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Christian Holmboe 《Computer Science Education》2013,23(4):277-296
The paper uses Ludwig Wittgenstein's theories about the relationship between thought, language, and objects of the world to explore the assumption that OO-thinking resembles natural thinking. The paper imports from research in linguistic philosophy to computer science education research. I show how UML class diagrams (i.e., an artificial context-free language) correspond to the logically perfect languages described in Tractatus Logico-Philosophicus. In Philosophical Investigations Wittgenstein disputes his previous theories by showing that natural languages are not constructed by rules of mathematical logic, but are language games where the meaning of a word is constructed through its use in social contexts. Contradicting the claim that OO-thinking is easy to learn because of its similarity to natural thinking, I claim that OO-thinking is difficult to learn because of its differences from natural thinking. The nature of these differences is not currently well known or appreciated. I suggest how explicit attention to the nature and implications of different language games may improve the teaching and learning of OO-modeling as well as programming. 相似文献
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We analyze the impact of exercising sports during childhood and adolescence on educational attainment. The theoretical framework is based on models of allocation of time and educational productivity. Using the rich information from the German Socio-Economic Panel (GSOEP), we apply generalized ordered probit models to estimate the effect of participation in sport activities on secondary school degrees and professional degrees. Even after controlling for important variables and selection into sport, we find strong evidence that the effect of sport on educational attainment is statistically significant and positive. 相似文献
65.
Elke Achtert Christian B?hm Peer Kr?ger Peter Kunath Alexey Pryakhin Matthias Renz 《Informatik - Forschung und Entwicklung》2007,15(3):179-195
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest
neighbors of which include a specified query object, has received increasing attention recently. Many
industrial and scientific applications call for solutions of the RkNN problem in arbitrary metric spaces
where the data objects are not Euclidean and only a metric distance function is given for specifying
object similarity. Usually, these applications need a solution for the generalized problem where the
value of k is not known in advance and may change from query to query. In addition, many applications
require a fast approximate answer of RkNN-queries. For these scenarios, it is important to generate
a fast answer with high recall. In this paper, we propose the first approach for efficient approximative
RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our approach
uses the advantages of existing metric index structures but proposes to use an approximation of the
nearest-neighbor-distances in order to prune the search space. We show that our method scales significantly
better than existing non-approximative approaches while producing an approximation of the true query
result with a high recall. 相似文献
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The effects of query structures and query expansion (QE) on retrieval performance were tested with a best match retrieval system (InQuery1). Query structure means the use of operators to express the relations between search keys. Six different structures were tested, representing strong structures (e.g., queries with facets or concepts identified) and weak structures (no concepts identified, a query is a bag of search keys). QE was based on concepts, which were first selected from a searching thesaurus, and then expanded by semantic relationships given in the thesaurus. The expansion levels were (a) no expansion, (b) a synonym expansion, (c) a narrower concept expansion, (d) an associative concept expansion, and (e) a cumulative expansion of all other expansions. With weak structures and Boolean structured queries, QE was not very effective. The best performance was achieved with a combination of a facet structure, where search keys within a facet were treated as instances of one search key (the SYN operator), and the largest expansion. 相似文献
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