but have not already learned the lesson), and incentive (students are interested in learning the lesson). These factors are multiplicative related to instructional efficiency, meaning that if any of them is zero, instructional efficiency and therefore achievement will also be zero. Of course, aptitude and motivation also contribute to instructional efficiency for any given student. Engaged time is primarily a product of allocated time and incentive. The contention that the relationships between the alterable variables, instructional efficiency and engaged time, and student achievement are multiplicative is of critical importance to the model proposed here. In addition to implying that achievement will be zero if any of the alterable variables are zero, it also implies that while improving any one of the variables is likely to increase achievement arithmetically, improving more than one is likely to increase achievement geometrically. Since there are many random or uncontrolled factors in student achievement, and since achievement in any particular skill is so much a function of prior knowledge, ability, and motivation, it may be that for any new program to have a measurable effect on student mean achievement, it must improve multiple elements of instruction and therefore have a geometric effect on learning, particularly when a measure of general learning (such as a standardized test) is used as a criterion of success for a program implemented over a substantial period of time. For example, consider how much additional vocabulary students in an experimental program would have to learn to show a measurably greater gain than control students on a standardized reading vocabulary test not specifically keyed to the material students studied. The chance elements involved in determining whether words or decoding skills taught in the use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 63 experimental program actually appeared on the vocabulary test would make it unlikely that any small effect of improved instruction would be detected. EFFECTIVE INSTRUCTIONAL MODELS The value of any theory or model lies in its usefulness in explaining or clarifying phenomena of interest. The remainder of this paper uses the concepts of the QAIT formulation to discuss research on several innovations directed at accelerating student achievement, and ends with a discussion of the application of these methods and of the QAIT model itself to military training. Individualized Instruction. Individualized or programmed instructional methods were developed primarily to solve the problem of differences in student prior knowledge and learning rate by allowing students to work on materials at their own levels and rates. In theory, individualized instruction should bring about a substantial improvement in the provision of appropriate levels of instruction. Yet reviews of research on the achievement effects of the individualzed models developed in the 1960’s and ‘70’s have uniformly concluded that these methods had few if any positive effects on student achievement (Hartley, 1977; Horak, 1981; Miller, 1976; Schoen, in press). The individualized methods were based on sound psychological theories and the materials were carefully constructed and piloted. What went wrong? One possibility is that what individualized instruction gained in appropriate levels of instruction it then lost in quality of instruction, incentive, and time. One serious problem of individualized instruction is that use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 64 it forces students to rely on printed material for the great majority of their instruction. If a teacher had enough aides to check student work, manage the flow of materials, and respond to non-instructional demands, and was extraordinarily well organized, the teacher could still spend only two minutes with each of twenty-five students in a fifty-minute period. In fact, many teachers using individualized programs spend most of their class time checking student work and managing materials, not teaching at all except when students have specific problems. The quality of instruction provided by the best written material is unlikely to match that provided by a teacher. Further, the incentive value of doing the same types of worksheets day after day with little interaction with other students or with the teacher cannot be very great for many students. Finally, the necessity for a substantial amount of time for procedural activities, such as waiting for materials to be checked, reduces time available for learning, and any lack of of incentive to make rapid progress may further reduce engaged time. An individualized mathematics program designed to solve these problems of the 1960’s models provides an interesting point of contrast. This is Team Assisted Individualization, or TAI (Slavin, 1985), an individualized mathematics program for the upper elementary grades. In TAI, students work in four-member heterogeneous learning teams. Students work within their teams on programmed materials appropriate to their own level of preparedness, check one another’s work against answer sheets, help one another with problems, and take care of all management concerns. The teams are rewarded based on the progress of each team member thorough the individualized sequence of units. Since the students themselves take responsibility for all checking and routine management, the teacher is free to spend all period teaching groups of students drawn from the different teams who are perform use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 65 ing at about the same level; students typically receive 10-20 minutes of direct instruction every class period. The team incentive, found in previous research to be a powerful motivator (Slavin, 1983a,b), provides ample motivation for students to proceed at a rapid rate with high accuracy and to help one another to master difficult concepts. This incentive may produce high levels of engagement, perhaps enough to counterbalance the time needed to engage in checking or management-related activities. Research on TAI has clearly established that when direct instruction and team incentives are added to an individualized program, achievement is accelerated. In six field experiments evaluating the program, the mean grade equivalent gain in computations on standardized tests was twice as great for TAI classes as that for control groups (Slavin, Leavey, & Madden, 1984; Slavin, Madden, & Leavey, 1984; Slavin & Karweit, 1985; Slavin, 1985). A component analysis of TAI by Cavanaugh (1984) found that the team incentive system was important to the success of the program. The contrast of the results of TAI to those of earlier individual models suggests that individualization is not inherently ineffective, but can be made effective if in addition to providing appropriate levels of instruction it also provides adequate direct instruction (quality of instruction) and enhanced incentives for learning. Attention to all four elements of effective instruction turned out in this case to be necessary to produce a positive effect on student achievement. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 66 Computer Assisted Instruction Computer Assisted Instruction, or CAI, refers to a wide range of means of using computers to help students learn, from drill-and-practice programs to tutorials to simulations and games. CAI offers a means of providing students with one-to-one, individualized instruction that, while very expensive, is much less expensive than providing live tutors. Also, there are many kinds of instruction (such as realistic simulations) that can only be provided by computers. The effectiveness of CAI for enhancing student achievement depends on many factors. One is the type of learning objective. For objectives that lend themselves to simulation, computers are uniquely appropriate. An example of such an objective is flight training, where computerized flight simulators have been standard for decades. Another example of this sort of application is “in-box” exercises, where the student is learning to perform a job in which he or she must deal with incoming information in real time. Obviously, learning computer programming requires a computer. For more traditional school learning, the benefits of CAI are less clear. Leaving aside simulations and computer programming, there are two major types of CAI used for instructional purposes. Drill-and-practice programs are by far the most common in elementary and secondary schools. These programs present students with problems, and the students type in their answers. The computer then indicates whether the answers were correct and often keeps track of the number of errors made. Tutorial programs vary their presentations of material according to student responses. For example, in many tutorial programs the computer will provide additional instruction or explanation before giving aditional problems of the same type, or use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 67 will move the student rapidly if he or she is responding correctly. Research on instructional uses of CAI indicates consistently positive effects only when CAI is used in addition to regular classroom instruction (Atkinson, 1984; Kulik, Bangert, & Williams, 1983; Chambers & Sprecher, 1983; Clark & Leonard, 1985). However, it is not clear whether it is the computer that is producing additional learning or if it is the additional time in itself. However, some studies (e.g., Ragosta, 1983) have found strong effects of CAI when it is used only ten to fifteen minutes per day (in addition to regular instruction). When CAI is used instead of regular classroom instruction, its effects on student achievement are much smaller and more inconsistent; in fact, when time, objectives, and instructors are all held constant, there is some question of whether there is any effect of CAI at all (Clark & Leonard, 1985). It is interesting to note that despite the theoretical advantages of tutorial over drill-and-practice instruction, few differences have been found between them in their achievement effects (Kulik, Bangert, & Williams, 1983). The problems of CAI are similar to those of programmed instruction, which it strongly resembles. CAI can substantially solve the problem of providing appropriate levels of instruction, but it may do so at a cost in instructional quality, as few computer programs can compare with the instruction provided by a talented teacher. CAI may increase motivation over the short run, but this wears off; studies showing the strongest positive effects of CAI have generally been quite brief, two weeks or shorter (Clark & Leonard, 1985). In terms of the QAIT model, CAI produces positive effects principally when the gains it provides in appropriate levels of instruction are use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 68 accompanied by a gain in instructional time. Mastery Learning Mastery learning is one of the most widely used of all instructional innovations. The basic idea behind mastery learning is the principle that differences in student performance are due to differences in the time students need to learn. Mastery learning theorists (e.g., Bloom, 1976) hold that the normal distribution of scores students exhibit on any performance test arise from the practice of holding instructional time constant for all students and allowing learning to vary. They suggest that instead, learning should be held constant and time allowed to vary. To accomplish this, students in mastery learning are given clear objectives, such as achievement of a score of 90% on a test of the content studied. Students may require two or more attempts to pass this test. Those who fail to pass the test on the first try receive corrective instruction designed to remediate any learning problems. It is in this corrective instruction that time is varied for students; at least in theory, students receive as much corrective instruction as they need to master the test at the designated criterion. Mastery learning is used in two primary forms. In group-based mastery learning (Block & Anderson, 1975), also called Learning for Mastery or LFM, students are taught in class groups. The teacher presents a one- to-four week lesson and then gives a formative test. Students who achieve a pre-established criterion (usually 80-90% correct) are given enrichment work or may serve as tutors to others. Students who fail to achieve the criterion receive corrective instruction from the teacher. This cycle may be repeated until nearly all students have achieved the criterion score. When mastery use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 69 learning is used at the elementary or secondary levels, it is almost always one or another form of a group-based model. In contrast, the second primary form of mastery learning, the Keller Plan (Keller, 1968) or Personalized System of Instruction (PSI), is used almost exclusively at the post-secondary level. In PSI, a set of tests are prepared to cover the content of a course and students may take as long as they need to pass them. Students may attend lectures, work with student tutors, or use self-instructional materials, but the responsibility to master the tests is essentially theirs. Both forms of mastery learning deal primarily with providing appropriate levels of instruction. They approach the problem of student heterogeneity not by accommodating instruction to student performance levels (as in individualized instruction) but rather by varying instructional time to equalize student performance levels. In this way, students can learn from group instruction because they have all mastered the prerequisites, regardless of how long it took them to do so. Mastery learning theorists would also hold that incentive is also increased, particularly for low achievers who perceive a chance to succeed if they exert themselves. Outcomes of group-based mastery learning in elementary and secondary schools have been mixed, but appear to depend on how these programs are organized (Slavin, forthcoming). The most common form of group- based mastery learning, which follows the teach-formative test-corrective instruction/enrichment-summative test cycle described above, has not generally been found to be superior to traditionally taught control groups in achievement of objectives taught equally in both treatments. For example, year-long experiments by Anderson, Scott, & Hutlock (1975), Kersh (1972), and Slavin & use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 70 Karweit (1984) found no significant advantage on standardized tests for mastery learning programs. However, in some studies instructional time was increased by providing corrective instruction outside of class. This increased total time for low achievers, who in some cases received as much corrective instruction as initial instruction (doubling their total instructional time), and avoided the problem of shunting high achievers aside to do enrichment activities. Studies of this type have found consistent achievement advantages for mastery learning as compared to traditional programs (e.g., Arlin & Webster, 1983; Dillashaw & Okey, 1983; Swanson & Denton, 1977; Wentling, 1973). The research on group-based mastery learning may support the prediction of the QAIT model that attending only to appropriate levels of instruction is not enough to significantly increase student achievement, but when a second element is also increased (in this case time), achievement is increased. However, it may be that the increase in instructional time, not the mastery learning program, is what accounts for the positive effects in the extra-time studies. Obviously, students who receive twice as much instruction will learn more than other students. A critical assumption of mastery learning theory is that because students always have prerequisite skills for what they are to learn, the need for corrective instruction will diminish over time. However, long-term research (e.g., Arlin, 1984) questions this assumption. Research on PSI (Keller Plan) is more consistently supportive of this approach (Kulik, Kulik, & Cohen, 1979). In general, students in PSI calsses achieve at a higher level than those in traditional classes. PSI students spend somewhat more time on their coursework than do other students, but use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 71 probably not enough to account for the effects. However, PSI students perceive their courses as significantly harder and more time-consuming than do traditionally taught students, and perhaps for that reason withdrawal rates for PSI courses are higher than for other courses. One problem in all mastery learning research is that by its nature mastery learning (whether group-based or PSI) focuses students and teachers on a narrowly defined set of objectives. When performance on those objectives is assessed, it is hardly surprising that mastery learning students achieve them better than other students. Even when mastery learning and control teachers agree on a common set of objectives and a common examination, it is likely that the mastery learning teachers will focus on those objectives more directly than will control teachers, who are much more likely to teach additional material that will not be on the test. In practice, this means that when there is a very specific set of objectives to be mastered and all students must master them, mastery learning approaches are particularly appropriate, but may be less appropriate when objectives are less concrete and variations in outcomes are acceptable. For example, mastery learning might be more appropriate in teaching the periodic table of the elements or automobile mechanics, which have limited, easily specified objectives, than in teaching the history of World War II or principles of evolution. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 72 Peer Tutoring Long ago, educators realized that students could help one another learn. For example, the Lancastrian System of the nineteenth century solved the problem of a shortage of teachers for children of the poor by having older students teach younger, less advanced students. Peer tutoring usually involves older student tutoring younger ones (called “cross-age tutoring). One reason for this is that students often resent being tutored by a classmate. Research on cross-age tutoring has found consistent positive effects on the achievement of the student receiving tutoring (the “tutee”), and equally strong effects in many cases on the achievement of the tutor, who apparently learns a great deal from the tutoring experience (Devin-Sheehan, Feldman, & Allen, 1976; Cloward, 1967). Schools sometimes take advantage of this latter finding by using as tutors older students who are having difficulties with basic skills themselves. By having them tutor younger students, they must review the basic skills they failed to master earlier in a setting that gives them high status. Effects of peer tutoring are particularly strong when tutors are trained in highly structured “programmed tutoring” methods (Ellson, 1976) which give tutors step-by-step procedures to follow in instructing and praising their tutees. As in the case of CAI and mastery learning, effects of peer tutoring are particularly strong when tutoring is done in addition to, not instead of, regular classroom instruction. However, peer tutoring does still appear to be quite effective when instructional time is held constant. Peer tutoring is often used as part of other methods. For example, it is a routine component of the Personalized System of Instruction (PSI), or use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 73 Keller Plan, and is often used to provide corrective instruction in group-based mastery learning. Informal peer tutoring is central to cooperative learning, discussed in the following section. In terms of the QAIT model, peer tutoring works because it impacts on three (and usually four) of the QAIT elements. It solves the problem of providing appropriate levels of instruction by totally individualizing instruction for each tutee. It increases incentive because students receive the undivided attention of a high-status individual whom they usually want to please, because their learning efforts are closely monitored, and because they receive frequent, immediate feedback on their work. Quality of instruction is increased, particularly when tutors are trained in programmed tutoring models, but also because the tutor can easily adjust the pace and content of instruction to the tutee’s needs and the tutee can ask questions when he or she does not understand. Finally, when tutoring is done in addition to regular classroom instruction, allocated time for instruction is increased. Even when this is not the case, time-on-task is likely to be higher in tutoring than in whole-class instruction. Cooperative Learning Cooperative learning refers to instructional methods in which students work in small, heterogeneous learning groups. It differs from peer tutoring in several ways. First, students in cooperative learning are generally all of the same age, and are learning the material together. There are high, average, and low achievers in each group, but the high achievers are not formally designated as tutors for the low achievers. Instruction in cooperative learning initially comes from the teacher. The learning group’s task use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 74 is usually to master what the teacher has initially presented. There are many forms of cooperative learning, but they can be grouped in two major categories. In group study methods, all students are working together to learn the same content. In task specialization methods, each group member is responsible for a different part of the group’s task. Research on group study methods indicates that this form of cooperative learning can be highly effective if two conditions are satisfied. First, the groups must be working toward a valued group goal, such as a group reward. Second, success in achieving this goal must depend only on the individual learning of every member of the group (Slavin, 1983 a, b). For example, in Student Teams-Achievement Divisions or STAD, students are assigned to four-member, heterogeneous teams. The teacher presents a lesson, and then students study worksheets relating to the lesson, attempting to ensure that all team members have mastered the concepts. Finally, the students are individually quizzed, and teams are rewarded with certificates or other recognition or rewards if their average scores exceed a pre-established criterion. In this way, the only way for teams to succeed is to make certain that their members have learned. Of thirty-five methodologically adequate studies of group study methods which (like STAD) used group rewards based on group members’ individual learning, twenty- eight found significantly higher achievement for cooperative than for control treatments (Slavin, 1986c). In contrast, evaluations of group study methods which did not use group rewards or based group rewards on the quality of a single team product have not been more successful than traditional methods (Slavin, 1983 a, b). One study done in a military training setting made exactly this comparison. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 75 Hagman and Hayes (1985) conducted two experiments on teaching U.S. Army Equipment Records and Parts Specialists supply-related tasks as part of their Advanced Individual Training. In both experiments they found that trainees who worked in four-member groups and were rewarded (with free time) based on their group’s average quiz scores performed significantly better than did trainees who received free time based on their individual scores only, regardless of whether or not they studied in groups. That is, in this as in many elementary and secondary school studies, simply working in groups was not enough; the group had to be rewarded based on the individual learning of its members. Achievement effects of cooperative learning models using task specialization are less clear cut. Consistent positive effects in social studies have been found for one complex model of this kind, called Group Investigation (Sharan, Hertz-Lazarowitz, & Ackerman, 1980), but other methods, using task specialization such as Jigsaw Teaching (Aronson et al., 1978) have been less successful. Cooperative learning impacts primarily on incentive to learn. By rewarding groups on the basis of their members’ learning, students encourage their groupmates to exert maximum learning efforts. This incentive system also motivates students to engage in effective peer tutoring, translating the teacher’s instruction into learners’ language, thereby increasing quality of instruction. However, the most effective of all cooperative learning methods are Team Assisted Individualization in mathematics (Slavin, 1985) and Cooperative Integrated Reading and Composition in reading and writing (Madden, Stevens, & Slavin, 1986). In addition to the incentive provided by group rewards, these methods also impact on appropriate levels of instruc use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 76 tion, as both combine individualization (or subgrouping) with cooperative learning. Both methods have produced gains on standardized tests twice as large as those produced by traditional methods of instruction. Suggestive Accelerative Learning Techniques (SALT) Suggestive Accelerative Learning Techniques, or SALT, is an instructional model derived from the work of Georgii Lozanov (1978), a Bulgarian psychologist. This approach is based primarily on the idea that by involving students in relaxation exercises, teaching mental concentration, and presenting information in a dynamic way, their capacity for learning will dramatically increase. The method uses what is in essence a mild form of hypnotism to increase receptivity to new information, and then uses methods similar to those used in advertising to get across the instructional “message.” A SALT lesson begins with inducing relaxation, playing classical music, and then presenting material in a dramatic, forceful way. Later the material is reviewed and practiced independently or in small groups. Students may participate in a play or psychodrama to act out the new information, and quizzes are given frequently as self-assessments of learning. While there is a good deal of research on SALT, this research is of mixed quality and is difficult to evaluate. Virtually all of it is published in the Journal of Suggestive-Accelerative Learning and Teaching , and therefore has not been subjected to the rigorous peer review typical of the journals published by the American Educational Research Association or other scientific organizations. The largest number of studies of SALT by far were authored or co-authored by the editor of the Journal, Donald Schuster. Some of the studies of SALT (e.g., Peterson, 1977; Schuster, 1976) compared SALT use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 77 to control methods, where the SALT students received half of the instructional time received by control students. When the achievement results were not significantly different, the the authors claimed that this showed SALT to be twice as efficient as the control method. In fact, use of small samples and measures of unknown reliability ensure that any observed differences will be non-significant. Other SALT studies (e.g., Schuster & Ginn, 1978) fail to hold content constant, comparing gains in SALT on a test designed for the SALT teachers to gains in “similar” control classes which may have been teaching different objectives. Most SALT studies are either very brief or use very small samples, or both, and some had no control groups. With all of these reservations in mind, the sheer volume of testimonial as well as scientific (though flawed) evidence supporting the use of SALT indicates that the method is at least worthy of independent evaluation. A few studies of SALT did attend to problems of making experimental and control groups comparable and holding both to the same objectives, and did find small but statistically significant advantages for the method (Prichard, Schuster, & Gensch, 1980; Schuster & Prichard, 1978). However, even if the effects of the method are taken at face value, it is by no means clear which elements of SALT account for its effects. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 78 APPLICATIONS TO MILITARY TRAINING The theories and research presented in this paper are derived primarily from studies done in elementary and secondary schools. The settings in which military training takes place differ in many ways from typical school settings. Military trainees are not only older, but they may be more motivated to learn, as there is likely to be a direct relationship between their success in training and their success in the military. The objectives of military training are often quite different from those typical of elementary and secondary schools; for example, many military tasks require hands-on, one-to-one training rather than classroom instruction. However, much of military training does involve instruction in classroom settings, and it is to this setting that the research discussed in this paper applies most directly. The applicability of the specific methods discussed in the previous section to military training depends on the training objectives and the situation in which training takes place. For example, if a training program had clearly specified, easily measured objectives, then some form of mastery learning might be appropriate. If resources were available to provide corrective instruction outside of class to students who failed to achieve mastery on a formative test, then group-based mastery could be a very effective strategy. If trainees had considerable leeway in how they used their time outside of class, then the Personalized System of Instruction (Keller Plan) might be used. If it is appropriate to allow all trainees to take as long as necessary to master a set of information or skills, then some form of individualizized instruction might be effective. use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 79 One program that has actually been evaluated and found to be effective in military training is cooperative learning (Hagman & Hayes, 1985). Cooperative learning lends itself well to the military envirornment, which already emphasizes squad organization, cohesiveness building, and mutual interdependence. Cooperative learning has been combined with individualized instruction (Slavin, 1985) and with mastery learning (Mevarech, 1985), and the results have been more positive than for either method alone, so it may be that some form of cooperative learning could be incorporated with other instructional formats in military training. The usefulness of peer tutoring in military training would depend once again on practical considerations. If more experienced or higher-ranking individuals are available to provide one-to-one instruction to trainees, this can be very effective. In particular, peer tutoring may be effectively used as corrective instruction in mastery learning programs. The applicability of SALT to military training is uncertain. One study (Peterson, 1977) did evaluate SALT in Navy ROTC naval science classes and found results that were somewhat supportive of the method. However, the author notes that “many (students) would make fun of the (SALT) exercise before the lesson and distract those who were trying to concentrate. Some of the students thought the method was a hoax and generally were the troublemakers” (page 6). It is unclear that military trainees would take deep breathing and Baroque music seriously, although it would be worth experimenting with. Beyond the particular methods, the principles outlined in this paper do apply just as well to military as to other instructional settings. Military training must emphasize well-organized, cognitively sensible instruction, it use the print version of this publication as the authoritative version for attribution.

About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be retained, and some typographic errors may have been accidentally inserted. Please ACCELERATED LEARNING 80 must take into account students’ levels of prior knowledge and skills, it must provide incentives for learning, and it must provide adequate learning time. There is no magic in instruction. Producing effective, transportable instructional models is a matter of analyzing instructional objectives and mobilizing training resources to provide high levels of instructional quality, appropriate levels of instruction, strong incentives to learn, and adequate time for learning. These are the raw materials of effective instruction, and instructional design to meet any particular objective and setting is a question of engineering available resources to provide them. use the print version of this publication as the authoritative version for attribution.

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Enhancing Human Performance: Background Papers, Learning During Sleep Get This Book
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Is it possible for people to register and retain what is said in their presence while they sleep? If it is possible, is the learning that takes place during sleep efficient enough to be of practical as well as theoretical significance? These are the questions of chief concern in this paper. To address these issues, the second section of the paper summarizes research dealing with a number of variables that may have an important influence on sleep learning. In the third section, some tentative conclusions concerning the possibility and practicality of learning during sleep are outlined.

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