The Art and Skills of Brain-Based Teaching

Education is a Learning Science

Dr. Kent Johnson, Founder & Executive Director of the Morningside Academy

The Science of Education

We know that all learning is environment-dependent because the brain depends on environmental input to modify itself. And because the brain is the organ of behavior, all learning is brain-based. Learning is a biological and environmental process that results in brain/behavior change, which occurs as a result of experience/consequences that increase/decrease the potential for improved/reduced performance and future learning. Learning can have positive as well as negative results. The integration of neuroscience and the science of behavior is rapidly expanding, and practical applications are evolving. Educational practices and decisions should be data-driven.

John T. Bruer, in his book Education and the Brain: A Bridge Too Far (1997), noted more than 20 years ago that the integration of education and neuroscience was promising. "Research on the effects of complex environments on the brain is exceedingly interesting and important because it does begin to link learning with synaptic change and brain plasticity." Education significantly contributes to shaping the synaptic self. Bauer also warned us at the time, "educators should be cautious in interpreting this work and in thinking about how it might inform policy and practice."

"It is well established that throughout a long evolutionary process, the human brain has incorporated a significant propensity for the influence of environment/experience to its development like that of no other species.  In other words, the human brain is a unique biological system that has evolved to become increasingly dependent on environmental input/experience and is in fact, less controlled by its biology. It is now clear that the human brain is an organ made for learning from experience. This fact is why we should make it a high priority to find the best ways to educate our children. It is possible to make a permanent difference in the architecture of the individual brain." (John T. Bruer, Education and the Brain: A Bridge Too Far).

Since then, the principles and research of brain-based learning have continued to expand, although rather slowly. Eric Jensen is a teacher with a Ph.D. in human development. In his books and articles, he synthesizes brain research and provides practical applications for teachers. He has published Teaching with the Brain in Mind (2005) where he provides educators with the message, "You have far more influence on student's brains than you realize…and you have an obligation to take advantage of the incredible revelations science is providing." In 2008, Jensen published A Fresh Look at Brain-Based Education and he noted, "The real issues that we should be talking about are what environmental, instructional, and social conditions can help us enrich student's lives." Good advice indeed!

Kieran O'Mahony is the founder of the Institute for Connecting Neuroscience with Teaching and Learning, a nonprofit that provides professional development for K-12 teachers with the aim of improving learning outcomes. He has conducted translational research by connecting neuroscience with teaching and learning at the University of Washington College of Education. He published The Brain-Based Classroom (2020), in which he translates findings from educational neuroscience into practices for teachers. He describes the importance of focusing on the teaching and learning environment, instructional methods, and social conditions as the key factors in developing evidence-based educational practices. 

Yi-Yuan Tang (2017), is a psychologist and neuroscientist at Arizona State University. In his book Brain-Based Learning and Education: Principles and Practices, he focuses on the integration of neuroscience and education that "takes us from a deep understanding of brain function to the frontline of the classroom." His is a practical and well-researched book.

The education community has taken notice that understanding the learning brain approach has the potential to enhance the practice of education as a data-driven learning science. Currently, there is a need to expand the research linking the learning environment, the teaching methodology and practices, curriculum development, and cognitive neuroscience. Accomplishing this will require the measurement of learning outcomes that are performance-based.

Brain Science and the Future of Education

Teachers are brain changers. They skillfully and artfully arrange the teaching environment for learning to occur. It is therefore imperative that they have the technical as well as practical knowledge about the organ of learning. Unfortunately, this is not happening. Most teachers are not taught how the brain receives, filters, and processes the input of information from the environment. Nor are they taught how the environment can be arranged to maximize learning and brain change. Most teachers are not cognizant of the impact of what they do on the developing brain of the children they teach. Colleges of Education need to invest in developing research centers and educating future teachers to bring the growing body of educational neuroscience research into the environmental design of schools, classrooms, curriculum, and performance measures. The goal is to ensure that each unique student - regardless of background - will learn and develop, with the guidance of a teacher who knows the research, methods, and specific curriculum to teach that child with their brain in mind.

Colleges of Education are entrusted to prepare future teachers to apply best practices. Knowledge about the science of learning and brain research can provide a component of a multidisciplinary conceptual framework for educators as they study and develop evidence-based teaching practices.

The American Federation of Teachers (2000) noted, "It is vital that teachers learn from scientific research how people learn." In our view, brain-compatible teaching is essential for optimal evidence-based teaching and learning.

Building Evidence-Based Education

Evidence-based education is founded on the premise that educational practices should be based on the best available scientific evidence. Proven educational practices lay the foundations for teaching and learning. They provide scientific evidence in the form of quantifiable individual student performance data that guide educational practices and policies. Educational decisions for each student should be data-driven.

Evidence-based teaching requires the use of evidence to do the following: 1) establish where students are in their learning (individualized performance measurement); 2) based on where the student is performing as measured, decide and implement appropriate teaching strategies and interventions; and 3) collect performance data to monitor and quantify the student progress and evaluate teaching effectiveness. This requires reframing our approach to the education of our children by adopting an individualized direct instruction and generative approach that can provide quantifiable data on a child's performance. This will address the variability in performance inherent in the student population and the learning process as well as work towards giving every child an equitable learning opportunity by creating an individualized and accountable learning environment.

The education establishment has a history of quickly adopting new ideas and practices without investing in scientifically evaluating their merits and outcomes. This absence of a scientific perspective has precluded systematic improvements in the system. Incorporation of teaching with the brain in mind will focus on individualized teaching and performance measurement that will ensure equal learning opportunities for all children.

Generative Learning

Merlin Wittrock was an educational psychologist who is best known for his generative theory of learning first published in 1974. It earned him the E. L. Thorndike Award in 1987. In 1992 he published in the Educational Psychologist one of his most referenced articles, Generative Learning Processes of the Brain. He described "the model of generative learning and teaching as a functional model of learning from instruction that builds upon knowledge about the processes of the brain and upon cognitive research on comprehension, knowledge acquisition, attention, motivation, and transfer." The student is not a passive recipient of the information; instead, the student is an active participant in the learning process, working to construct a meaningful understanding of information found in the environment. Learning then becomes a generative activity. 

Generative learning involves actively making sense of to-be-learned information by the process of recognizing and integrating the information with one's prior knowledge, thereby enabling the learner to apply what they have learned to new situations. The learning process is based on the memory that has been stored in the brain from previous experiences, and as new data are added to long-term memory, they become part of the knowledge base. The teaching environment and the brain are working together in the student's acquisition of new knowledge. Learners, in the process of "generation," establish relationships between new information and the information already in the brain's memory. Problem-solving is one of the most effective generative learning activities since it requires the student to evaluate all of the circumstances surrounding the problem and evaluate them using the skills and information they already have.

The fact is that by engaging in generative learning the brain’s neural networks are being rewired and modified. Neuroimaging studies have demonstrated that the human brain involves multiple levels of organization, with cognitive function arising from the interaction of functional specialization and integration of data in response to environmental input. These studies, involving functional imaging, have begun to systematically evaluate the fundamental properties of human brain organization involved in learning. Teaching can become a data-based practice and the brain/behavior changes will be quantified. By individualizing the teaching process, we can make sure that, when we teach with the brain in mind, we are creating brain networks that support worthy performances.

Here is a great reference for those who want to learn more about learning science. The Organisation For Economic Co-Operation and Development, composed of 30 countries including the United States, published Understanding the Brain: The Birth of a Learning Science through the Centre for Educational Research and Documentation. This extensive and well-researched document is available via Google Scholar.

Morningside Academy - Generative Instruction Model

Kent Johnson founded Morningside Academy in 1980. It is based in Seattle, Washington, and offers a learning guarantee. One of the principles is that many learning problems are mostly teaching problems. Their teaching methodology incorporates the behavioral methods of Precision Teaching (PT), a measurement and decision-making technology, developed by Ogden Lindsley. PT uses frequency and rate of change in behavior as its basic data. It is a precise and systematic method for evaluating instructional practices and curricula. They also use Direct Instruction (DI), developed by Sigfried Engelmann. DI was designed to maximize the effectiveness and efficiency of instruction, emphasizing that students must establish and demonstrate mastery of skills to progress. This requires students to be taught in small groups so that individualized instruction can be provided, and the group should be based on skill level (nifdi.org for more detail). The teacher also incorporates task analysis and instructional design described by Susan Markle in her book, Design for Instructional Designers, 1978. Task analysis is used to break down complex skills into manageable, discrete steps. The data from task analysis provides a better understanding of the learner’s objectives, the context within which they operate, and the task they must perform so one can design proper measurements of performance. Based on the task analysis, the instructional design can be developed by identifying in quantifiable measures the learning objectives, instructional activities, and the assessments used to measure performance.

Generative teaching uses behavioral methods to bring a student's knowledge of skills to the level of "fluency." Carl Binder, in The Behavior Analyst (1996) published Behavior Fluency: Evolution of a New Paradigm. He defines fluency as "second-nature knowledge, near automatic performance, the ability to perform without hesitation-in short, true mastery." The ultimate objective is to teach generative repertoires such as thinking, reasoning, and questioning routines that facilitate complex problem-solving.

One of the hallmarks of Morningside Academy is that once a student has learned basic skills, instruction changes focus and concentrates on teaching thinking skills in reading comprehension, mathematics, social studies, and science. Then the method of Talk-Aloud-Problem-Solving (TAPS) is used. Teachers model and coach students to think out loud, using specially designed protocols that represent many ways to solve problems. Then students coach each other to become fluent in using the TAPS protocol to solve a range of problems. This gradual shift from DI to TAPS allows students to master basic academic skills as well as highly advanced problem-solving and thinking skills. There is then a gradual move from teacher-directed instruction to independent learning. Self-directed behavior is generated. This will serve the student well in the journey through life.

Students that are not performing well or lagging behind are provided additional support by a variety of methods, including peer tutoring as well measuring students' performance daily. Teachers as well as students use these data to make decisions about instructional and learning strategies. The learning environment created by the generative model of instruction, like coaching each other, promotes prosocial behavior. Nurturing and cooperative behavior enhances the learning environment and sets the stage for improving academic outcomes. By encouraging sharing, like helping others via peer tutoring, prosocial behavior is shaped, reinforced, and practiced.  

The generative approach facilitates the acquisition of skills that are not directly taught. It becomes a fluent and lifelong learning enterprise. Through the generative learning experience, the child has acquired the brain wiring and behavior to engage in a life of prosocial behavior and worthy performances. Imagine the society and culture that they will create!

For those that want to learn more about Generative Instruction, we recommend:

Johnson, K., Street, E. M., Kieta, A. R., & Robbins, J. K. (2021). The Morningside Model of Generative Instruction - Building a Bridge Between Skills and Inquiry Teaching. Sloan Publishing.

Johnson, K. (2015). Behavioral Education in the 21st Century. Journal of Organizational Behavior Management. https://doi.org/10.1080/01608061.2015.1036152 

Pass it on and see you next week.

Francisco I. Perez, PhD.

Henry S. Pennypacker, PhD.

Faris R. Kronfli, PhD.

Our book Engineering the Upswing can be found at the Cambridge Center for Behavioral Studies and Amazon.