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Peer reviewedUrbano, Richard C.; And Others – Journal of Experimental Child Psychology, 1971
Descriptors: Cognitive Processes, Handicapped Children, Memory, Mental Retardation
Peer reviewedRemington, Robert J. – Journal of Psychology, 1971
Descriptors: Cognitive Processes, Decision Making, Experiments, Reaction Time
Smith, Nathaniel C., Jr. – J Gen Psychol, 1969
Descriptors: Cognitive Processes, College Students, Difficulty Level, Perception
Peer reviewedMorrison, Frederick J. – Journal of Experimental Child Psychology, 1982
To explore possible age differences, the first experiment assessed speed and maintenance of alertness in 5-year-olds, 8-year-olds, and adults. The second study tested the hypothesis that developmental variation in processing speed observed in some studies was attributable in part to age differences in alerting processes. (MP)
Descriptors: Adults, Age Differences, Children, Cognitive Processes
Peer reviewedKirby, N. H.; And Others – American Journal of Mental Deficiency, 1982
When two nonoperative lights were added to each of the ends of a stimulus display in a four choice reaction time (RT) task, the RTs of mentally retarded and nonretarded young adults Ss were slowed to about the same extent. (Author)
Descriptors: Cognitive Processes, Mental Retardation, Postsecondary Education, Reaction Time
Peer reviewedMayer, Richard E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 1982
Equation problems elicited a strategy in which the subject attempted to isolate the X variables on one side of the equation, whereas word problems elicited a strategy in which the subject attempted to reduce the expression. These results suggest that problem format influences the type of strategy used to solve algebra problems. (Author/PN)
Descriptors: Algebra, Cognitive Processes, Deduction, Higher Education
Peer reviewedSwanson, Lee – Journal of Child Psychology and Psychiatry and Allied Disciplines, 1981
Tested whether learning disabled children start a vigilance task (1) with the same capacity or detectability as nondisabled children but decline as time on task increases; (2) at a lower level of stimulus detectability due to a reduced capacity for information processing but do not decline in attention faster than nondisabled children. (Author/DB)
Descriptors: Attention Span, Children, Cognitive Processes, Learning Disabilities
Peer reviewedDashiell, William; Killian, Paul W., Jr. – Perceptual and Motor Skills, 1981
Eighteen college students solved addition problems using the Hutchings Low Fatigue Addition Algorithm, which requires a written record of running sums, and the standard algorithm, which does not. Students using the Hutchings algorithm had significantly higher reaction times to a tone, indicating that the Hutchings method requires less cognitive…
Descriptors: Addition, Adolescents, Algorithms, Cognitive Processes
Peer reviewedKerr, Beth; And Others – Journal of Experimental Child Psychology, 1980
Two experiments were conducted to test the possibility that children are slower than adults because they are less able than adults to process the information available about subsequent events in parallel with an ongoing response. Subjects were second, third, and sixth graders and college students. (MP)
Descriptors: Age Differences, Cognitive Processes, College Students, Elementary School Students
Macht, Michael L.; O'Brien, Edward J. – Journal of Experimental Psychology: Human Learning and Memory, 1980
Results of three experiments indicated that latency of correct recognition was sensitive to the influence of a priming treatment. The magnitude of the priming effect depended on both the taxonomic frequency of the probe items, and the length of the interval between the prime and the recognition test. (Author/RD)
Descriptors: Cognitive Processes, Context Clues, Higher Education, Memory
Loftus, Geoffrey R.; Kallman, Howard J. – Journal of Experimental Psychology: Human Learning and Memory, 1979
Subjects who named details in pictures performed better on subsequent recognition tests than their counterparts. Data support a model which assumes: (1) a constant probability of encoding a detail and (2) a detail is named either if it was encoded at study or with some bias probability. (Author/CP)
Descriptors: Bias, Cognitive Processes, Higher Education, Pictorial Stimuli
Peer reviewedSentis, Keith P.; Burnstein, Eugene – Journal of Personality and Social Psychology, 1979
Investigates the structural differences in the representation of balance and imbalance information by using a technique originated by Sternberg (1966). Subjects were 38 college students. (MP)
Descriptors: Cognitive Processes, College Students, Influences, Information Retrieval
Peer reviewedMiller, Linda T.; Vernon, Philip A. – Developmental Psychology, 1997
Used computer-administered tests to measure the reaction time to nonverbal stimuli of 4- through 6-year-olds and adults. Found age-related increases in processing speed that could not be attributed to increased accuracy and error rate monitoring. Used these results to evaluate R. Kail's (1991) model of processing speed, which adequately accounted…
Descriptors: Adults, Age Differences, Cognitive Development, Cognitive Processes
Peer reviewedNeubauer, Aljoscha C. – Intelligence, 1990
The relationship between psychometric intelligence and 2 selective reaction time (RT) tasks was determined for 81 university students (27 males and 54 females). Results generally support the paradigm of W. E. Hick (1952). Some surprising findings are discussed with respect to the specific demands of selective RT tasks. (SLD)
Descriptors: Cognitive Processes, College Students, Higher Education, Intelligence
Peer reviewedRatcliff, Roger – Psychological Review, 1988
The technique for examining the time course of information processing developed by D. E. Meyer et. al. (1988) is analyzed. Research is provided, which suggests that this new method gives important qualitative support to some stochastic models and quantitative support to the continuous diffusion model of information processing. (SLD)
Descriptors: Cognitive Processes, Higher Education, Information Processing, Models


