Notes on Memory
January 2011
Martinez, M. E. (2010). Human Memory The Basics. Phi Delta Kappan, 91(8), 62-‐65. Abstract The article discusses human memory as a component of learning, noting that, like computers, humans have short-‐term and long-‐term memory. Unlike computers, humans have emotion and agency, or will. Learning, it notes, occurs when information is transferred from short-‐term into long-‐term memory. Remembering occurs when information flows from long-‐term into short-‐ term memory. It notes that information is stored in the mind in the form of language as well as sensory images including visual, sound, taste and smell. It notes that dynamic imagery is often not stored accurately. Mental limitations of humans are discussed including limited short-‐term memory, long-‐term memory that is highly selective and subject to distortion, and the usefulness of patterns in creating meaning. Jaemyung, G. (2010). Working Memory and Reactivity Goo Working Memory and Reactivity. Language Learning, 60(4), 712-‐752. Abstract The present study explores the relationship between working memory capacity (WMC) and think-‐alouds, focusing on the issue of reactivity. Two WM span tasks (listening span and operation span) were administered to 42 English-‐speaking learners of Spanish. Learner performance on reading comprehension and written production was measured under two experimental conditions (think-‐aloud vs. non-‐think-‐aloud conditions). Results showed that think-‐alouds had negatively affected learner performance on reading comprehension, indicating the presence of reactive effects. Particularly interesting is the finding that reactive effects of think-‐alouds seem to have occurred in the course of rule learning among the high-‐ WMC learners, but not among the low-‐WMC learners. The findings suggest that individual differences in WMC should be taken into careful consideration in future research that involves think-‐aloud protocols.
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Mrazik, M., Bender, S., & Makovichuk, C. (2010). Memory functioning in post-‐secondary students with learning disabilities. Research in Higher Education Journal, 81-‐9. Abstract Working memory is a core psychological process. Deficits in working memory have been shown to be related to performance in academic tasks including literacy and mathematics. A limited-‐capacity working memory system has been shown to underlie some academic difficulties presented by children with diagnosed learning disabilities. Although similar findings have been found for adults with learning disabilities, less research has been conducted with this population. The current study examined 107 adults who were pursuing post-‐secondary schooling. The subjects were referred by career counselors who suspected them to have undiagnosed learning disabilities. Subjects underwent a cross-‐battery including assessment of intellectual, achievement, and verbal learning and memory. All subjects met the criterion for a learning disability according to the DSM-‐IV. After controlling for full-‐scale IQ, analyses revealed significant partial correlations (p<0.05) between working memory, verbal learning and memory, and reading comprehension. Results from regression analysis indicated that working memory was a significant predictor of reading comprehension. Findings provide corroborating evidence of working and auditory memory deficits in adults with learning disabilities. Eun Sook, J., & Reid, N. (2009). Working memory and attitudes. Research in Science & Technological Education, 27(2), 205-‐223. Abstract Working memory capacity has been shown to be an important factor in controlling understanding in the sciences. Attitudes related to studies in the sciences are also known to be important in relation to success in learning. It might be argued that if working memory capacity is a rate controlling feature of learning and success in understanding leads to more positive attitudes, then working memory capacity might be associated with more positive attitudes. This study explores this with 714 school students (aged 12 and 14) taking science in typical schools in South Korea. Working memory capacity was measured by the figural intersection test while attitudes were explored using a questionnaire. It was found that, in general, working memory space is correlated more significantly with students' attitudes towards studies in science than attitudes towards scientists while students who have low working memory capacity tend to express consistently more negative views about their studies. Of considerable importance is the observation that students who have high working memory capacity tend to try to understand science knowledge while students who have low working memory capacity tend more to try to memorise science knowledge.
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Andersson, U. (2008). Working memory as a predictor of written arithmetical skills in children: The importance of central executive functions. British Journal of Educational Psychology, 78(2), 181-‐203. Abstract The study was conducted in an attempt to further our understanding of how working memory contributes to written arithmetical skills in children. Aim. The aim was to pinpoint the contribution of different central executive functions and to examine the contribution of the two subcomponents of children's written arithmetical skills. Sample and method. A total of 141 third-‐ and fourth-‐graders were administered arithmetical tasks and measures of working memory, fluid IQ and reading. Regression analysis was used to examine the relationship between working memory and written arithmetical skills. Results. Three central executive measures (counting span, trail making and verbal fluency) and one phonological loop measure (Digit Span) were significant and predictors of arithmetical performance when the influence of reading, age and IQ was controlled for in the analysis. Conclusions. The present findings demonstrate that working memory, in general, and the central executive, in particular, contribute to children's arithmetical skills. It was hypothesized that monitoring and coordinating multiple processes, and accessing arithmetical knowledge from long-‐term memory, are important central executive functions during arithmetical performance. The contribution of the phonological loop and the central executive (concurrent processing and storage of numerical information) indicates that children aged 9-‐10 years primarily utilize verbal coding strategies during written arithmetical performance. Gerlich, R., Browning, L., & Westermann, L. (2010). I've Got The Music In Me: A Study Of Peak Musical Memory Age And The Implications For Future Advertising. Journal of College Teaching & Learning, 7(2), 61-‐69. Abstract Neuropsychologists have demonstrated the effect music has on the human brain, and that a peak "musical memory age" occurs around 14, when normal bodily maturation is in progress. A group of 114 college students between the ages of 19 and 25 was exposed to short clips of the top 20 songs from each of the 11 years during their youth; participants were asked to rate their liking of each song sample on a 0-‐10 scale. Data analysis showed that the peak musical memory age of these students was not as precise as prior research had shown, and that overall there was difference in degree of musical affinity between age groups in the sample. This deviation firm prior findings may have resulted from changes in how music is available today. Whereas specifically targeted music was once standard procedure in past TV advertising, these findings produce new implications for future TV advertising.
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Wen-‐Chao, C., & Whitehead, R. (2009). Understanding physics in relation to working memory. Research in Science & Technological Education, 27(2), 151-‐160. Abstract The aim of physics education is to generate understanding of physics and there is considerable anecdotal evidence that passing examinations in physics is not the same as understanding the subject. This paper describes how the areas of difficulties in understanding of physics were determined for pupils in Taiwan aged 13-‐15. Test material which placed little load on working memory was then developed for several of these areas and the pupil performance was related to measured working memory capacity. Those with higher working memory capacities were found consistently to understand the ideas of physics better. The implications are discussed. Venugopalan, J., & Gopal, A. (2010). A Unified Instructional Strategy. International Journal of Learning, 17(2), 141-‐153. Abstract Direct learning methods have been the traditional forms of learning from time immemorial. The late 60's saw the rise of inquiry based and experiential learning models which have attained some degree of success. More recently neuroscience based learning models have become prevalent. The paper attempts to arrive at a new model for instructional approach which integrates direct learning, experiential learning and cognitive neuro-‐scientific learning principles to arrive at the Unified Instructional Strategy. Due importance is given to the architecture of human memory. The semantic declarative and procedural aspects of long term memory are considered so as to more efficiently associate new learning to existing learning, thus cementing this into long term memory. The methodology involves a 5 stage approach: (i) Review of learning already present in participant memory. (ii) Introduction of new concepts linking them to known concepts (iii) Introduction of new principles and procedures and relating them to the concepts learnt. (iv) Give a wider perspective to the concepts and principles /procedures learnt (v) Expose the participants to a problem solving situation which applies the new learning. This 5 fold approach to instructional strategy will help participants grasp the subject better and enable its storage in long term memory. Chinnappan, M., & Chandler, P. (2010). Managing cognitive load in the mathematics classroom. Australian Mathematics Teacher, 66(1), 5-‐11. The article discusses the management of cognitive load in a mathematics classroom. It explores the cognitive processes that cause mathematics learning and knowledge organization as well as the three types of memory, which are sensory memory, working memory (WM) and long term memory (LTM). It details the types of cognitive loads including intrinsic load, extraneous load and germane load.
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Lusk, D. L., Evans, A. D., Jeffrey, T. R., Palmer, K. R., Wikstrom, C. S., & Doolittle, P. E. (2009). Multimedia learning and individual differences: Mediating the effects of working memory capacity with segmentation. British Journal of Educational Technology, 40(4), 636-‐651. Abstract Research in multimedia learning lacks an emphasis on individual difference variables, such as working memory capacity (WMC). The effects of WMC and the segmentation of multimedia instruction were examined by assessing the recall and application of low (n=66) and high (n=67) working memory capacity students randomly assigned to either a segmented instruction (SI) or non-‐segmented instruction (NSI) version of a multimedia tutorial on historical inquiry. WMC was found to have a significant, positive effect on participants' recall and application scores; however, the use of segmentation mediated the effects of WMC to allow learners with lower WMC to recall and apply equal to those with higher WMC. Willis, J. (2009). What Brain Research Suggests for Teaching Reading Strategies. Educational Forum, 73(4), 333-‐346. How the brain learns to read has been the subject of much neuroscience educational research. Evidence is mounting for identifiable networks of connected neurons that are particularly active during reading processes such as response to visual and auditory stimuli, relating new information to prior knowledge, long-‐term memory storage, comprehension, and memory retrieval. This article offers strategies that build on current research showing the correlation of brain structure and literacy development, providing interventions for educators.