By Daniel Kane, 858-534-3262, firstname.lastname@example.org
San Diego, CA, January 12, 2007 -- Professors, researchers, teachers and students looking to build a science of how time and timing affect learning met in San Diego this week for an “all hands meeting.” The recently established Temporal Dynamics of Learning Center (TDLC) is based at UC San Diego and funded primarily by the National Science Foundation. A multidisciplinary and multi-institution group of TDLC members met for three days of brainstorming, sharing scientific expertise, building community, meeting new colleagues and strengthening established research collaborations.
The TDLC mission is to develop a science of learning that treats time and timing as a crucial element across a wide range of scales. Understanding how the brain learns, from the perspective of time, will help to clarify how students learn in the classroom and is expected to lead to science-based improvements in teaching practices.
When you learn new facts, interact with colleagues and teachers, experiment with new gadgets, or engage in countless other learning activities, timing plays a role in the functioning of your neurons, in the communication between and within sensory systems, and in the interactions between different regions of your brain. The success or failure of attempts to communicate using gestures, expressions and verbal language also depends on timing.
The three-day meeting included presentations of recent work, more specialized breakout sessions, and reflections on how the collaboration itself will work.
TDLC is built around four networks of scientists, and each network focuses on time and learning at a different level. These networks will also interact with each other, with “bridge members” facilitating these interactions. In addition, members of all the networks will address a series of big-picture questions such as: What general principles explain the dynamics of learning across multiple scales and domains?
“As scientists, we are all used to competing with one another. In the scientific literature, this has led to what I call ‘the blind man and the elephant problem.’ Everyone has their own view of research topics. For example, some say visual expertise is like a rope, others say it’s like a tree trunk, a fan or a spear. With our cooperative research model, we get to see the whole elephant,” said Garrison Cottrell, the Principal Investigator for TDLC and a Computer Science and Engineering professor from UCSD’s Jacobs School of Engineering.
By taking a collaborative look at the whole elephant – or perhaps an entire herd of elephants – the members of TDLC plan to develop a new science of learning that integrates the study of the dynamics of learning across multiple time scales, brain systems, individuals, and social systems; and change educational practice based on sound science. In order to address such a huge task, they have developed a novel center organization, which they call the “network of networks” structure. The idea is to maintain groups of researchers that are small enough to closely interact, while having enough disciplines represented to be able to address the problems from multiple perspectives.
“We are creating a culture where technique is at the service of ideas, rather than the other way around,” said Andrea Chiba, TDLC’s scientific director and a professor of Cognitive Science and Neuroscience at UCSD.
The four interacting networks are:
* Sensory Motor Learning Network: led by Dan Feldman, professor of Biology and Neuroscience at UCSD.
* Interacting Memory Systems Network: led by Andrea Chiba, professor of Cognitive Science and Neuroscience at UCSD.
* Perceptual Expertise Network: led by Isabel Gauthier and Tom Palmeri, professors of Psychology at Vanderbilt University.
* Social Interaction Network : led by Javier Movellan, director of the Machine Perception Lab at UCSD’s Institute for Neural Computation, located at Calit2 on the La Jolla campus.
“By interacting at the network level with people who are interested in similar conceptual questions and who use highly related techniques, there can be a lot of transfer of information about how to do practical experiments,” said Feldman. “By working with members of other networks, we also have the opportunity to interact with people who use fundamentally different approaches to study similar questions.”
The collaborative network-of-networks structure was inspired by an interdisciplinary, multi-institution research group called the Perceptual Expertise Network (PEN) which Cottrell, Gauthier and others helped to create five years ago.
“Creating the PEN network changed the way we do science. We have had so many productive ideas that would have gone nowhere if we each had been in our own little restricted worlds,” said Gauthier.
“Being in PEN changed my life,” Cottrell quipped. “As I was building my models, it was invaluable to have instant access to all the data people in the network were generating.”
Students and post doctoral researchers are a crucial part of this idea-generating community and are expected to play a large role in TDLC.
“We don’t want the students to miss the excitement. We are creating a community of the people actually doing the research,” said Gauthier.