Despite optimism from many who believe that neuroscience can make a meaningful contribution to education, and that the potential exists for the establishment of a research field of educational neuroscience, some researchers believe that the two disciplines are simply too different to ever be directly linked in a practically meaningful way. In 1997 John Bruer published a major critique of what he called the "Neuroscience and education argument".
The ‘neuroscience and education argument’ as Bruer defines it, stems from three major findings in developmental neurobiology.
Early childhood is characterised by rapid growth in the number of synapses in the brain (synaptogenesis), and this expansion is followed by a pruning period.
There are so called experience dependant critical periods during which the developing brain is best suited to develop certain sensory and motor skills.
A stimulus rich environment causes greater synaptogenesis. The essential argument is that children are capable of learning more at an early age when they have an excess of synaptic growth and peak brain activity.
The knowledge of early brain development afforded by neurobiology has been used to support various arguments with regards to education. For example, the idea that any subject can to be taught to young children in some intellectually honest form, due to the great adaptability and learning potential of the young brain. Alternatively, the idea that critical periods exist for learning certain skills or knowledge sets appeals to the fact that in animal studies, if the developing brain is deprived of certain sensory inputs, the brain areas responsible for processing those inputs fail to develop fully later in development, and thus “if you miss the window, you are playing with a handicap”.
One of Bruer’s major points of contention with reports in favour of neuroscience and education is the lack of actual neuroscience evidence. Reports such as Years of Promise: A Comprehensive Learning Strategy for America's Children (Carnegie Corporation of New York, 1996) cite many cognitive and behavioural psychology studies, but no more than a handful of brain based studies, and yet draws dramatic inferences with regards to the role of the brain in learning.
Bruer argues that behavioural science can provide a basis for informing educational policy, but the link to neuroscience is “a bridge too far”, and the limitations of the application of neuroscience to education stem from the limitations of neuroscience knowledge itself. Bruer supports his critique by arguing the limitations of current knowledge regarding the three key tenets of the neuroscience and education argument. See Neuromyths
Another problem is the discrepancy between spatial resolution of imaging methods and the spatial resolution of synaptic changes that are suggested to underlie learning processes. A similar problem is true with regards to the temporal resolution. This makes it hard to relate subcomponents of cognitive skills to brain function. However, the primary flaw of the education neuroscience argument in Bruer’s opinion is that it attempts to link what happens at the synaptic level to higher order learning and instruction. The terminology, "Mind, brain and education" alludes to the idea that if we cannot bridge education and neuroscience directly, then we can use two existing connections to inform education. These are the link between cognitive psychology and education, and between cognitive psychology and neuroscience.
Bruer contends that neuroscience in its current form has little to offer educators at the practical level. Cognitive science on the other hand, can serve as a basis for the development of an applied science of learning and education. Other researchers have suggested alternative bridges to the cognitive psychology suggested by Bruer. Mason suggests that the gap between education and neuroscience can be best bridged by educational psychology, which she outlines as being concerned with "developing descriptive, interpretive and prescriptive models of student learning and other educational phenomena".
Challenges to educational neuroscience
Despite Willingham’s assertion that the potential for neuroscience to contribute to educational practice and theory is already beyond doubt, he highlights three challenges that need to be overcome in order to marry the two disciplines effectively.
The Goals Problem: Willingham suggests that education is a so called "artificial science" that seeks to construct an ‘artifact’, in this case a set of pedagogic strategies and materials. Neuroscience, on the other hand is a so called "natural science", concerned with the discovery of natural principles that describe neural structure and function. This difference means that some goals set by education are simply impossible to answer using neuroscience research, for example, the building of character or aesthetic sense in children.
The Vertical Problem: Levels of analysis: Willingham suggests that the highest level of analysis employed by neuroscientists is the mapping of brain structure and activity onto cognitive function, or even the interaction of cognitive functions (i.e. the impact of emotion on learning). Within neuroscience research these functions are studied in isolation for the sake of simplicity, and the nervous system as a whole, functioning in its entirety with all its huge composition of functional interactions, is not considered. For educators, on the other hand, the lowest level of analysis would be the mind of a single child, with levels increasing to incorporate the classroom, neighborhood, country etc.
Thus, importing research about a single cognitive factor in isolation, into a field in which context is essentially important creates an inherent difficulty. For example, while rote learning may be shown to improve learning in the research laboratory, the teacher cannot implement that strategy without considering the impact on the child’s motivation. In return, it is difficult for neuroscientists to characterize such interactions in a research setting.
The Horizontal Problem: Translating research findings: While education theory and data are almost exclusively behavioral, findings from neuroscience research can take on many forms (e.g. electrical, chemical, spatial, temporal etc). The most common form of data taken from neuroscience to education is the spatial mapping of brain activation to cognitive function. Willingham (2009) highlights the difficulty in applying such spatial information to educational theory. If a certain brain region is known to support a cognitive function relevant for education, what can actually be done with that information? Willingham suggests that this ‘horizontal problem’ can be solved only when a rich body of behavioral data and theories already exist, and points out that such methods have already been successful in identifying subtypes of dyslexia (e.g.).
Willingham suggests that what is essential for a successful union of neuroscience and education is that both fields have realistic expectations of one another. For example, educators should not expect that neuroscience will provide prescriptive answers for educational practice, answers for educational goals that are incompatible with neuroscientific methods (e.g. aesthetic training), or levels of analysis beyond the individual level. Finally Willingham suggests that neuroscience will only be useful to educators when targeted at a specific problem at a fine grained level of analysis, such as how people read, but that these data will only be useful in the context of well developed behavioral theories.
Other researchers, such as Katzir & Pareblagoev have pointed out that neuroimaging methodology as it stands may not be suitable for the examination of higher level cognitive functions, because it relies primarily on the ‘subtraction method’. By this method, brain activity during a simple control task is subtracted from that of a ‘higher order’ cognitive task, thus leaving the activation that is related specifically to the function of interest. Katzir & Pareblagoev suggest that while this method may be very good for examining low level processing, such as perception, vision and touch, it is very hard to design an effective control task for higher order processing, such as comprehension in reading and inference making. Thus, some researchers argue that functional imaging technologies may not be best suited for the measurement of higher order processing. Katzir & Pareblagoev, suggest that this may not be a deficit of the technology itself, but rather of the design of experiments and the ability to interpret the results. The authors advocate using experimental measures in the scanner for which the behavioural data is already well understood, and for which there exists a strong theoretical framework.
Transforming challenges into opportunities
Another recent review of the educational neuroscience debate by Varma, McCandliss and Schwartz focuses on eight primary challenges, divided into scientific challenges and practical challenges, facing the field, and attempts to transform those challenges into opportunities.
Scientific challenges
Methods: Neuroscience methods create artificial environments and thus cannot provide useful information about classroom contexts. Furthermore, the concern is that if neuroscience begins to influence educational practice too heavily, there may be a de-emphasis of contextual variables, and solutions to educational problems may become primarily biological rather than instructional. However, Varma et al. argue that novel experimental paradigms create the opportunity to investigate context, such as brain activation following different learning procedures and that neuroimaging can also allow for the examination of strategic/mechanistic developmental changes that cannot be tapped by reaction time and behavioural measures alone. Furthermore, Varma et al. cite recent research that shows that the effects of cultural variables can be investigated using brain imaging (e.g.), and the results used to draw implications for classroom practice.
Data: Knowing the brain region that supports an elementary cognitive function tells us nothing about how to design instruction for that function. However, Varma et al suggest that neuroscience provide the opportunity for a novel analyses of cognition, breaking down behaviour into elements invisible at the behavioural level. For example, the question of whether different arithmetic operations show different speed and accuracy profiles is the result of different efficiency levels within one cognitive system versus the use of different cognitive systems.
Reductionist Theories: Applying neuroscience terminology and theory to educational practice is a reduction and is of no practical use to educators. Nothing is gained be redescribing a behavioural deficit in neuroscientific terms. Varma et al. point out that reductionism is a mode by which sciences are unified, and that the co-opting of neuroscience terminology does not necessitate the elimination of education terminology, it simply provides the opportunity for interdisciplinary communication and understanding.
Philosophy: Education and neuroscience are fundamentally incompatible, because attempting to describe behavioural phenomena in the classroom by describing physical mechanisms of the individual brain is logically wrong. However, neuroscience may help to resolve internal conflicts within education resulting from differing theoretical constructs and terminologies used within subfields of education by providing a measure of uniformity with regards to results reporting.
Pragmatic concerns
Costs: Neuroscience methods are highly expensive, and the expected outcomes do not justify the costs. However, Varma et al. point out that educationally relevant neuroscience may attract addition funding to education research rather than usurping resources. The essential claim of educational neuroscience is that the two fields are interdependent and that a portion of the funding allocated collectively to the two fields should be directed towards shared questions.
Timing: Neuroscience, while expanding rapidly, is still in relative infancy with regards to the non-invasive study of healthy brains, and thus education researchers should wait for more relevant data to be collected and distilled into succinct theories. Contrary to this, Varma et al. argue that some success is already evident. For example studies examining the success of dyslexia remediation programmes have been able to reveal the impact of these programmes on the brain networks supporting reading. This in turn leads to the generation of new research questions.
Control: If education allows neuroscience in the door, theories will increasingly be cast in terms of neural mechanisms and debates will rely increasingly on neuroimaging data. Neuroscience will cannibalise resources and education research will lose its independence. Varma et al argue that the assumption of an asymmetric relationship between the two fields is unnecessary. Education has the potential to influence neuroscience, directing future research into complex forms of cognition and education researchers can help Educational Neuroscience to avoid naïve experiments and repetition of earlier mistakes.
Neuromyths: Thus far most of the neuroscience findings applied to education have turned out to be neuromyths, irresponsible extrapolations of basic research to education questions. Furthermore, such neuromyths have escaped beyond academia and are being marketed directly to teachers, administrators and the public. Varma et al. respond that the existence of neuromyths reveals a popular fascination with brain function. Appropriate translation of educational neuroscience results and well established collaborative research can decrease the likelihood of neuromyths.
A bidirectional relationship
Researchers such as Katzir & Pareblagoevand Cacioppo & Berntson (1992) argue that as well as neuroscience informing education, the educational research approach can contribute to the development of new experimental paradigms in neuroscience research. Katzir and Pareblagoev (2006) suggest the example of dyslexia research as a model of how this bidirectional collaboration might be achieved. In this case, theories of reading processes have guided both the design and interpretation of neuroscience research, but the existing theories were developed primarily from behavioural work. The authors suggest that the establishment of theories, which delineate required skills and subskills for educationally relevant tasks, is an essential requirement for educational neuroscience research to be productive. Furthermore, such theories need to suggest empirically testable connections between educationally relevant behaviours and brain function.
The role of educators
Kurt Fischer, director of Harvard University’s Mind, Brain and Education graduate program states "One of the reasons there is so much junk out there is that there are so few people who know enough about education and neuroscience to put the thing together". Educators have been reliant upon others’ expertise for the interpretations from Neuroscience hence have not been able to discern whether the claims made are valid or invalid representations of the research. Without a direct access to the primary research educators may be at risk of misusing results from neuroscience research. The need for so called ‘middlemen’ in the translation of research to practice has led to a situation where the application of cognitive neuroscience research findings is running ahead of the research itself.
In order to negate the need for middlemen, some researchers have suggested the need to developed a group of "neuro-educators", a specially trained class of professionals whose role would be to guide the introduction of cognitive neuroscience into educational practice in a "sensible and ethical manner". Neuro-educators would play a pivotal role in assessing the quality of evidence purporting to be relevant to education, assessing who is best placed to employ newly developed knowledge, and with what safeguards, and how to deal with unexpected consequences of implemented research findings.
Byrnes & Fox (1998) have suggested that developmental psychologists, educational psychologists and teachers generally fall into one of four orientations with respect to neuroscientific research "(1) those who readily accept (and sometimes over interpret) the results of neuroscientific studies; (2) those who completely reject the neuroscientific approach and consider the results of neuroscientific studies to be meaningless; (3) those who are unfamiliar with and indifferent toward, neuroscientific research; and (4) those who cautiously accept neuroscientific findings as being a proactive part of the total pattern of findings that have emerged from different corners of the cognitive and neural sciences". Greenwood (2009) suggests that as the body of knowledge available to educators increases, and the ability to be expert in all areas diminishes, the most productive standpoint would the fourth outlined by, that of cautious acceptance of neuroscientific findings and proactive collaboration.
Bennett & Rolheiser-Bennett (2001) point out that "teachers must be aware of and act on the science within the art of teaching". They suggest that educators must become aware of other methods and incorporate them into their practice. Furthermore, Bennett and Rolheiser-Bennett suggest that specific bodies of knowledge will play an important role in informing educators when making important decisions with regards to the "design of learning environments". The bodies of knowledge discussed include multiple intelligences, emotional intelligences, learning styles, the human brain, children at risk and gender. As the authors explain these and other areas are just ‘‘lenses designed to extend teachers’ understanding of how students learn, and from that understanding, to make decisions about how and when to select, integrate, and enact items in the … list’’.
Mason supports calls for a two-way constructive collaboration between neuroscience and education, whereby, rather than neuroscience research simply being applied to education, findings from neuroscience research would be used to constrain educational theorizing. In return, education would influence the types of research questions and experimental paradigms used in neuroscience research. Mason also gives the example that while pedagogical practice in the classroom may give rise to educational questions regarding the emotional bases of performance on school tasks, neuroscience has the potential to reveal the brain basis of higher-order thinking processes and thus may help to understand the role that emotion plays in learning and open new areas of study of emotional thought in the classroom.