8 research outputs found
The role of historical and ecological factors on initial survival of Copaifera langsdorffii Desf. (Fabaceae)
Non-affirmative Theory of Education as a Foundation for Curriculum Studies, Didaktik and Educational Leadership
This chapter presents non-affirmative theory of education as the foundation for a new research program in education, allowing us to bridge educational leadership, curriculum studies and Didaktik. We demonstrate the strengths of this framework by analyzing literature from educational leadership and curriculum theory/didaktik. In contrast to both socialization-oriented explanations locating curriculum and leadership within existing society, and transformation-oriented models viewing education as revolutionary or super-ordinate to society, non-affirmative theory explains the relation between education and politics, economy and culture, respectively, as non-hierarchical. Here critical deliberation and discursive practices mediate between politics, culture, economy and education, driven by individual agency in historically developed cultural and societal institutions. While transformative and socialization models typically result in instrumental notions of leadership and teaching, non-affirmative education theory, previously developed within German and Nordic education, instead views leadership and teaching as relational and hermeneutic, drawing on ontological core concepts of modern education: recognition; summoning to self-activity and Bildsamkeit. Understanding educational leadership, school development and teaching then requires a comparative multi-level approach informed by discursive institutionalism and organization theory, in addition to theorizing leadership and teaching as cultural-historical and critical-hermeneutic activity. Globalisation and contemporary challenges to deliberative democracy also call for rethinking modern nation-state based theorizing of education in a cosmopolitan light. Non-affirmative education theory allows us to understand and promote recognition based democratic citizenship (political, economical and cultural) that respects cultural, ethical and epistemological variations in a globopolitan era. We hope an American-European-Asian comparative dialogue is enhanced by theorizing education with a non-affirmative approach
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Stochastic synapses enable efficient brain-inspired learning machines
Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware