Understanding Science Through Knowledge Organizers--论文代写范文精选

在上世纪初,一群科学哲学家,俗称逻辑法学派,构建科学的语法。在当前的知识氛围下，逻辑实证主义或多或少被认为是罪恶的。一个主要原因是基于实证主义的认识论,科学理论是建立在观察和逻辑连接的语言。

Abstract 
We propose, in this paper, a teaching program based on a grammar of scientific language borrowed mostly from the area of knowledge representation in computer science and logic. The paper introduces an operationizable framework for understanding knowledge using knowledge representation (KR) methodology. We start with organizing concepts based on their cognitive function, followed by assigning valid and authentic semantic relations to the concepts. We propose that in science education, students can understand better if they organize their knowledge using the KR principles. The process, we claim, can help them to align their conceptual framework with that of experts’ conceptual framework which we assume is the goal of science education.

Introduction 
At the turn of the last century a group of philosophers of science, popularly known as logical positivists, began to build the grammar of science. In the current intellectual atmosphere logical positivism is more or less considered a sin. One main reason for that being the epistemological ground of positivism, that scientific theories are grounded and logically connected in observational language, was more or less convincingly demonstrated to be incorrect. In the process the baby was thrown with the bath water. What we are trying to do here is to propose a way to fetch what was lost in that bath water, the grammar of scientific language. It is justified to believe that science, unlike folk-lore or common sense, is more rigidly organized body of knowledge. Exact sciences like mathematics and physics tend to be very economical in the number of concepts used to describe the phenomena and the connectors, to express the possible relations, between the concepts. 

It is the objective of science to eliminate ambiguity and use concepts as precisely as possible. Scientists do this by 1 creating an artificial language of their own, a constrained ‘natural’ language. This constrained natural language is a very small sub-set of any natural language in which science is communicated. Since communication of science is often done in a natural language (most commonly in English) we fail to explicitly realize that the grammar of this scientific language is distinct from those of natural languages. Consequently when we teach science we fail to communicate its grammar. We think that the practice of science teaching also suffers due to a lack of explicit teaching program to introduce the grammar of science. 

With this assumption in mind we began exploring to create a teaching program based on a grammar of scientific language borrowed mostly from the area of knowledge representation in computer science and logic. What we present here are some preliminary results. In one preliminary study we found that students encounter about 4000 concepts of biology (excluding the names of all the species of plants and animals) up to higher secondary level of education (equivalent to K12) in a typical Indian school[20]. Complexity of biological science is well known, and describing such a phenomena obviously requires a richer language. Added to this is the fact that most of biological terms are derivatives of Latin or Greek. When confronted with such a large and ‘remote’ vocabulary, biology teachers often explain the etymology and explain the formation rules of such terms explaining in terms of suffix and prefix derivatives. Another very interesting recourse that biology teachers take is the abundant use of diagrams. This does help to a large extent. Carefully illustrated diagrams communicate the precision required in science, sometimes more successfully than written words. Apart from these normally followed methods, we think, it is important to add to it an explicit teaching of the grammar of scientific knowledge. This approach, in addition to enhancing precision in science communication, will also help in improving conceptual understanding of the subject.

Methodology 
In the methodology adopted by us, we have followed the KR approach to organize biological knowledge and create a knowledge base. The steps followed are: to organize concepts on the basis of their cognitive function; to assign valid and authentic semantic relations to the concepts; to analyze the knowledge-base based on the usage of different kinds of semantic relations applied; to compare the novice’s knowledge structure with that of an experts knowledge structure; to restructure (reorganize) to align the novice’s knowledge structure with the experts knowledge structure; and fi- nally to develop a minimal set of relation types (knowledge organizers) for representing the entire domain of biology. 

Graphical representation such as concept maps, concept graphs can be generated based on the knowledge base. We would like to point out that at this stage, we have managed to fulfill the first two objectives which are presented in this article and the latter ones are part of our ongoing research project[11]. Organizing concepts on the basis of their cognitive function Knowledge organizers consists of (1) concepts (ObjectTypes) and the types of concepts (MetaTypes) used in knowledge (2) types of relations used to relate the concepts (RelationTypes) and (3) logical connectors and quanti- fiers used to express the knowledge. We start with organizing the body of knowledge into concepts and relations (monadic predicates as attributes, and dyadic predicates as relations). The type of concepts are organized in the MetaType layer. The type concepts (general) are organized in the Type layer and the instances (specific) are organized in the Token layer.

Drawing concept map following the principled/logical approach 

A principled or a logical approach is based on the grammar of scientific knowledge. We can draw principled or logical based concept maps (using the KR approach) which are different from the concept maps influenced by Novak. Figure 4, shows a principled concept map on organic molecules generated from our knowledge base. The concept map depict the minimal set of knowledge organizers i.e. relation types for representing the biomolecules. It is possible to represent some of the knowledge about organic molecules with using just two relation types i.e. semantic relations (knowledge organizers) as depicted in the figure. We intend to develop a set of such knowl- 12 edge organizers for each domain which can be applied in science education. In the domain of KO, various tools exists such as Cyc[12], UMLS[16] etc. which have been built using the logical approach. The principled concept map is very close to the way an expert tries to represent scientific knowledge in terms of unambiguous relations. Parsimony is maintained in the representation of scientific knowledge and the relations used are clear and precise which helps for a better understanding of scientific knowledge after teaching normal concept maps. We propose that if we teach the students to draw concept maps using this principled/logical or KR approach, then restructuring of knowledge can occur in a novice which helps in transforming a novice into an expert, which is the goal of science education. However, for each domain of science an acceptable grammar of science among the practitioners should be arrived after careful discussions. 

Conclusion 
The study is regarding characterizing and organizing knowledge based on KR using the grammar of scientific knowledge. We introduce the model for representing a small domain of biology. The purpose of this communication is limited to share the approach and assumptions followed. Our methodology sought to classify and organize a small domain of biological knowledge and arrive at a minimal set of knowledge organizers for representing the structural relations in the biological domain. Using these knowledge organizers, we can eliminate ambiguity, maintain parsimony and apply precision to the scientific body of knowledge. At present, we are working on building a process ontology inorder to represent the processes (events), states or stages and cycles of the biological sciences. We propose that if the students (novices) are trained to characterize and organize knowledge using KR principles i.e. following the grammar of scientific language, then their conceptual framework can be aligned with that of experts’ conceptual framework. We think that the principled approach, in place of standard concept mapping, has a direct role to play in science education.（essay代写)

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