Brain based learning - University of Delaware



Understanding how brain-based research and Universal Design for Learning may have implications on the use of multimedia in the classroom

Dan Fendler

December, 2007

 

The phrase “brain-based learning” today is often over used. It refers to the role of modern imaging and electromagnetic technology in studying how the brain functions under a cognitive load and its potential application to the classroom. There has been a great deal of work done in the area of brain imaging. This work covers a number of different areas of brain research, but none more exciting or highly debated than its potential application to the field of education. A number of overly-enthusiastic members of the media and the educational community have propagated myths and misconceptions that have caused friction between those who see the tremendous promise of brain research in educational applications and those neuroscientists who caution that, while promising, application of brain research directly to classroom practice is premature.

A quick look at some of the tools, terminology and technologies used in the study of brain function is requisite to a discussion of brain research. Cognitive neuroscientists use several technologies to study the physical functioning of the brain. Some of the more frequently used include the following:

• Positron Emission Tomography (PET), which measures the change in cerebral blood flow, oxygen use and glucose use related to brain activity. This is not used much in research of younger subjects due to the need to inject trace radioactive elements.

• Functional Magnetic Resonance Imaging (fMRI), which measures changes in the ratio of oxygenated blood to deoxygenated blood that, theoretically, can be linked to neural activity. It measures how different areas of the brain use nutrients and oxygen while performing cognitive tasks. fMRI’s strength is that it has good spatial resolution (ie: can be used to pinpoint the area of neural activity), but poor temporal resolution (ie: it’s more difficult to use to determine the timing of electrical impulses in brain activity). fMRI measures the change in blood flow in seconds. Complex cognitive functions take place in milliseconds (Szűcs and Goswami, 2007).

• Both PET and fMRI allow neuroscientists to take "pictures" of the brain while the subject performs cognitive tasks. Because of the limits of the technology, the pictures, or images, do not provide the detail needed to determine how the different components of the brain interact with each other. So at this point in neuroscience, the images can't really be used to draw conclusions about how the research might translate into creating more effective "brain-based" education.

• Electroencephalograms (EEG's) provide functional brain images (Szűcs, Goswami, 2007). An EEG can measure that electrical brain activity is occurring, but cannot pinpoint the exact location of the activity (ie: EEG’s provide good temporal resolution but poor spatial resolution). Goswami (2004) discusses a neuroimaging concept useful in cognitive neuroscience research: ERP, or event related potential. ERP rhythms provide information on the timing of neural events, which can be "used to understand underlying cognitive processes." Wikipedia defines an event-related potential (ERP) as any stereotyped electrophysiological response to an internal or external stimulus. More simply, it is any measured brain response that is directly the result of a thought or perception. EEG’s can reliably measure ERP’s.

• Magnetoencephalography (MEG) takes the technology a step further than EEG and measures the magnetic field generated by neural activity, and also provides better spatial resolution. The biggest drawback to MEG is its cost - it's much more expensive than EEG.

• When used in concert, these tools provide a picture that is difficult to interpret. Much more research is needed in how to correlate output from the different techniques.

Brain-based controversy

Tremendous strides in the area of brain imaging technology are partially responsible for the propagation of many misconceptions surrounding the application of brain science to education. These misconceptions are commonly referred to neuromyths. One of the prominent voices in the application of neuroscience to education, John Bruer, has been outspoken in warning the community at large that the use of neuroscience to support educational policy and programs is premature. In his oft cited article Education and the Brain: A Bridge Too Far (1997), Bruer spoke to the idea that neuroscience does not have much to offer the field of education today. Educators, however, are extremely interested in how neuroscience research might improve education. Some Cognitive science, educational and neuroscience researchers flirt with the idea that brain research could potentially benefit curriculum development if the research can be directly applied. One of Bruer’s concerns is that certain educators cite research that they claim supports a neuroscience-education link, regardless of the lack of empirical evidence that supports the claim. Bruer argues that a creating a link is premature and that neuroscience does not adequately understand brain development and therefore cannot be used to support scientific claims that foster changes in curricular development.

To get a clearer picture of the nature of the conversation taking place, it is useful to discuss the different disciplines involved. Study of the mind is traditionally the bailiwick of cognitive psychology. The study of the physical attributes and functioning of brain (which covers the study of the physical processes that take place in the brain) is traditionally the area of neuroscience. The study of the mind-brain interface is the bailiwick of cognitive neuroscience. Bruer claims that cognitive psychology has a justified claim to the area of applying basic science to the area of learning and education. He argues that neuroscience discoveries about neurons and synapses are not sufficient to guide educational practices and suggests that cognitive psychology is better suited to help solve instructional design issues. Cognitive neuroscience, he states, is too new to be used to help guide educational practice.

Mayer writes that educational psychologists have, until recently, ignored much brain research. He cites the predominant use of drill and practice educational methods as put forth by E. L. Thorndike (1926), a prominent educational psychologist who played a central role in connectionist theory of learning, as an example of building educational psychology around brain research (Mayer, 1998). It wasn't until the 1960's that cognitive psychologists considered these connectionist theories less meaningful than constructivist theories of learning that are discussed today. Mayer cautions against making similar mistakes in tying educational psychology to brain research today.

Sousa, a fairly prolific author and former educator, argued in 1998 that it was not premature to begin using brain-based research in the classroom because there is too much encouraging evidence that it has positive effects on learning (Sousa, 1998). However, he freely admits that the evidence he offers is anecdotal. Sousa does agree that collaborative efforts on the part of cognitive psychologists, neuroscientists and educational practitioners will help improve educational practice.

Murray, in an article titled From Brain Scan to Lesson Plan (Murray, 2000) reports that most researchers and educators agree that psychologists need to be a part of the process of interpreting imaging research and it's implication on educational practice. The articles sub-heading states that “Neuroscientists are uncovering how the human brain learns and will soon be able to translate that knowledge to the classroom”. It’s headings like these that may have fueled the tension between neuroscience and education. She does agree that increased collaboration between the disciplines is needed to progress in any meaningful way. 

In an article titled Brain-based Learning: A Reality Check (Jenson, 2000), Jenson writes that brain-based learning is no panacea to solving the problems in education. He argues that to ignore the implications of brain-based learning is short sighted, but also cautions that well meaning educators may misinterpret findings on brain-based research. Educators should exercise caution when citing research that justifies a particular strategy. Jenson also recognizes that research needs to be more collaborative in order to piece together the complex puzzle of brain research and its implications on educational practice.

Wolfe speculates about how an experience enters the brain and is distributed over the cortex.  Because different content is stored in different areas, she argues that since recalling information requires different brain functioning and processing (eg, images are stored in one area, source information in another), providing multiple means of representation will help a student remember what is learned. Wolfe encourages educators to become more literate in the area of the brain and brain research. She also provides some insight to educators on how to read and interpret research. She urges caution when making broad implications of research science and the classroom (Wolfe, 2001).

Bruer again cautions the educational community against making inference from brain structure to function (Bruer, 2002). He writes that the media, some policy advisers and so called brain-based educators seem more eager to embrace current brain science research than the educational research community. He reiterates that research in this area (ie: how neural structures implement mental functions) is still in the early stages.

Taking a more philosophical perspective, Davis jumps into the fray and tries to show (in a very philosophical article) "how the contribution of brain science to our grasp of the nature of learning is limited in principle" (Davis, 2004). He does, however, conclude that a collaborative approach to research is needed to make progress in the understanding of learning. He imagines a group consisting of neurophysiologists, cognitive psychologists, anthropologists and social scientists (with help from philosophers) that could collaboratively consider recommending approaches to education and learning.

In a review of brain-based learning, Hall points out that there are at least three different levels of study involved in brain science: neuroscience, psychology and education. While he outlines the distinctions between the various disciplines, he also advises that there is a big gap between the physiology of the brain and any practical application to education. Hall apparently agrees that skeptics are justified in criticizing the wilder claims that may serve the purpose of supporting their own views. He attempts to dispel the myth of instant transformation of teaching and learning based on so called brain-based education. He also agrees that a more collaborative approach is needed and that there are promising developments in the areas of "language learning, literacy, numeracy dyslexia and the link between emotion and learning" (Hall, 2005).

In her article titled Neuroscience and education (Goswami, 2004), Goswami points out that the field of neuroscience does not yet study teaching. This leads her to state that the creative use of cognitive neuroscience has promise in the areas of curriculum design, in addition to teaching practices.

In a Science magazine editorial, Stern (2005) strongly advises that we need to scale down unrealistic expectations to ensure that false promise is not given to public policy makers, or the general public. She also warns that some early adopters of "brain-based" educational programs have overlooked the lack of empirical evidence supporting their positions. She does hold out hope for more collaboration between the various disciplines, which could prove promising.

Szűcs and Goswami argue that, with the advances in neuroscience research, responsible use of neuroscience research to inform education is not a "bridge too far" (Szűcs and Goswami, 2007). They provisionally define educational neuroscience as "the combination of cognitive neuroscience and behavioral methods to investigate the development of mental representations." The authors clearly favor a collaborative, multi-disciplined approach to educational neuroscience research.

Toward a more collaborative approach

A common theme that recurs throughout the literature surrounding brain-based research is the idea of pursuing a more collaborative approach to addressing these issues. Harvard University took a leadership position in this collaborative approach and, in 2000, announced a concentration in Mind, Brain and Education as part of Harvard’s graduate program (Blake & Gardner, 2007) to answer the increasing public interest in this area. In 2002 Fisher and Gardner began to teach a course called “Cognitive Development, Education, and the Brain” as part of that program. The program was designed to help synthesize information across the disciplines of psychology, neuroscience, genetics and education. Since this time, there have been more collaborative efforts in addressing some of these issues surrounding the use of neuroscience research in educational practice. A journal that was launched in 2007, Mind, Brain, and Education (MBE), “grew out of the International Mind, Brain, and Education Society's mission to create a new field of mind, brain and education, with educators and researchers expertly collaborating in integrating the variety of fields connecting mind, brain, and education in research, theory, and/or practice” (Blackwell publishing website, 2007). The International Mind, Brain, and Education Society’s objectives are:

• To improve the state of knowledge in and dialogue between education, biology, and the developmental and cognitive sciences.

• To create and develop resources for scientists, practitioners, public policy makers, and the public.

• To create and identify useful information, research directions, and promising educational practices. (From the IMBES website, )

Much of the literature stresses the importance of establishing bridges between the various disciplines in order to advance brain functioning knowledge. Among those who were working toward advancing the dialogue were Ansari and Coch (2006), who suggested a framework of multiple bridges to make and strengthen connections between education and cognitive neuroscience. In a provocative article, the authors discuss this framework as a mechanism to facilitate collaboration between the different disciplines. They discuss the emerging field of mind, brain and education (MBE). They believe "that MBE should be characterized by multiple methodologies and levels of analysis in multiple contexts, in both teaching and research, and by members who will in the future effortlessly translate among those levels, in essence a multilingual constituency". Ansari and Coch are also strong proponents of increasing scientific and cognitive literacy among teachers. They feel that the lack of teacher neuroscience literacy leads to misguided claims and practices related to brain-based learning techniques in the classroom. They find it surprising that pre-service teachers are not required to receive cognitive neuroscience training in their studies. They also note that the idea of integrating cognitive neuroscience training into teacher education is not new. In fact, it was proposed over 20 years ago. Ways to improve communication between teachers and neuroscientists are also suggested. In addition to integrating some cognitive neuroscience training in teachers’ education, they also propose integrating classroom experience in neuroscience training. They conclude the article by suggesting that two bridges need to be built to advance the science of learning: one path leading to the development of educators that apply cognitive neuroscience evidence to teaching practice, and the second to facilitate the development of scientists who communicate with educators.

Universal Design for Learning

The origin of Universal Design for Learning (UDL) has its roots in brain-based research. Rose and Strangman (2007) write that “although neuroscience suggests that every act of cognition is considerably complex, psychological and neuropsychological research recognize three broad but anatomically and psychologically distinct functions that are involved in every act of cognition”. These functional areas are defined as brain components that recognize patterns, generate patterns and recognize the significance of patterns that are essential to the core of UDL. These areas have been roughly identified and studied with the use of brain imaging technology.

The idea of Universal Design (applied to architecture, not education) originated approximately 30 years ago. Ron Mace, an architect and wheel chair user, proposed the idea that buildings, landscape and other physical environments should be proactively designed to accommodate the needs of the widest array of individuals. According to the North Carolina State University website, "[Ron] coined the term "universal design" to describe the concept of designing all products and the built environment to be aesthetic and usable to the greatest extent possible by everyone, regardless of their age, ability, or status in life." In the early 1990's, an organization called the Center for Applied Special Technology, or CAST, was working to apply the concept of universal design to the area of education. CAST coined the term "Universal Design for Learning", or UDL, to define that effort (Hitchcock, et al, 2002). Some of the foundations of UDL lie in the work of Vygotsky (1978, 1986), who laid out conditions that must be met in order for learning to occur. According to Vygotsky, for learning to occur, the learner must (a) recognize patterns in sensory data, (b) have one or more strategies for operating on the perceived patterns, and (c) be engaged both by the strategies and the sensory data to which he or she is applying them (Pisha and Coyne, 2001). In UDL terms, these conditions map to three important UDL defined primary networks that play a role in learning: the recognition network, the strategic network and the affective network. As described in Teaching Every Student (CAST, 2002), these networks are said to be used in a variety of cognitive tasks related to learning. Take the recognition network, for example. According to CAST, recognition (employed in the cognitive task of reading) is facilitated by distributed processes in the brain. Different processes employ different areas in the brain. Reading, for example, uses different areas of the brain depending on whether the material is presented visually, tactilely (eg, Braille) or auditorily. CAST suggests that presenting material in a variety of ways might improve the chance that a learner could use the brain area best suited to their own learning style to complete the task at hand.

Here's a brief definition of each of the networks as put forth by CAST (Teaching Every Student, 2002):

o Recognition networks are specialized to sense and assign meaning to patterns we see; they enable us to identify and understand information, ideas, and concepts.

o Strategic networks are specialized to generate and oversee mental and motor patterns. They enable us to plan, execute, and monitor actions and skills.

o Affective networks are specialized to evaluate patterns and assign them emotional significance; they enable us to engage with tasks and learning and with the world around us.

UDL principles call for altering teaching methods and materials in order to accommodate each individual learner’s brain networks. They propose doing all the necessary work up front in the curriculum design phase. Much of the work in the area of effective curricular design was in part inspired by the need for more effective teaching techniques that could reach a wider range of students, including those with special needs.

In order to support the diverse range of students in today’s classroom, UDL principles suggest employing multiple means of representation to accommodate the recognition network, and thereby support the use of digital text to provide the needed flexibility. By providing text in alternate formats, CAST believes that students with different learning styles can have access to the format that best complements their own learning style. UDL principles also suggest anticipating and accommodating differences in the strategic network by employing multiple means of expression tactics in order to support the individual strengths each student possesses. For example, students may be allowed to write a paper, create a presentation, or record a podcast as an option to complete an assignment. UDL also emphasizes the importance of student engagement in the learning process. According to CAST, students would theoretically be more engaged in the learning process if curricula were designed from the start to appeal to the affective network. CAST suggests using tools and techniques to support the affective network through multiple means of engagement. Adherence to any of these principles certainly implies a potential increase in classroom multimedia usage.

Caveats regarding UDL’s application to education

It is important to note here that there is not much empirical evidence available that support UDL claims. Research continues in this area, but no definitive conclusions can be drawn regarding the scientific underpinnings of UDL. In their article, McGuire, el al (2006), discuss Universal Design and several different models of educational applications, including Universal Design for Learning, Universal Instructional Design and Universal Design for Instruction. While they recognize the promise of such constructs, they caution against a rush to blanket acceptance until significant research is conducted that supports claims that may be promoted as fact.

There is some indication that UDL may be gaining ground in some education circles. This becomes evident when you look at pending legislation sponsored by several US senators. Support for Universal Design for Learning is included in a NCLB “reauthorization measure sponsored by Sen. Joseph I. Lieberman, I-Conn. and co-sponsored by Sens. Norm Coleman, R-Minn., and Mary L. Landrieu, D-La. Much of the Senate bill includes language taken verbatim from the coalition's materials” (Education Week, 2007). The passage of sweeping education reform not supported by rigorous scientific research may not be a recipe for long term success. In my own opinion, it would be more prudent to fund and conduct much more research before implementing broad changes in education policy without scientific underpinnings.

Implications for the use of Multimedia in education

Technology does not necessarily improve education. Take a simple innovation like the pencil: One can use it to write a superlative essay, to drum away the time, or to poke out someone’s eye.

Veenema & Gardner, 2002

An attempt to discuss the current trends in multimedia learning cannot be undertaken without recognizing that there is no universal agreement in published literature that the use of multimedia in educational materials is entirely effective. While it is not my intent address this issue in any substantial way, it is prudent to recognize that a wide range of contradictory views exist on the subject of multimedia learning (Samaras, et al, 2006). I should be clear that I do side with Veenema and Gardner (2002) who write that “technologies like CD-ROM that include a variety of media may well be able to help more students form rich representations of an event and cultivate deeper understandings. However, it is unrealistic to expect this to happen by simply adding more information and more media”.

The principles put forth by UDL suggest an increased use of multimedia in class materials and methods. For example, in an effort to support multiple means of representation, CAST has been instrumental in the implementation of the National Instructional Materials Accessibility Standards, or NIMAS. According to the CAST website, “NIMAS is a technical standard used by publishers to produce source files (in XML) that may be used to develop multiple specialized formats (such as Braille or audio books) for students with print disabilities”. The NIMAS standards were part of IDEA 2004, and went into effect in December 2006. All new classroom materials developed after that time are required to be provided in the NIMAS format. The intent is to make text readily available in a format that will accommodate individuals with visual impairment and students with organically based learning disabilities. As part of the NIMAS regulations, a National Instructional Materials Access Center, or NIMAC, was established to function as a repository for instructional materials in NIMAS format. What this means is that recent material from publishers is being held in this repository in order to provide ready access. The NIMAC is now live and can be accessed at nimac.us.

While access to the NIMAC is not available to schools directly, it is a step in the direction of providing easier access to digital content. This could potentially open up a number of multimedia opportunities relative to this digital content. For example, digital content can easily be transformed to audio format by using text-to-speech software. Digital text can also be easily manipulated to alter the text size if needed. Digital representation could also allow for more flexibility in how graphs and tables are manipulated and viewed, potentially accommodating a number of different learning styles. As more educational publishers incorporate more multimedia components (eg: video, sound, images, etc) into their publications, this may also open up additional opportunities to achieve multiple means of representation.

Regarding the strategic network outlined by CAST, there is ample opportunity to incorporate multimedia in the curriculum to support multiple means of expression. For example, when assessing comprehension of a reading assignment, options might be offered to each student. They could produce an essay (handwritten, typed, or voice generated), create a presentation, or create a movie as acceptable possibilities. Any of these suggestions could potentially include a multimedia component. In order to make lessons more engaging and thus address the need for multiple means of engagement, careful integration of any number of multimedia components is possible.

Closing Thoughts

It is clearly an exciting and challenging time in education today. Exciting, but also intimidating to many educators. The advances in brain-based research seem to hold much promise, particularly if they can be applied to classroom methods that may help our children achieve a powerful and effective education. But it may be wiser to temper that excitement by reminding ourselves that, while promising, there is very little empirical evidence supporting the notion that brain-based research can be applied directly to the classroom.

One obvious presumption is that much more research is needed, particularly in the area of classroom research that has roots in brain-based neuroscience. I believe that it is critical to conduct that research prior to implementing broad changes in educational policy. While a collaborative approach seems inevitable among education, neuroscience and psychology, the temptation to jump to hasty conclusions is hard for some to resist. We must resist the temptation of a quick fix to an issue that has such essential consequences. To best prepare for the technological onslaught of the implications of cognitive neuroscience, we might seek to educate all interested parties in this conversation (especially teachers), as appears to be the goal of the International Mind, Brain and Education Society and Harvard University. But perhaps most importantly, we should be mindful of rushing headlong into broad education policy changes until more research has been conducted. The consequences of any potential missteps are far too critical.

References

 

Ansari, D., & Coch, D. (2006), Bridges over troubled waters: Education and cognitive neuroscience. Trends in Cognitive Sciences, Vol. 10, No. 4, 146-151.

Blake, P.R., & Gardner, H. (2007), A first course in mind, brain, and education, Mind, Brain, and Education, Vol. 1, No. 2, 61-65.

Bruer, J.T. (1997), Education and the brain: A bridge too far. Educational Researcher 26, 4-16.

Bruer, J.T. (2002), Avoiding the pediatricians’ error: How neuroscientists can help educators (and themselves). Nature Neuroscience Supplement, Vol. 5, 1031-1033.

Davis, A. (2004), The credentials of brain-based learning, Journal of Philosophy of Education, Vol 38, No. 1 21-35.

Fischer, K.W., Daniel, D., Immordino-Yang, M.H., Stern, E., Battro, A., & Koizumi, H., (2007) Why Mind, Brain, and Education? Why Now?, Mind, Brain, and Education, 1, 1–2.

Goswami, U. (2004), Neuroscience and education, British Journal of Educational Psychology, 74, 1-14.

Goswami, U. (2006), Neuroscience and education: From research to practice?, Nature Reviews Neuroscience, 7, 406-413.

Hall, J. (2005), Neuroscience and education: What can brain science contribute to teaching and learning?, The SCRE Centre, Retrieved November 12, 2007 from .

Hitchcock, C., Meyer, A., Rose, D. & Jackson, R. (2002), Providing access to the general curriculum, Universal Design for Learning, Teaching Exceptional Children, Vol. 35, No. 2, 8-17.

Jenson, E. (2000), Brain-based learning: a reality check, Educational Leadership, Vol. 57, No. 7, 76-79.

Mayer, R.E. (1998), Does the brain have a place in educational psychology?, Educational Psychology Review, Vol. 10, No. 4, 389-396.

Mayer, R.E. (2003), The promise of multimedia learning: using the same instructional design methods across different media, Learning and Instruction, 13, 125-139.

McGuire, J.M., Scott, S.S., & Shaw, S.F. (2006), Universal Design and its applications in educational environments, Remedial and Special Education, Vol. 27, No. 3, 166-175.

Murray, B. (2000), From brain scan to lesson plan, Monitor on Psychology, Vol. 31, No. 3, Retrieved Nov 16, 2007 from .

Pisha, B., & Coyne, P. (2001), The promise of Universal Design for Learning, Remedial and Special Education, 22(4), 197-203.

Pisha, B., & Coyne, P. (2001), Jumping off the page: Content area curriculum for the Internet age, Reading Online, 5(4), Retrieved Nov 12, 2007 from: .

Rose, D.H. & Meyer, A. (2002), Teaching every student in the digital age: Universal Design for Learning. Alexandria, VA: Association for Supervision and Curriculum Development.

Rose, D.H. & Strangman, N. (2007), Universal Design for Learning: Meeting a challenge of individual learning differences through a neurocognitive perspective, Universal Access in the Information Society, Vol. 5, No. 4, 381-391.

Sousa, D. A. (1998, December 16). Is the fuss about the brain research justified? Education Week, 18(16). Retrieved Nov 13, 2007 from .

Stern, E. (2005), Pedagogy meets neuroscience. Science. Vol. 310, 745.

Szűcs, D., & Goswami, U. (2007), Educational neuroscience: Defining a new discipline for the study of mental representations, Mind, Brain, and Education, Vol. 1, No. 3, 114-127.

Samaras, H., Giouvanakis, T., Boustiou, D., & Tarabanis, K. (2006), Towards a new generation of multimedia learning research, AACE Journal, 14(1), 3-30.

Veenema, S. & Gardner, H (2002), Multimedia and multiple intelligences, The American Prospect, Vol. 7, Issue 29.

Wolfe, P. (2001), Brain research and education: fad or foundation? Brain Connection, Retrieved Nov 16, 2007 from content/160_1.

Websites



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