Science College July 2, 2012
“Brain - Machine - Society: Exploring LEARNING”.
You are cordially invited to take part in this year’s Science College focussing on the topic “Brain - Machine - Society: Exploring LEARNING”
Date: July 2, 2012 (all day)
The discussion beyond science borders in workshops and lectures about current scientific findings and debates should facilitate a revised understanding of LEARNING.
We offer two lectures in the morning with sufficient time for questions and discussions, followed by seven parallel workshops in the afternoon, conducted by invited experts and moderated by doctoral fellows. Experts of the academic areas of education, philosophy, neurosciences, neuroinformatics, psychology and history present issues like ‘Foundations of learning’, ‘Learning from history’, ‘Limits of learning’, ’Learning through and about technology’, ‘Neurosciences... new perspectives on learning?’, ’Machine learning’, ‘Cognitive mistakes and learning’.
The day will be rounded off by an evening lecture followed by a common dinner. There, you will meet doctoral fellows from other disciplines and you have the chance to continue your discussion with the invited speakers. You are cordially invited to take part! Download full programme.
Registration is open now. We ask you to indicate two priorities for your workshop participation.
Requirements (CP)
Your participation in the Science College will be acknowledged for the structured doctoral training programme of RURS if you attend keynote lectures, evening lecture and one of the workshops (including the presentation of the workshop results). Nevertheless we hope that you will take part in the dinner as well.
According to the doctoral training programme of RURS you should participate in the Science College at least once within your PhD but of course you are welcome to take part in the Science College as often as you like.
Keynotes
How does the brain learn and remember?
Prof. Dr. Denise Manahan-Vaughan, Department of Neurophysiology, RUB
Homepage
The presentation will address on the one hand, the basic foundations of memory in terms of the forms of memory we create and the brain regions responsible for this. On the other hand it will address current knowledge about key cellular mechanisms that underlie memory formation in the brain. Some topical issues will be dealt with, such as the influence of emotions and stress on memory and how living in a society where multitasking has become a "condicio sine qua non" influences our abilty to learn and retain memories.
How scientists make discoveries: Mistakes, errors and the unexpected
Prof. Dr. Kevin N. Dunbar, Department of Human Development and Quantitative Methodology, University of Maryland
Homepage
Over the past 30 years we have probed the cognitive and neural mechanisms of the scientific mind using three main methodologies; Video and audiotaping scientists as they think and reason at their lab meetings, conducting experiments with students reasoning about scientific phenomena, and the neuroimaging (fMRI, fNIRS) of students reasoning about Physics, Chemistry, and Biology problems. All three approaches converge on strategies that expert scientists use to interpret and sometimes inhibit findings that are inconsistent with their hypotheses. These unexpected findings play a crucial role in scientific discoveries that are at the core of revolutionary science. Using examples from our three different approaches I provide a model of science that combines neural and behavioral cognitive mechanisms that underlie the ways that contemporary scientists think and reason. Put another way, Pasteur said that "Chance favors the prepared mind" however he did not say what he meant by the prepared mind. Here, we elucidate many of the strategies that are at the core of the prepared mind and are at the core of contemporary science.
Workshops
Workshop 1
Learning as self regulated process
Prof. Dr. Joachim Wirth, Department of Learning and Instruction, RUB
Homepage
Topics addressed:
What does self-regulation mean? What are the features of self-regulated learning in comparison with other learning styles? Which competencies are fundamental for self-regulation in learning? How does self-regulation work, how is it 'regulated'? How can the capacity for self-regulated learning be acquired? Is self-regulated learning possible across lifespan? Is there empirical basis for different learning styles? What do those findings mean for educational concepts? What do they mean concerning our understanding of learning?
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Workshop 2
Concept aquisition and the problem of induction
Prof. Dr. Markus Werning, Chair of Philosophy of Language and Cognition, RUB
Homepage
Topics addressed:
Induction and deduction in learning. How do we acquire general knowledge? What is the fundamental basis for the acquisition of concepts? Do we need concepts?
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Workshop 3
Learning in history!?
Prof. Dr. Wolfgang Hasberg, Historical Institute, Didactics of History, U Köln
Homepage
Topics addressed:
How does learning happen in history? How is learning regulated in history? What are the foundations for learning in history? What are limitations, challenges in learning? How do educational concepts support a specific learning attitude/learning activity/success in learning? Can societies learn?
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Workshop 4
Advances in the modeling of biological learning
Prof. Dr. Sen Cheng, Mercator Research Group ‚Structure of Memory’, RUB
Homepage
Topics addressed:
What different types of biological learning can/ have to be distinguished?
How can we model biological learning?
Why is modeling important/ interesting?
What have we learned from modeling? What do we hope to accomplish in
the future? What role does modeling play in the natural sciences?
How can modeling contribute to disciplines in other scientific areas?
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Workshop 5
What does learning mean for machines?
Prof. Dr. Tobias Glasmachers, Department of Neuroinformatics RUB
Homepage
Topics addressed:
The goal of the workshop is to understand principles of machine learning, and to elaborate their parallels with and differences from human thinking and learning. The core questions will be whether and how machine learning encompasses the human brain, understood as a learning algorithm, and if such a consideration is actually
meaningful. The following topics will guide us:
- How do machines learn from data? What is a learning machine? The no-free-lunch theorem and theoretically optimal learners. Bayesian learning: prior + data.
- What does an algorithm "understand"? Interpolation or intelligence? How to know what is important? How to generalize knowledge?
- Does statistical learning theory encompass human thinking? What are the principal differences between artificial and human learners? Can/should we judge human learning with statistical learning theory? Does machine learning cover the human brain's "learning algorithm"? Is statistical machine learning the "right" framework towards artificial intelligence?
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Workshop 6
Learning under stress
Prof. Dr. Oliver T. Wolf, Department of Cognitive Psychology, RUB
Homepage
Topics addressed:
How does stress affect learning? Does stress enhance or impair learning?
What are the neurobiological (or neuroscientific) foundations of those effects?
What are promising strategies in dealing with stress and its effect on learning?
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Workshop 7
Analogy and Causal Thinking as the Engines of Human Learning
Prof. Dr. Kevin N. Dunbar, Department of Human Development and Quantitative Methodology, U of Maryland
Homepage
Topics addressed:
Analogy and causal thinking are often proposed as key mechanisms of discovery in science. However, the underlying ways that people construct analogies and causal models has been mysterious. We have investigated the ways that analogical and causal reasoning are used in both real-world and experimental contexts. This work provides more detailed mechanisms of the ways that analogical and causal reasoning are invoked in the brain. Most importantly, we have been able to discover the time course of activation of specific regions in the brain allowing us to answer crucial questions about the nature of causality and analogy.
Evening Talk
Limits and Resources of the Brain in Learning
Prof. Dr. Niels Birbaumer, Institute of Medical Psychology and Behavioral Neurobiology U Tübingen
Homepage
Topics addressed:
Most brain systems in the human brain change their activity during and after learning more or less permanently. Several different mechanisms behind neuroplastic changes reflect the various types of learning and memory: explicit (conscious) and implicit classical and instrumental conditioning, motor skill acquisition and others. Less known are the consequences of those learning processes modifying directly brain activities which underly behavior: Direct voluntary and involuntary self-regulation of specific brain systems and reward-dependent changes in cellular activities permanently affect the neural actions and the associated behavior. In clinical research these self-regulatory procedures based on the well-known rules of operant conditioning are often described as neurofeedback or brain-machine-interfaces (BMI). Three clinical examples of the powerful effects of direct brain learning will be demonstrated: learning of communication in the completely paralyzed, learned restoration of movements in severe chronic stroke and self-regulation of circumscribed emotional brain circuits responsible for psychological disorders such as psychopathy, schizophrenia and addictions. The lasting self-modification of brain systems follows the well known rules of instrumental skill learning and thus can be applied to animals, healthy people and severely handicapped patients alike independent of their cognitive status, age, sex and genetic or educational biographies.
N.B. is supported by the Deutsche Forschungsgemeinschaft (DFG), the Bundesministerium für Bildung (BMBF), Bernstein Netzwerk für Computational Neuroscience und der European Union (ERC).
Programme
Programme
9.00 – 9.30 am
Registration and Coffee
9.30 – 9.45 am
Welcome
Prof. Dr. Nils Metzler-Nolte,
Speaker Research School
Moderation: Prof. Dr. Sen Cheng,
Mercator Research Group ‚Structure of Memory’
9.45-12.15 am
Keynote Lectures
How does the brain learn and remember?
Prof. Dr. Denise Manahan-Vaughan, Department of Neurophysiology, RUB
How scientists make discoveries: Mistakes, errors and the unexpected
Prof. Dr. Kevin N. Dunbar, Depart-ment of Human Development and Quantitative Methodology, U of Maryland
12.30 - 1.30 pm
Lunch
1.30 – 4.30 pm
Parallel Workshops
1. Learning as self regulated process
Prof. Dr. Joachim Wirth, Department of Learning and Instruction, RUB
2. Concept aquisition and the problem of induction
Prof. Dr. Markus Werning, Chair of Philosophy of Language and Cognition, RUB
3. Learning in history!?
Prof. Dr. Wolfgang Hasberg, Historical Institute, Didactics of History, U Köln
4. Advances in the modeling of biological learning
Prof. Dr. Sen Cheng, Mercator Research Group ‚Structure of Memory’, RUB
5. What does learning mean for machines?
Prof. Dr. Tobias Glasmachers, Department of Neuroinformatics, RUB
6. Learning under stress
Prof. Dr. Oliver T. Wolf, Department of Cognitive Psychology, RUB
7. Analogy and causal thinking as the engines of human learning
Prof. Dr. Kevin N. Dunbar, Department of Human Development and Quantitative Methodology, U of Maryland
4.30 – 5.15 pm
Presentation of the results of the Workshops
5.30 – 7.00 pm
Evening Talk
Limits and resources of the brain in learning
Prof. Dr. Niels Birbaumer, Institute of Medical Psychology and Behavioral Neurobiology, U Tübingen
From 7.00 pm
Dinner
Childcare
Additional child care during Science College
In case you will need surplus hours of childcare in addition to the regular childcare hours for your full participation of the Science College, you will be refunded from Research School. Please find the receipt/ “Quittung” here. We kindly ask you to hand it in (important: signed by the nanny) during the office hours of Maria Sprung.
Do you miss an interdisciplinary event (Science College) during your Research School membership? Click here for more information.
