Six characteristics of effective representational systems for conceptual learning in complex domains have been identified. Such representations should: (1) integrate levels of abstraction; (2) combine globally homogeneous with locally heterogeneous representation of concepts; (3) integrate alternative perspectives of the domain; (4) support malleable manipulation of expressions; (5) possess compact procedures; and (6) have uniform procedures. The characteristics were discovered by analysing and evaluating a novel diagrammatic representation that has been invented to support students' comprehension of electricity—AVOW diagrams (Amps, Volts, (...) Ohms, Watts). A task analysis is presented that demonstrates that problem solving using a conventional algebraic approach demands more effort than AVOW diagrams. In an experiment comparing two groups of learners using the alternative approaches, the group using AVOW diagrams learned more than the group using equations and were better able to solve complex transfer problems and questions involving multiple constraints. Analysis of verbal protocols and work scratchings showed that the AVOW diagram group, in contrast to the equations group, acquired a coherently organised network of concepts, learnt effective problem solving procedures, and experienced more positive learning events. The six principles of effective representations were proposed on the basis of these findings. AVOW diagrams are Law Encoding Diagrams, a general class of representations that have been shown to support learning in other scientific domains. (shrink)

Six characteristics of effective representational systems for conceptual learning in complex domains have been identified. Such representations should: (1) integrate levels of abstraction; (2) combine globally homogeneous with locally heterogeneous representation of concepts; (3) integrate alternative perspectives of the domain; (4) support malleable manipulation of expressions; (5) possess compact procedures; and (6) have uniform procedures. The characteristics were discovered by analysing and evaluating a novel diagrammatic representation that has been invented to support students' comprehension of electricity—AVOW diagrams (Amps, Volts, (...) Ohms, Watts). A task analysis is presented that demonstrates that problem solving using a conventional algebraic approach demands more effort than AVOW diagrams. In an experiment comparing two groups of learners using the alternative approaches, the group using AVOW diagrams learned more than the group using equations and were better able to solve complex transfer problems and questions involving multiple constraints. Analysis of verbal protocols and work scratchings showed that the AVOW diagram group, in contrast to the equations group, acquired a coherently organised network of concepts, learnt effective problem solving procedures, and experienced more positive learning events. The six principles of effective representations were proposed on the basis of these findings. AVOW diagrams are Law Encoding Diagrams, a general class of representations that have been shown to support learning in other scientific domains. (shrink)

"This comprehensive volume - containing 27 chapters and contributions from six continents - presents and discusses key principles, perspectives, and practices of social learning in the context of sustainability. Social learning is explored from a range of fields challenged by sustainability including: organizational learning, environmental management and corporate social responsibility; multi-stakeholder governance; education, learning and educational psychology; multiple land-use and integrated rural development; and consumerism and critical consumer education. An entire section of the book is (...) devoted to a number of reflective case studies of people, organizations and communities using forms of social learning in moving towards sustainability. 'This book brings together a range of ideas, stories, and discussions about purposeful learning in communities aimed at creating a world that is more sustainable than the one currently in prospect....The book is designed to expand the network of conversations through which our society can confront various perspectives, discover emerging patterns, and apply learning to a variety of emotional and social contexts.' From the Foreword by Fritjof Capra, co-founder of the Center of Ecoliteracy. 'Joining what is so clear and refreshing in this book with the larger movements toward a critically democratic and activist education that is worthy of its name, is but one step in the struggle for sustainability. But it is an essential step if we are to use the insights that are included in this book.' From the Afterword by Michael Apple, author of 'Educating the ""Right"" Way: Markets, Standards, God, and Inequality'.". (shrink)

The key assumption behind evolutionary epistemology is that animals are active learners or ‘knowers’. In the present study, I updated the concept of natural learning, developed by Henry Plotkin and John Odling-Smee, by expanding it from the animal-only territory to the biosphere-as-a-whole territory. In the new interpretation of natural learning the concept of biological information, guided by Peter Corning’s concept of “control information”, becomes the ‘glue’ holding the organism–environment interactions together. The control information guides biological systems, from bacteria (...) to ecosystems, in the process of natural learning executed by the universal algorithm. This algorithm, summarized by the acronym IGPT (information-gain-process-translate) incorporates natural cognitive methods including sensing/perception, memory, communication, and decision-making. Finally, the biosphere becomes the distributed network of communicative interactions between biological systems termed the interactome. The concept of interactome is based on Gregory Bateson’s natural epistemology known as the “ecology of mind”. Mimicking Bateson’s approach, the interactome may also be designated “physiology of mind”—the principle behind regulating the biosphere homeostasis. (shrink)

Complete URL to this document: http://srsc.ulb.ac.be/axcWWW/93-Principles.html.

Environmentalists have advocated the Precautionary Principle (PP) to help guide public and private decisions about the environment. By contrast, industry and its spokesmen have opposed this. There is not one principle, but many that have been recommended for this purpose. Despite the attractiveness of a core idea in all versions of the principle—that decision-makers should take some precautionary steps to ensure that threats of serious and irreversible damage to the environment and public health do not materialize into harm—even one of (...) the most widely endorsed principles needs considerable specification and refinement before it can be used. Moreover, the PP is an approach or guide to utilizing scientific evidence in social or legal decision-making contexts. In this it does not differ in kind from other approaches to using factual information such as in the law. The law provides some models for different strategies to guide decision-making under uncertainty when factual issues cannot be resolved with certainty. These in turn can help guide the formulation of different versions of PP and help clarify some presuppositions of the principle. Once some plausible versions of PP are articulated, I suggest some applications to existing environmental problems. (shrink)

Cognitive neuroscience aims to improve our understanding of aspects of human learning and performance by combining data acquired with the new brain imaging technologies with data acquired in cognitive psychology paradigms. Both neuroscience and psychology use the philosophical assumptions underpinning the natural sciences, namely the scientific method, whereby hypotheses are proposed and tested using quantitative approaches. The relevance of 'brain science' for the classroom has proved controversial with some educators, perhaps because of distrust of the applicability of so-called 'medical (...) models' to education. Nevertheless, the brain is the main organ of learning, and so a deeper understanding of the brain would appear highly relevant to education. Modern science is revealing the crucial role of biology in every aspect of human experience and performance. This does not mean that biology determines outcomes. Rather, there is a complex interplay between biology and environments. Improved knowledge about how the brain learns should assist educators in creating optimal learning environments. Neuroscience can also identify 'biomarkers' of educational risk, and provide new methodologies to test the effects of educational interventions. (shrink)

Big data and Machine learning Techniques are reshaping the way in which food safety risk assessment is conducted. The ongoing ‘datafication’ of food safety risk assessment activities and the progressive deployment of probabilistic models in their practices requires a discussion on the advantages and disadvantages of these advances. In particular, the low level of trust in EU food safety risk assessment framework highlighted in 2019 by an EU-funded survey could be exacerbated by novel methods of analysis. The variety of (...) processed data raises unique questions regarding the interplay of multiple regulatory systems alongside food safety legislation. Provisions aiming to preserve the confidentiality of data and protect personal information are juxtaposed to norms prescribing the public disclosure of scientific information. This research is intended to provide guidance for data governance and data ownership issues that unfold from the ongoing transformation of the technical and legal domains of food safety risk assessment. Following the reconstruction of technological advances in data collection and analysis and the description of recent amendments to food safety legislation, emerging concerns are discussed in light of the individual, collective and social implications of the deployment of cutting-edge Big Data collection and analysis techniques. Then, a set of principle-based recommendations is proposed by adapting high-level principles enshrined in institutional documents about Artificial Intelligence to the realm of food safety risk assessment. The proposed set of recommendations adopts Safety, Accountability, Fairness, Explainability, Transparency as core principles (SAFETY), whereas Privacy and data protection are used as a meta-principle. (shrink)

This article presents a set of principles for knowledge modeling in knowledge organization systems in specific domains. It discusses the representational problem, comparing the abstraction mechanisms present in the theories related to representation in concept systems, taken from foundational authors of information science, computer science, and terminology approaches. Parallel to this context, several representational possibilities arise to assist the modeler in the activity of elaborating models of representation. It describes the application of theoretical and methodological principles when organizing, (...) representing, and managing navigation on learning paths in the corporate education field. As a concept proof, it exposes a conceptual model of learning paths and discusses a literature review on this subject to verify to what extent these principles are being applied. It concludes that we can consider the principles discussed in this study as relevant, since they expand the modelers’ freedom, not making him hostage to a specific model. (shrink)

Even though social engineering has gained a bad reputation, due to new possibilities in the information age, it may be time to reconsider Karl Popper’s conception of “piecemeal social engineering.” Piecemeal social engineering is not only an element within Popper’s open society. It also connects his political philosophy to his philosophy of science and his evolutionary epistemology. Furthermore, it seems to fit well into the search for implementation strategies for policies and social actions in the context of nonideal theory. Nevertheless, (...) this does not necessarily undermine the need for political ideals and first-order principles, which are inhabitants of “World 3.”. (shrink)

These essays explore the continuities and discontinuities between the Neo-Confucian thought of Ming China and early Tokugawa Japan and the "practical learning" of the 17th and 18th centuries, underlining the need for a deeper examination of the complex relationship between "traditional" and "modern" thoughts and values.

These essays explore the continuities and discontinuities between the Neo-Confucian thought of Ming China and early Tokugawa Japan and the practical learning of the 17th and 18th centuries, underlining the need for a deeper examination of the complex relationship between traditional and modern thoughts and values.

This article argues that a successful answer to Hume's problem of induction can be developed from a sub-genre of philosophy of science known as formal learning theory. One of the central concepts of formal learning theory is logical reliability: roughly, a method is logically reliable when it is assured of eventually settling on the truth for every sequence of data that is possible given what we know. I show that the principle of induction (PI) is necessary and sufficient (...) for logical reliability in what I call simple enumerative induction. This answer to Hume's problem rests on interpreting PI as a normative claim justified by a non-empirical epistemic means-ends argument. In such an argument, a rule of inference is shown by mathematical or logical proof to promote a specified epistemic end. Since the proof concerning PI and logical reliability is not based on inductive reasoning, this argument avoids the circularity that Hume argued was inherent in any attempt to justify PI. (shrink)

Study is recently re-invoked as an alternative educational formation to disrupt the learning trap and trope. This paper calibrates study and learning as two hermeneutic principles and correlates them with seeing, hearing, and observing as three onto-epistemic modes that respectively underpin Greco-Christian, Rabbinic, and ancient Chinese exegetical traditions. Linking study and learning with the hermeneutic issues of language, text, meaning, and reality, my calibration unfolds in four steps. First, I introduce an epistemic aporia encountered in interpreting (...) some Chinese educational “wind” texts, exposing our naturalized reasoning of learning along a representational enclosure. Second, turning to Susan Handelman’s writing, I trace this learning-as-representation enclosure as being conditioned upon the Greco-Christian exegetical mode of seeing, meanwhile correlating study back with the Rabbinic hearing hermeneutic. Third, I move on to explicate an onto-cosmological Yijing observing, proffering a study hermeneutic as a movement of observing, following, and attuning to wendao, literally put, “a crisscrossing pattern that turns with dao.” Finally, I re-observe and study the crisscrossing Chinese educational “wind” texts, evoking a Chinese “wind-teaching” sensibility so far rarely discerned through representational thinking and learning. (shrink)

With the emergence of systems biology the notion of organizing principles is being highlighted as a key research aim. Researchers attempt to ‘reverse engineer’ the functional organization of biological systems using methodologies from mathematics, engineering and computer science while taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-20th century. The aim of this (...) paper is to draw on this historical background in order to increase the understanding of the motivation behind the systems theoretic approach and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational and system-level properties, ii) the inherent critique of reductionism and fragmentation of knowledge resulting from overspecialization, and iii) the insight that the ideal of formulating abstract organizing principles is complementary to, rather than conflicting with, the aim of formulating detailed explanations of biological mechanisms. We argue that looking back not only helps us understand the current practice but also points to possible future directions for systems biology. (shrink)

This chapter contains section titled: Principles New Principle Learning Feng's Histories of Chinese Philosophy and New Principle Learning Problems of a Modern Confucian Rationalist.

Pothos & Busemeyer's (P&B's) query about whether quantum probability can provide a foundation for the cognitive modeling embodies so many underlying implications that the subject is far from exhausted. In this brief commentary, however, I suggest that the conceptual thresholds of the meaningful learning give rise to a typical Boltzmann's weighting measure, which indicates a statistical verisimilitude of quantum behavior in the human cognitive ensemble.

Unsupervised statistical learning is the standard setting for the development of the only advanced visual system that is both highly sophisticated and versatile, and extensively studied: that of monkeys and humans. In this extended abstract, we invoke philosophical observations, computational arguments, behavioral data and neurobiological findings to explain why computer vision researchers should care about (1) unsupervised learning, (2) statistical inference, and (3) the visual brain. We then outline a neuromorphic approach to structural primitive learning motivated by (...) these considerations, survey a range of neurobiological findings and behavioral data consistent with it, and conclude by mentioning some of the more challenging directions for future research. (shrink)