Neurodevelopmental framework for learning

Last updated

Neurodevelopmental framework for learning, like all frameworks, is an organizing structure through which learners and learning can be understood. Intelligence theories and neuropsychology inform many of them. The framework described below is a neurodevelopmental framework for learning. The neurodevelopmental framework was developed by the All Kinds of Minds Institute in collaboration with Dr. Mel Levine and the University of North Carolina's Clinical Center for the Study of Development and Learning. It is similar to other neuropsychological frameworks, including Alexander Luria's cultural-historical psychology and psychological activity theory, but also draws from disciplines such as speech-language pathology, occupational therapy, and physical therapy. It also shares components with other frameworks, some of which are listed below. However, it does not include a general intelligence factor (abbreviated g), since the framework is used to describe learners in terms of profiles of strengths and weaknesses, as opposed to using labels, diagnoses, or broad ability levels. This framework was also developed to link with academic skills, such as reading and writing. Implications for education are discussed below as well as the connections to and compatibilities with several major educational policy issues.

Contents

This framework consists of 8 constructs, sometimes referred to as systems. [1]

Constructs

In addition to the 8 constructs, this framework includes several "cross-construct" phenomena: rate alignment (working at optimal speed), strategy use (working and thinking tactically), chunk size capacity – the amount of material that can be processed, stored or generated, and metacognition (degree of knowledge about learning and insight into one's own neurodevelopmental strengths and weaknesses). [25] [26] [27] [28] [29] [30]

Other learning frameworks

Numerous frameworks are available that describe development and help to organize observations of learning behavior. Intelligence theories date back to the 19th century and the early 20th century, such as Charles Spearman's concept of general intelligence factor, or g. Though there were exceptions (e.g., Thorndike), most theories of intelligence included g, a general index of cognitive ability. [31] [32] An intelligence theory that has drawn considerable attention is Cattell-Horn-Carroll (CHC), which is grounded in extensive factor analytic research from cognitive ability test databases, as well as studies of development and heritability. CHC is actually an amalgam of Cattell-Horn Gf-Gc theory and Carroll's three-tier model. [33] proposed a framework with the broadest level a general intelligence factor conceptually similar to Spearman's g. This general factor was divided into eight narrower abilities, each consisting of narrow factors. Cattell-Horn's model was similar on several fronts, including its hierarchical structure. In the 1990s, Carroll's model was combined with Cattell-Horn's work by Flanagan, McGrew, and Ortiz (2000). [34] CHC contains three strata: stratum III is g, stratum II consists of broad cognitive abilities, and stratum I consists of narrow cognitive abilities. The broad cognitive abilities (stratum II) include fluid reasoning (or Gf, forming and recognizing logical relationships among patterns, inferencing, and transforming novel stimuli) and comprehension-knowledge (or Gc, using language and acquired knowledge). There is on-going discussion by proponents of CHC about g's importance in the framework. The Structure of Intellect (SOI) model includes three axes (with 5-6 components per axis) that form a 3-dimensional cube; because each dimension is independent, there are 150 different potential aspects of intelligence. [35] Howard Gardner has written about several categories of intelligence, as opposed to a hierarchical model. [36] Neuropsychologists have sought to map various mental abilities onto brain structures. In so doing they have created frameworks that include factors and sub-components. Luria [37] organized brain functions into now-familiar categories, such as speech and memory. Luria's conception of attention included three units: Unit 1 (brainstem and related areas) regulates cortical activity and levels of alertness, Unit 2 (lateral and posterior regions of neocortex) analyzes and stores newly received information, and Unit 3 (frontal lobes) programs and regulates activity. [37] More recently, the PASS (Planning, Attention, Successive, and Simultaneous) model [38] yields both a global index of ability while emphasizing specific cognitive processes. For example, "successive" refers to information that is perceived, interpreted, and/or remembered in a serial order (e.g., language), whereas "simultaneous" refers to material that is perceived, interpreted, and/or remembered as a whole (e.g. visual-spatial).

Footnotes

  1. Levine, M.D. (1998). Developmental Variation and Learning Disorders, Second Edition. Cambridge, MA: Educators Publishing Service.
  2. Posner, M.I., & Rothbart, M.K. (2007). Educating the Human Brain. Washington, DC: American Psychological Association.
  3. Bishoff-Grethe, A.; Goedert, K.M.; Willingham, D.T.; Grafton, S.T. (2004). "Neural substrates of response-based sequence learning using fMRI". Journal of Cognitive Neuroscience. 16 (1): 127–138. doi:10.1162/089892904322755610. PMID   15006042. S2CID   832676.
  4. Parmentier, F.B.R.; Andres, P.; Elford, G.; Jones, D.M. (2006). "Organization of visuo-spatial serial memory: interaction of temporal order with spatial and temporal grouping". Psychological Research. 70 (3): 200–217. doi:10.1007/s00426-004-0212-7. PMID   15844005. S2CID   468986.
  5. Zorzi, M.; Priftis, K.; Meneghello, F.; Marenzi, R.; Umilt, C. (2006). "The spatial representation of numerical and non-numerical sequences: Evidence from neglect". Neuropsychologia. 44 (7): 1061–1067. doi:10.1016/j.neuropsychologia.2005.10.025. PMID   16356515. S2CID   34616356.
  6. Garderen, D. (2006). "Spatial visualization, visual imagery, and mathematical problem solving of students with varying abilities". Journal of Learning Disabilities. 39 (6): 496–506. doi:10.1177/00222194060390060201. PMID   17165617.
  7. Mammarella, I.; Cornoldi, C.; Pazzaglia, F.; Toso, C.; Grimoldi, M.; Vio, C. (2006). "Evidence for a double dissociation between spatial-simultaneous and spatial-sequential working memory in visuospatial (nonverbal) learning disabled children". Brain and Cognition. 62 (1): 58–67. doi:10.1016/j.bandc.2006.03.007. PMID   16750287. S2CID   19946786.
  8. Kozhevnikov, M.; Motes, M.; Hegarty, M. (2007). "Spatial Visualization in Physics Problem Solving". Cognitive Science. 31 (4): 549–579. doi: 10.1080/15326900701399897 . PMID   21635308.
  9. Swanson, H.; Jerman, O. (2007). "The influence of working memory on reading growth in subgroups of children with reading disabilities". Journal of Experimental Child Psychology. 96 (4): 249–283. doi:10.1016/j.jecp.2006.12.004. PMID   17437762.
  10. Kail, R.; Hall, L. K. (2001). "Distinguishing short-term memory from working memory". Memory and Cognition. 29 (1): 1–9. doi: 10.3758/BF03195735 . PMID   11277452.
  11. Imbo, I.; Vandierendonck, A. (2007). "The development of strategy use in elementary school children: Working memory and individual differences". Journal of Experimental Child Psychology. 96 (4): 284–309. doi:10.1016/j.jecp.2006.09.001. hdl: 1854/LU-373960 . PMID   17046017.
  12. Katzir, T.; Youngsuk, K.; Wolf, M.; O'Brien, B.; Kennedy, B.; Lovett, M.; Morris, R. (2006). "Reading fluency: The whole is more than the parts". Annals of Dyslexia. 56 (1): 51–82. doi:10.1007/s11881-006-0003-5. PMID   17849208. S2CID   25800842.
  13. Nagy, W.; Berninger, V.; Abbott, R. (2006). "Contributions of morphology beyond phonology to literacy outcomes of upper elementary and middle-school students". Journal of Educational Psychology. 98 (1): 134–147. doi:10.1037/0022-0663.98.1.134.
  14. Altemeier, L.; Jones, J.; Abbott, R.; Berninger, V. (2006). "Executive functions in becoming writing readers and reading writers: Note taking and report writing in third and fifth graders". Developmental Neuropsychology. 29 (1): 161–173. doi:10.1207/s15326942dn2901_8. PMID   16390292. S2CID   2317324.
  15. Williams, J.; Thomas, P.; Maruff, P.; Wilson, P. (2008). "The link between motor impairment level and motor imagery ability in children with developmental coordination disorder". Human Movement Science. 27 (2): 270–285. doi:10.1016/j.humov.2008.02.008. PMID   18384899.
  16. Bar-Haim, Y.; Bart, O. (2006). "Motor function and social participation in kindergarten children". Social Development. 15 (2): 296–310. doi:10.1111/j.1467-9507.2006.00342.x.
  17. Contreras-Vidal, J. (2006). "Development of forward models for hand localization and movement control in 6 to 10-year-old children". Human Movement Science. 25 (4–5): 634–645. doi:10.1016/j.humov.2006.07.006. PMID   17011659.
  18. Blake, R.; Shiffrar, M. (2007). "Perception of Human Motion". Annual Review of Psychology. 58 (47): 47–73. doi:10.1146/annurev.psych.57.102904.190152. PMID   16903802. S2CID   5867069.
  19. Blakemore, S.J. (2007). "Brain development during adolescence". Education Review. 20 (1): 82–90.
  20. Brewer, M.B. & Hewstone, M. (2004). Social Cognition. Malden, MA: Blackwell Publishing.
  21. Holtgraves, T.M.; Kashima, Y. (2008). "Language, meaning, and social cognition". Personality and Social Psychology Review. 12 (1): 73–94. doi:10.1177/1088868307309605. PMID   18453473. S2CID   33579992.
  22. Russ, R.; Scherr, R.; Hammer, D.; Mineska, J. (2008). "Recognizing mechanistic reasoning in student scientific inquiry: A framework for discourse analysis developed from philosophy of science". Science Studies and Science Education. 92 (3): 499–525. Bibcode:2008SciEd..92..499R. doi: 10.1002/sce.20264 .
  23. Hertzog, N. (2007). "Transporting Pedagogy: Implementing the project approach in two first grade classrooms". Journal of Advanced Academics. 18 (4): 530–564. doi:10.4219/jaa-2007-559. S2CID   145808825.
  24. Amsterlaw, J. (2006). "Children's beliefs about everyday reasoning". Child Development. 77 (2): 443–464. doi:10.1111/j.1467-8624.2006.00881.x. PMID   16611183.
  25. Benjamin, A. S.; Bird, R. D. (2006). "Metacognitive control of the spacing of study repetitions". Journal of Memory and Language. 55: 126–137. doi:10.1016/j.jml.2006.02.003.
  26. Broekkamp, H.; Van Hout-Wolter, B.H.A.M. (2007). "Students' adaptation of study strategies when preparing for classroom tests". Educational Psychology. 19 (4): 401–428. doi:10.1007/s10648-006-9025-0. S2CID   145415194.
  27. Flavell, J. (1979). "Metacognition and cognitive monitoring: A new era of cognitive-developmental inquiry". American Psychologist. 34 (1): 906–911. doi:10.1037/0003-066X.34.10.906. S2CID   8841485.
  28. Halford, G.S.; Wilson, W.H.; Phillips, S. (1998). "Processing capacity defined by relational complexity: Implications for comparative, developmental, and cognitive psychology". Behavioral and Brain Sciences. 21 (6): 803–831. doi:10.1017/S0140525X98001769. PMID   10191879.
  29. Hofer, B.K. (2004). "Epistemological understanding as a metacognitive process: Thinking aloud during online searching". Educational Psychologist . 39 (1): 43–55. doi:10.1207/s15326985ep3901_5. S2CID   9660431.
  30. Lungu, O. V.; Liu, T.; Waechter, T.; Willingham, D. T.; Ashe, J. (2007). "Strategic modulation of cognitive control". Journal of Cognitive Neuroscience. 19 (8): 1302–1315. doi:10.1162/jocn.2007.19.8.1302. PMID   17651004. S2CID   19772984.
  31. Bolles, R.C. (1993). The Story of Psychology: A Thematic History. Pacific Grove, CA: Brooks/Cole.
  32. Fancher, R.E. (1990). Pioneers of Psychology, Second Edition. New York: Norton & Company.
  33. Carroll, J. B. (1993). Human Cognitive Abilities: A Survey of Factor Analytic Studies. New York: Cambridge University.
  34. Flanagan, D.P., McGrew, K.S., & Ortiz, S. (2000). The Wechsler Intelligence Scales and Gf- Gc Theory: A contemporary approach to interpretation. Needham Heights, MA: Allyn & Bacon.
  35. Guilford, J.P. (1982). "Cognitive psychology's ambiguities: Some suggested remedies". Psychological Review. 89: 48–59. doi:10.1037/0033-295X.89.1.48.
  36. Gardner, H. (1999). Intelligence Reframed. Multiple intelligences for the 21st century, New York: Basic Books.
  37. 1 2 Luria, A.R. (1973). The Working Brain: An Introduction to Neuropsychology (B. Haigh, Trans.). New York: Basic Books.
  38. Das, J.P., Naglieri, J.A., & Kirby, J.R. (1994). Assessment of Cognitive Processes: The PASS Theory of Intelligence. Boston: Allyn and Bacon.

Related Research Articles

Working memory is a cognitive system with a limited capacity that can hold information temporarily. It is important for reasoning and the guidance of decision-making and behavior. Working memory is often used synonymously with short-term memory, but some theorists consider the two forms of memory distinct, assuming that working memory allows for the manipulation of stored information, whereas short-term memory only refers to the short-term storage of information. Working memory is a theoretical concept central to cognitive psychology, neuropsychology, and neuroscience.

<span class="mw-page-title-main">Cognition</span> Act or process of knowing

Cognition is the "mental action or process of acquiring knowledge and understanding through thought, experience, and the senses". It encompasses all aspects of intellectual functions and processes such as: perception, attention, thought, imagination, intelligence, the formation of knowledge, memory and working memory, judgment and evaluation, reasoning and computation, problem-solving and decision-making, comprehension and production of language. Cognitive processes use existing knowledge and discover new knowledge.

<span class="mw-page-title-main">Animal cognition</span> Intelligence of non-human animals

Animal cognition encompasses the mental capacities of non-human animals including insect cognition. The study of animal conditioning and learning used in this field was developed from comparative psychology. It has also been strongly influenced by research in ethology, behavioral ecology, and evolutionary psychology; the alternative name cognitive ethology is sometimes used. Many behaviors associated with the term animal intelligence are also subsumed within animal cognition.

Dyscalculia is a disability resulting in difficulty learning or comprehending arithmetic, such as difficulty in understanding numbers, learning how to manipulate numbers, performing mathematical calculations, and learning facts in mathematics. It is sometimes colloquially referred to as "math dyslexia", though this analogy is misleading as they are distinct syndromes.

The concepts of fluid intelligence (gf) and crystallized intelligence (gc) were introduced in 1963 by the psychologist Raymond Cattell. According to Cattell's psychometrically-based theory, general intelligence (g) is subdivided into gf and gc. Fluid intelligence is the ability to solve novel reasoning problems and is correlated with a number of important skills such as comprehension, problem-solving, and learning. Crystallized intelligence, on the other hand, involves the ability to deduce secondary relational abstractions by applying previously learned primary relational abstractions.

<span class="mw-page-title-main">Spatial memory</span> Memory about ones environment and spatial orientation

In cognitive psychology and neuroscience, spatial memory is a form of memory responsible for the recording and recovery of information needed to plan a course to a location and to recall the location of an object or the occurrence of an event. Spatial memory is necessary for orientation in space. Spatial memory can also be divided into egocentric and allocentric spatial memory. A person's spatial memory is required to navigate around a familiar city. A rat's spatial memory is needed to learn the location of food at the end of a maze. In both humans and animals, spatial memories are summarized as a cognitive map.

<span class="mw-page-title-main">David C. Geary</span> American cognitive and evolutionary psychologist

David Cyril Geary is an American cognitive developmental and evolutionary psychologist with interests in mathematical learning and sex differences. He is currently a Curators’ Professor and Thomas Jefferson Fellow in the Department of Psychological Sciences and Interdisciplinary Neuroscience Program at the University of Missouri in Columbia, Missouri.

Spatial visualization ability or visual-spatial ability is the ability to mentally manipulate 2-dimensional and 3-dimensional figures. It is typically measured with simple cognitive tests and is predictive of user performance with some kinds of user interfaces.

Domain-general learning theories of development suggest that humans are born with mechanisms in the brain that exist to support and guide learning on a broad level, regardless of the type of information being learned. Domain-general learning theories also recognize that although learning different types of new information may be processed in the same way and in the same areas of the brain, different domains also function interdependently. Because these generalized domains work together, skills developed from one learned activity may translate into benefits with skills not yet learned. Another facet of domain-general learning theories is that knowledge within domains is cumulative, and builds under these domains over time to contribute to our greater knowledge structure. Psychologists whose theories align with domain-general framework include developmental psychologist Jean Piaget, who theorized that people develop a global knowledge structure which contains cohesive, whole knowledge internalized from experience, and psychologist Charles Spearman, whose work led to a theory on the existence of a single factor accounting for all general cognitive ability.

The concept of motor cognition grasps the notion that cognition is embodied in action, and that the motor system participates in what is usually considered as mental processing, including those involved in social interaction. The fundamental unit of the motor cognition paradigm is action, defined as the movements produced to satisfy an intention towards a specific motor goal, or in reaction to a meaningful event in the physical and social environments. Motor cognition takes into account the preparation and production of actions, as well as the processes involved in recognizing, predicting, mimicking, and understanding the behavior of other people. This paradigm has received a great deal of attention and empirical support in recent years from a variety of research domains including embodied cognition, developmental psychology, cognitive neuroscience, and social psychology.

<span class="mw-page-title-main">Nora Newcombe</span>

Nora S. Newcombe is the Laura H. Carnell Professor of Psychology and the James H. Glackin Distinguished Faculty Fellow at Temple University. She is a Canadian-American researcher in cognitive development, cognitive psychology and cognitive science, and expert on the development of spatial thinking and reasoning and episodic memory. She was the principal investigator of the Spatial Intelligence and Learning Center (2006-2018), one of six Science of Learning Centers funded by the National Science Foundation.

Working memory training is intended to improve a person's working memory. Working memory is a central intellectual faculty, linked to IQ, ageing, and mental health. It has been claimed that working memory training programs are effective means, both for treating specific medical conditions associated with working memory deficit, as and for general increase in cognitive capacity among healthy neurotypical adults.

Educational neuroscience is an emerging scientific field that brings together researchers in cognitive neuroscience, developmental cognitive neuroscience, educational psychology, educational technology, education theory and other related disciplines to explore the interactions between biological processes and education. Researchers in educational neuroscience investigate the neural mechanisms of reading, numerical cognition, attention and their attendant difficulties including dyslexia, dyscalculia and ADHD as they relate to education. Researchers in this area may link basic findings in cognitive neuroscience with educational technology to help in curriculum implementation for mathematics education and reading education. The aim of educational neuroscience is to generate basic and applied research that will provide a new transdisciplinary account of learning and teaching, which is capable of informing education. A major goal of educational neuroscience is to bridge the gap between the two fields through a direct dialogue between researchers and educators, avoiding the "middlemen of the brain-based learning industry". These middlemen have a vested commercial interest in the selling of "neuromyths" and their supposed remedies.

<span class="mw-page-title-main">Embodied cognition</span> Interdisciplinary theory

Embodied cognition is the concept suggesting that many features of cognition are shaped by the state and capacities of the organism. The cognitive features include a wide spectrum of cognitive functions, such as perception biases, memory recall, comprehension and high-level mental constructs and performance on various cognitive tasks. The bodily aspects involve the motor system, the perceptual system, the bodily interactions with the environment (situatedness), and the assumptions about the world built the functional structure of organism's brain and body.

Spatial cognition is the acquisition, organization, utilization, and revision of knowledge about spatial environments. It is most about how animals including humans behave within space and the knowledge they built around it, rather than space itself. These capabilities enable individuals to manage basic and high-level cognitive tasks in everyday life. Numerous disciplines work together to understand spatial cognition in different species, especially in humans. Thereby, spatial cognition studies also have helped to link cognitive psychology and neuroscience. Scientists in both fields work together to figure out what role spatial cognition plays in the brain as well as to determine the surrounding neurobiological infrastructure.

<span class="mw-page-title-main">Attentional control</span> Individuals capacity to choose what they pay attention to and what they ignore

Attentional control, colloquially referred to as concentration, refers to an individual's capacity to choose what they pay attention to and what they ignore. It is also known as endogenous attention or executive attention. In lay terms, attentional control can be described as an individual's ability to concentrate. Primarily mediated by the frontal areas of the brain including the anterior cingulate cortex, attentional control is thought to be closely related to other executive functions such as working memory.

This relationship between autism and memory, specifically memory functions in relation to Autism Spectrum Disorder (ASD), has been an ongoing topic of research. ASD is a neurodevelopmental disorder characterised by social communication and interaction impairments, along with restricted and repetitive patterns of behavior. In this article, the word autism is used to refer to the whole range of conditions on the autism spectrum, which are not uncommon.

Sex differences in cognition are widely studied in the current scientific literature. Biological and genetic differences in combination with environment and culture have resulted in the cognitive differences among males and females. Among biological factors, hormones such as testosterone and estrogen may play some role mediating these differences. Among differences of diverse mental and cognitive abilities, the largest or most well known are those relating to spatial abilities, social cognition and verbal skills and abilities.

<span class="mw-page-title-main">Spatial ability</span> Capacity to understand 3D relationships

Spatial ability or visuo-spatial ability is the capacity to understand, reason, and remember the visual and spatial relations among objects or space.

<span class="mw-page-title-main">Insect cognition</span>

Insect cognition describes the mental capacities and study of those capacities in insects. The field developed from comparative psychology where early studies focused more on animal behavior. Researchers have examined insect cognition in bees, fruit flies, and wasps. 

References