• Title/Summary/Keyword: Aesop's Fables

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Effects of Storytelling Based Software Education on Computational Thinking (Storytelling기반 SW교육이 Computational Thinking에 미치는 영향)

  • Park, Jungho
    • Journal of The Korean Association of Information Education
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    • v.19 no.1
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    • pp.57-68
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    • 2015
  • Since the entering SW-centered society in which people make the best use of SW in order to express their own personal ideas or to solve problems, the significance of SW education has been emphasized. It is generally known that storytelling provides motivational and contextual environments. This study conducted an experimental research to find out how Aesop's fables-applied SW educational program would influence computational thinking. Of these students who had participated in an SW educational camp on every Saturday for a total of 6 weeks, the experimental group learned on basic concepts of Scratch programming as working on Aesop's fables and they were led to diverse SW activities such as stories, games, simulations arts, and others. After that, the study carried out a comparison research in relation to the groups' SW concepts, SW implementation and attitudes toward SW education. The result shows that the experimental group came up with higher levels of SW concepts, implementation and positive attitude toward SW education.

Generation of Natural Referring Expressions by Syntactic Information and Cost-based Centering Model (구문 정보와 비용기반 중심화 이론에 기반한 자연스러운 지시어 생성)

  • Roh Ji-Eun;Lee Jong-Hyeok
    • Journal of KIISE:Software and Applications
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    • v.31 no.12
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    • pp.1649-1659
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    • 2004
  • Text Generation is a process of generating comprehensible texts in human languages from some underlying non-linguistic representation of information. Among several sub-processes for text generation to generate coherent texts, this paper concerns referring expression generation which produces different types of expressions to refer to previously-mentioned things in a discourse. Specifically, we focus on pronominalization by zero pronouns which frequently occur in Korean. To build a generation model of referring expressions for Korean, several features are identified based on grammatical information and cost-based centering model, which are applied to various machine learning techniques. We demonstrate that our proposed features are well defined to explain pronominalization, especially pronominalization by zero pronouns in Korean, through 95 texts from three genres - Descriptive texts, News, and Short Aesop's Fables. We also show that our model significantly outperforms previous ones with a 99.9% confidence level by a T-test.