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Summary of the Presentation


Daniela Kaufer is Associate Professor of Integrative Biology, Director of the Kaufer Laboratory, and a faculty member of the Helen Wills Neuroscience Institute at UC Berkeley. Professor Kaufer’s research focuses on cellular and molecular neurobiology, specifically the events that underlie the plasticity of the brain in the face of stress and neurological injury, and its effects on learning and memory. She has published in numerous journals including Nature NeuroscienceNature, the Proceedings of the National Academy of Sciences, the Journal of NeuroscienceNature Medicine, and Science. Professor Kaufer participated in the Presidential Chair Fellows Program at UC Berkeley during the 2007–2008 academic year, and she is the recipient of the 2010 National Institute of Mental Health Director’s New Innovator Award.

Video of the Presentation

Presentation by Daniela Kaufer to the How Students Learn Working Group on January 25, 2011.

Summary of the Presentation

Mind, Brain, and Education

Professor Kaufer opened with a quotation: “All animals learn, very few teach” (Blakemore and Frith, The Learning Brain). She pointed out that, although the educational process involves both learning and teaching, neuroscience research usually focuses only on learning, as teaching is less common in animal models and difficult to study using neuroscience methodology. There is, however, a developing subfield within neuroscience called “Mind, Brain and Education” (MBE) that attempts to link research with teaching. MBE researchers consider how to take advantage of the natural human attention span, how to use studies about memory systems to inform lesson planning, and how to use research on the role of emotions in learning.

Research on Stress and Learning

In regard to this last point, the role of the emotions in learning, Kaufer described the “affective filter hypothesis,” the idea that how we feel influences how we are able to learn. Emotional states, particularly stress, influence learning, memory, and decision making. Neurobiologically, stress indicates activation of the amygdala, the segment of the brain connected with emotions and fear. The amygdala sends information to the hippocampus, the brain region associated with learning and memory; as a result, we learn and remember differently when the amygdala is firing. The stress response — popularly known as the “fight or flight” response — is chemically understood as the production of a variety of hormones, most significantly cortisol. In brief moments of stress such as emergencies (Kaufer gave the classic example of seeing a poisonous snake), the adrenal gland releases cortisol into the brain, which helps us to combat or avoid the situation. However, when people experience chronic stress, the amygdala is constantly activated, and stress becomes an event in itself, rather than a response to a stimulus. Because the stress response has a negative impact on decision making, and decision making is a key component of learning, chronic stress decreases our ability to learn.

Cellular Biology of Learning: Neuroplasticity and Neurogenesis

Kaufer went on to describe several of the biological aspects of learning, including neuroplasticity and neurogenesis. Plasticity, the capacity of the brain to change and develop, is both synaptic and dendritic. That is, changes may occur regarding the connections between neurons (synapses) or in the neurons themselves (dendrites) — or, to put it simply, we can both reorganize our knowledge and change the quality and nature of the knowledge itself. In addition, new discoveries with regard to neurogenesis — the ability of the brain to generate new neurons — suggest that some areas of the brain, including the hippocampus, can birth new cells throughout a person’s lifetime. (This reverses an earlier hypothesis that neurogenesis ends after a certain age, that by adulthood we have all the brain cells we will ever possess and that they slowly die off.) In animal models, Kaufer explained, there are very specific aspects of learning that are dependent on neurogenesis, such as spatial learning and emotional memory. Newly generated neurons are recruited into existing networks, strengthening or developing preexisting connections in the brain.

Behaviors and conditions that influence plasticity and neurogenesis include sleep, nutrition, exercise, stress (cortisol levels), and happiness (dopamine levels). Kaufer explained that these exist in dynamic relation to one another. For example, voluntary exercise can counter the effects of stress. Kaufer also explained that the relationship between stress and cognition is a “classic inverted U-curve.”

Graphing of performance level (y-axis) in relation to stress level (x-axis).

That is, high levels of stress tend to correlate with low performance — but low levels of stress also correlate with low performance. A moderate amount of stress results in the highest performance. What constitutes a “moderate amount,” however, varies greatly between individuals.

Neurobiology and Active Learning

The value distinction between “active learning” and “passive learning,” long used in educational research and philosophy, also seems to have a neurobiological basis. Kaufer described a recently published study, “Hippocampal Brain-Network Coordination During Volitional Exploratory Behavior Enhances Learning” (Voss et al., Nature Neuroscience 14 (2011), 115-120), which concludes:

Our data support the notion that volitional control is an omnipresent determinant of exploratory behaviors that occurs whenever an organism is unconstrained in interactions with the environment.

Professor Kaufer translated and elaborated this conclusion for the non-specialist audience:

There is recruitment of multiple cortical areas (and cross talk with the hippocampus) that produces optimized learning with active learning process. Active learning (volitional control) is advantageous for learning because distinct neural systems related to executive functions (planning or predicting, attention and object processing) are dynamically activated and communicate with the hippocampus, to enhance its performance.

In addition to helping us understand why active learning is effective, neuroscience research seems to support the efficacy of tools like Bloom’s taxonomy (see diagram below), which describes cognitive tasks in ascending orders of complexity.

Diagram roughly mapping the cognitive verbs of Bloom's Taxonomy onto regions of the human brain.

Kaufer explained some of her own techniques for increasing active learning in the classroom, especially the large lecture classroom in which small-group discussion may not be a viable option. She is a proponent of using polling technology such as the i-clicker, a tool that allows instructors to receive real-time feedback from students on questions posed during a lecture. She uses the i-clicker in a variety of ways in her own classroom: giving short quizzes on reading material; asking a “reality check” question to make sure students are following and have grasped key information; allowing students to self-evaluate and learn from their peers as they see how others answer; doing in-class problem solving; and as a lead-in to a class activity. She also uses other techniques, such as asking students to break into discussion pairs, and prefacing class with music, which sets the tone for students and simultaneously relaxes and stimulates them.

Learning Styles and Neural Pathways

Appealing to different learning styles is also a technique that seems to be supported by the latest neurobiological research, though not in the way that is popularly understood. Kaufer described a study entitled “Influencing Brain Networks: Implications for Education” (Posner and Rothbart, Trends in Cognitive Sciences 9.3 [March 2005], 99–103), which suggested that, although there is strong evidence of brain networks common to all human beings, there are also individual differences due to genes and experiences. The article also suggested that learning seemed to be most effective when learners were “tagging” new information to old knowledge, suggesting that prior knowledge and preconceptions are particularly important for teaching and learning.

Another article on learning styles, “The Neural Correlates of Visual and Verbal Cognitive Styles” (Kraemer et al., Journal of Neuroscience 29.12 (March 25, 2009, 3792–3798), showed that individuals who identified themselves as visual or verbal learners tended to show activation of different neural pathways while performing learning tasks. In addition, researchers observed a “translation” effect: self-characterized “verbal” learners tended to show activation of verbal-related areas of the brain when performing visual tasks, and self-characterized “visual” learners tended to show activation of visual-related areas when performing verbal tasks. This suggests that appealing to multiple learning styles is useful not in order to cater to each student’s primary mode of learning, as is often assumed, but because cross-connections are created when people perform tasks in a manner different from their “preferred” cognitive style. It’s the variety of brain regions recruited through multiple neural pathways that makes learning most effective for all learners.

Applications to Teaching

Professor Kaufer concluded by reiterating some of the ways she implements these principles in the classroom, including the i-clickers, multiple ways of presenting an important point, taking a break in a long class, encouraging a variety of forms of class participation, using music, presenting questions in a context that is personally relevant to the student (for example, phrasing questions in the second person), and encouraging students to be physically active (for example, using qigong movements during a class break).