63 research outputs found

    Wiedza milczฤ…ca w nauce. Koncepcja Michaela Polanyi'ego

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    tekst zamieszczony w czasopiล›mie "Zagadnienia naukoznawstwa" nr 1 (183), 2010

    Knowledge externalities and growth in peripheral regions: introductory notes

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    The aim of this paper is to discuss the idea that knowledge externalities, as discussed in the Endogenous Growth Theory, can be spread over any kind of space. Although this point has already been discussed by some scholars in the heterodox tradition (Nelson, 1998, Martin and Sunley, 1998, among others), we would like to bring into discussion a new perspective that analyses the validity of this assumption in peripheral regions/countries. It will be argued that there are some peripheral structural conditions that constrain the generation, transfer and absorption of knowledge externalities. Above of all, it will be argued that the construction of โ€œspaceโ€ in the periphery is determinant for the absence of widespread diffusion of this kind of externality. This conclusion implies that the generality of the New Growth Theory is very difficult to be assumed.

    The effect of regional differences on the performance of software firms in the Netherlands

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    In this paper, we concentrate on how evolutionary economics contributes to a better understanding of the spatial evolution of newly emerging industries. Inspired by evolutionary thinking, four types of explanations are discussed and tested in an empirical analysis of the spatial pattern of the software sector in the Netherlands. Traditionally, agglomeration economies provide an explanation for the spatial concentration of an industry. Firms located in a cluster of similar or related sectors benefit from cost reductions, due to lower transportation costs, a thick labour market, specialised suppliers and information spillovers. An evolutionary approach on agglomeration economies provides an alternative view. It focuses explicit attention on knowledge spillovers as a vehicle of local diffusion of organizational routines or competences from one firm to the other. Such transfers of (tacit) knowledge are facilitated by spatial proximity of firms and a common knowledge base. In addition, an evolutionary approach takes a dynamic perspective on the role of agglomeration economies. During the initial stage of development of a new industry, the surrounding environment is still directed to routines and competences related to existing industries. When the new industry concentrates in a particular area to a considerable degree, a supportive environment (specialized knowledge, labour with specific skills) may gradually come into being, and localization economies may arise. Other evolutionary mechanisms may also provide an explanation for the spatial formation of new industries. We distinguish another three of them. First of all, transfer of knowledge and successful routines between firms in an emerging industry may occur through spin-off dynamics. Secondly, (social) networks may function as effective channels of knowledge diffusion and interactive learning, because they can provide a common knowledge base and mutual understanding and trust. Thirdly, firms in new industries with organizational capabilities that can deal effectively with the lack of required resources (such as knowledge, skills and capital) may become dominant, due to selection and imitation. Based on cross-sectional data gathered among 265 software firms in the Netherlands in 2003, we have tested which factors have influenced the innovative productivity of these firms. Using regression techniques, the outcomes suggest that spin-offs and firms with organizational capabilities perform better, while networks relations do not seem to affect the performance of software firms. Geography matters as well: software firms located in a region with a labour market with more ICT-skills show a higher innovative productivity. Keywords: evolutionary economics, industrial location, evolution of industries, software sector, agglomeration economies, organizational capabilities, spin-off, networks

    The effect of regional differences on the performance of software firms in the Netherlands

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    In this paper, we concentrate on how evolutionary economics contributes to a better understanding of the spatial evolution of newly emerging industries. Inspired by evolutionary thinking, four types of explanations are discussed and tested in an empirical analysis of the spatial pattern of the software sector in the Netherlands. Traditionally, agglomeration economies provide an explanation for the spatial concentration of an industry. Firms located in a cluster of similar or related sectors benefit from cost reductions, due to lower transportation costs, a thick labour market, specialised suppliers and information spillovers. An evolutionary approach on agglomeration economies provides an alternative view. It focuses explicit attention on knowledge spillovers as a vehicle of local diffusion of organizational routines or competences from one firm to the other. Such transfers of (tacit) knowledge are facilitated by spatial proximity of firms and a common knowledge base. In addition, an evolutionary approach takes a dynamic perspective on the role of agglomeration economies. During the initial stage of development of a new industry, the surrounding environment is still directed to routines and competences related to existing industries. When the new industry concentrates in a particular area to a considerable degree, a supportive environment (specialized knowledge, labour with specific skills) may gradually come into being, and localization economies may arise. Other evolutionary mechanisms may also provide an explanation for the spatial formation of new industries. We distinguish another three of them. First of all, transfer of knowledge and successful routines between firms in an emerging industry may occur through spin-off dynamics. Secondly, (social) networks may function as effective channels of knowledge diffusion and interactive learning, because they can provide a common knowledge base and mutual understanding and trust. Thirdly, firms in new industries with organizational capabilities that can deal effectively with the lack of required resources (such as knowledge, skills and capital) may become dominant, due to selection and imitation. Based on cross-sectional data gathered among 265 software firms in the Netherlands in 2003, we have tested which factors have influenced the innovative productivity of these firms. Using regression techniques, the outcomes suggest that spin-offs and firms with organizational capabilities perform better, while networks relations do not seem to affect the performance of software firms. Geography matters as well: software firms located in a region with a labour market with more ICT-skills show a higher innovative productivity.Evolutionary economics, industrial location, evolution of industries, software sector, agglomeration economies, organizational capabilities, spin-off, networks

    ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹ ๊ตฌ์„ฑ ๊ณผ์ •์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ˆ˜ํ•™๊ต์œก๊ณผ, 2015. 2. ์ด๊ฒฝํ™”.๋ณธ ์—ฐ๊ตฌ๋Š” ์ˆ˜ํ•™๊ต์‚ฌ ๊ต์œก์—์„œ ๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹์˜ ์ค‘์š”์„ฑ์ด ์ ์ฐจ ๊ฐ•์กฐ๋˜๊ณ  ์žˆ์œผ๋‚˜, ์‹ค์ฒœ์  ์ง€์‹์˜ ์˜๋ฏธ์™€ ๊ตฌ์„ฑ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๋…ผ์˜๊ฐ€ ๋ถ€์กฑํ•˜๋‹ค๋Š” ๋ฌธ์ œ์˜์‹์—์„œ ์ถœ๋ฐœํ•˜์˜€๋‹ค. ํŠนํžˆ, ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹ ๊ตฌ์„ฑ์„ ์œ„ํ•œ ๊ตฌ์ฒด์ ์ธ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๋…ผ์˜๊ฐ€ ์ด๋ฃจ์–ด์ง€๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ต์‚ฌ์˜ ์‹ค์ฒœ์— ๋ฐ˜๋“œ์‹œ ์ˆ˜๋ฐ˜๋˜๋Š” ์•”๋ฌต์  ์ง€์‹์— ๋Œ€ํ•œ ๋ถ„์„์ด ์„ ํ–‰๋˜์–ด์•ผ ํ•จ์— ์ฃผ๋ชฉํ•˜์˜€๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฌธํ—Œ ๋ถ„์„์„ ํ†ตํ•ด ๊ต์‚ฌ์˜ ์‹ค์ฒœ์— ๊ด€์—ฌํ•˜๋Š” ๋‹ค์–‘ํ•œ ์ง€์‹๊ณผ ๋”๋ถˆ์–ด ์•”๋ฌต์  ์ง€์‹์˜ ์˜๋ฏธ๋ฅผ ๋ฉด๋ฐ€ํžˆ ํŒŒ์•…ํ•˜์˜€๋‹ค. ๊ต์ˆ˜ํ•™์  ๋‚ด์šฉ์ง€์‹, ์ˆ˜ํ•™์„ ๊ฐ€๋ฅด์น˜๊ธฐ ์œ„ํ•œ ์ง€์‹ ๋“ฑ ๋ถ„์ ˆ์ ์œผ๋กœ ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์ „๋ฌธ์  ์ง€์‹์— ๋Œ€ํ•ด ์ด๋ฃจ์–ด์ง„ ๊ธฐ์กด์˜ ๋…ผ์˜์—, ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์‹ค์ฒœ์„ ๋‘˜๋Ÿฌ์‹ผ ์•”๋ฌต์  ์ฐจ์›์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ๋ณด์™„ํ•จ์œผ๋กœ์จ ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹์˜ ์˜๋ฏธ๋ฅผ ๊ตฌ์ฒดํ™”ํ•˜์˜€์œผ๋ฉฐ, ์‹ค์ œ ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹ ๊ตฌ์„ฑ ๊ณผ์ •์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ณผ์ œ ์„ค๊ณ„์—์„œ๋ถ€ํ„ฐ ์ˆ˜์—… ์‹คํ–‰์— ์ด๋ฅด๋Š” ์ผ๋ จ์˜ ๊ณผ์ •์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ํด๋ผ๋‹ˆ์˜ ์ธ์‹๋ก ์— ๊ทผ๊ฑฐํ•˜์—ฌ ์•”๋ฌต์  ์ง€์‹์˜ ์˜๋ฏธ๋ฅผ ์‚ดํŽด๋ณธ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ๋จผ์ € ์•”๋ฌต์  ์ง€์‹์€ ์‚ผ์›์  ๊ตฌ์กฐ๋กœ ์ด๋ฃจ์–ด์ง€๋ฉฐ, ์ธ์‹์ž, ๋ณด์กฐ์‹, ์ดˆ์ ์‹์ด ๊ทธ ์„ธ ์š”์†Œ์ด๋‹ค. ์ธ์‹์ž๋Š” ๋ณด์กฐ์‹์˜ ์„ธ๋ชฉ๋“ค์ด ๋ฌด์—‡์ธ์ง€ ์ •ํ™•ํ•˜๊ฒŒ ์‹๋ณ„ํ•  ์ˆ˜๋Š” ์—†์ง€๋งŒ ๊ทธ๊ฒƒ๋“ค์„ ์ œ์–ดํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜, ์ธ์‹์ž๋Š” ํŠน์ •ํ•œ ๋ชฉ์ ๊ณผ ์˜๋„๋ฅผ ๊ฐ€์ง€๊ณ  ์˜์‹ํ•˜๋Š” ์ดˆ์  ๋Œ€์ƒ์— ๋ณด์กฐ์‹์˜ ์„ธ๋ชฉ๋“ค์„ ๊ด€๋ จ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ์ด ๊ณผ์ •์— ์˜ํ•˜์—ฌ ์ดˆ์ ์‹๊ณผ ๋ณด์กฐ์‹์ด ๊ต๋Œ€๋˜๋ฉด์„œ ๊ธฐ์ˆ ๊ณผ ์ง€์‹์ด ๋ฐœ๋‹ฌํ•œ๋‹ค. ์ด์™€ ๊ฐ™์€ ๊ด€์ ์— ๋น„์ถ”์–ด๋ณด๋ฉด, ๊ต์‚ฌ๋Š” ์ž์‹ ์˜ ์‹ ๋…๊ณผ ๊ฐ™์€ ์•”๋ฌต์  ์ง€์‹๊ณผ ๋ฌด์˜์‹์ ์œผ๋กœ ํ–‰ํ•˜๋Š” ๊ต์ˆ˜ ํ™œ๋™์„ ๋ฐ˜์„ฑํ•˜๊ณ  ์˜์‹ํ™”ํ•˜๊ณ , ์˜์‹์ ์œผ๋กœ ๊ต์ˆ˜ ํ–‰์œ„๋ฅผ ํ•˜๋ฉด์„œ ๋‹ค์‹œ ๋ฌด์˜์‹์ ์œผ๋กœ ํ–‰ํ•˜๊ฒŒ ๋˜๋Š” ๊ณผ์ •์„ ํ†ตํ•ด ์‹ค์ฒœ์  ์ง€์‹์„ ๊ตฌ์„ฑํ•˜๊ณ  ๋ฐœ๋‹ฌ์‹œ์ผœ๋‚˜๊ฐ„๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ์š”์ปจ๋Œ€, ๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹์€ ๋ช…์‹œ์  ์ฐจ์›๊ณผ ์•”๋ฌต์  ์ฐจ์›์ด ์กด์žฌํ•˜๋ฉฐ, ๊ต์‚ฌ๊ฐ€ ์•”๋ฌต์  ์ฐจ์›์˜ ์ž‘์šฉ์„ ์ธ์‹ํ•˜๊ณ  ์ด๋ฅผ ์„ฑ์ฐฐํ•˜๋Š” ๊ฒƒ์€ ๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹ ๊ตฌ์„ฑ ๊ณผ์ •์—์„œ ๋งค์šฐ ์ค‘์š”ํ•˜๋‹ค๋Š” ์ ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ต์‚ฌ์˜ ์‹(awareness)์€ ๊ต์‚ฌ์˜ ์ง€์‹๊ณผ ๋”๋ถˆ์–ด ์ฃผ๊ด€์ ์ธ ๊ฒฝํ—˜๊ณผ ๊ด€๋ จ์ด ์žˆ๋‹ค. ์‹ค์ œ ์ˆ˜์—… ์ƒํ™ฉ์—์„œ์˜ ๊ต์‚ฌ์˜ ์‹(awareness)์€ ๊ต์‚ฌ์˜ ์˜๋„์™€ ๋ชฉ์ ์— ๋”ฐ๋ผ ์ฃผ๊ด€์ ์ธ ๊ฒฝํ—˜์„ ํ†ตํ•ด ํ˜•์„ฑ๋œ ๊ฐ๊ฐ๊ณผ ์ƒํ™ฉ์œผ๋กœ๋ถ€ํ„ฐ์˜ ๋‹จ์„œ๊ฐ€ ๊ต์‚ฌ์˜ ์ง€์‹๊ณผ ๊ฒฐํ•ฉ๋˜์–ด ์„ธ๋ถ€์ ์ธ ์‚ฌํ•ญ๋“ค์„ ์ง€๊ฐํ•จ์œผ๋กœ์จ ๊ต์‚ฌ์˜ ํ–‰๋™์œผ๋กœ ๋“œ๋Ÿฌ๋‚˜๊ฒŒ ๋œ๋‹ค. ์ ์ ˆํ•˜๊ณ  ํ•ฉ๋ฆฌ์ ์ธ ๋ฐฉ์‹์œผ๋กœ ์ˆ˜์—…์„ ์‹คํ–‰ํ•˜๊ธฐ ์œ„ํ•ด์„œ, ๊ต์‚ฌ๋Š” ์ˆ˜์—…์—์„œ ์ค‘์š”ํ•˜๊ฒŒ ๋‹ค๋ฃจ์–ด์ ธ์•ผ ํ•  ์ธก๋ฉด๋“ค์— ์˜๋„์ ์ด๊ณ  ์˜์‹์ ์œผ๋กœ ์ฃผ์˜๋ฅผ ๊ธฐ์šธ์ด๊ณ  ์ง€์†์ ์œผ๋กœ ๊ด€์ฐฐํ•˜๋ฉด์„œ ์ˆ˜์—…์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์‚ฌ๊ฑด๋“ค์˜ ๋ฏธ๋ฌ˜ํ•œ ์ฐจ์ด๋“ค์„ ์•Œ์•„์ฐจ๋ฆฌ๊ณ  ์ด์— ์ ์ ˆํ•œ ๋Œ€์‘์„ ๊ฒฝํ—˜ํ•ด๋‚˜๊ฐ€๋ฉด์„œ ๊ทธ ์ƒํ™ฉ์— ๋Œ€ํ•œ ์‹(awareness)์„ ํ‚ค์›Œ๋‚˜๊ฐˆ ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๊ต์‚ฌ์˜ ์‹(awareness)์— ๋Œ€ํ•œ ๋…ผ์˜๋กœ๋ถ€ํ„ฐ ๋„์ถœํ•œ ์‹œ์‚ฌ์ ์€ ๊ต์‚ฌ๊ฐ€ ์ž์‹ ์˜ ๊ต์ˆ˜ ํ™œ๋™์„ ์˜์‹ํ™”ํ•จ์œผ๋กœ์จ ์ž์‹ ์˜ ํ–‰๋™ ์ด๋ฉด์— ์กด์žฌํ•˜๋Š” ์•”๋ฌต์  ์ฐจ์›์ด ์ˆ˜์—…๊ณผ ํ•™์ƒ์˜ ํ•™์Šต์— ์ค‘์š”ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๊นจ๋‹ซ๊ฒŒ ๋˜๋ฉด์„œ ์‹ค์ฒœ์  ์ง€์‹์„ ๊ตฌ์„ฑํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์‹ค์ฒœ์  ์ง€์‹์— ๋Œ€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ์™€ ์•”๋ฌต์  ์ง€์‹์— ๋Œ€ํ•œ ๋…ผ์˜๋ฅผ ํ† ๋Œ€๋กœ, ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹ ๊ตฌ์„ฑ์„ ์œ„ํ•ด์„œ๋Š” ๊ต์‚ฌ์˜ ์‹ค์ฒœ ๊ฒฝํ—˜, ์ด๋ก ์  ์ง€์‹ ๊ทธ๋ฆฌ๊ณ  ๊ต์‚ฌ์˜ ์‹(awareness)์˜ ์„ธ ์š”์†Œ๊ฐ€ ํ•„์š”ํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ต์‚ฌ์˜ ์‹(awareness)์„ ๊ฐ•ํ™”์‹œํ‚ค๊ธฐ ์œ„ํ•œ ์ „๋žต์œผ๋กœ ๊ต์‚ฌ์˜ ๋ฐ˜์„ฑ๊ณผ ์•Œ์•„์ฐจ๋ฆผ(noticing)์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์•Œ์•„์ฐจ๋ฆผ์€ ์ฒด๊ณ„์ ์ธ ๋ฐ˜์„ฑ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ต์‚ฌ์˜ ๋ฏผ๊ฐ์„ฑ์„ ํ‚ค์šธ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ๊ต์‚ฌ์˜ ์‹(awareness)์„ ๊ฐ•ํ™”์‹œํ‚ค๊ณ  ๊ฒฝํ—˜๊ณผ ๋ช…์‹œ์ ์ธ ์ง€์‹์ด ์กฐํ™”๋กญ๊ฒŒ ๊ท ํ˜•์„ ์ด๋ฃจ๋Š”๋ฐ ํšจ๊ณผ์ ์ธ ๋ฐฉ๋ฒ•์ด ๋  ์ˆ˜ ์žˆ๋‹ค. ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์‹ค์ฒœ์  ์ง€์‹ ๊ตฌ์„ฑ์„ ์œ„ํ•œ ์„ธ ์š”์†Œ์™€ ๋ฐ˜์„ฑ๊ณผ ์•Œ์•„์ฐจ๋ฆผ ์ „๋žต์„ ํ† ๋Œ€๋กœ ๊ต์‚ฌ๊ต์œก์˜ ์ ˆ์ฐจ๋ฅผ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๋‹ค์„ฏ ๋‹จ๊ณ„๋กœ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์ด๋ก ํ•™์Šต, ๊ณผ์ œ์„ค๊ณ„, ์‚ฌ๊ณ ์‹คํ—˜, ์ˆ˜์—…์‹คํ–‰, ์ˆ˜์—…์— ๋Œ€ํ•œ ๋ถ„์„์ด ๊ทธ๊ฒƒ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ค‘ํ•™๊ต ๊ต์‚ฌ๊ฐ€ ์ด ์ ˆ์ฐจ์— ๋”ฐ๋ผ ์‹ค์ฒœ์  ์ง€์‹์„ ๊ตฌ์„ฑํ•˜๋Š” ๊ณผ์ •์— ๋Œ€ํ•˜์—ฌ ์‚ดํŽด๋ณด์•˜๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ์‹ค์ฒœ์  ์ง€์‹์˜ ๊ตฌ์„ฑ ๊ณผ์ •์€ ํฌ๊ฒŒ ์ดˆ์ ์‹ํ™”์™€ ๋ณด์กฐ์‹ํ™”๋กœ ์ด๋ฃจ์–ด์ง„๋‹ค๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ดˆ์ ์‹ํ™” ๊ณผ์ •์—์„œ ๊ต์‚ฌ๋Š” ์•”๋ฌต์  ์ฐจ์›์˜ ๋ณด์กฐ์‹๋“ค์„ ์˜์‹ํ™”ํ•˜๊ณ  ๋ฐ˜์„ฑํ•จ์œผ๋กœ์จ ์‹ค์ฒœ์„ ๋ณ€ํ™”์‹œํ‚ค๋ ค๋Š” ์˜์ง€๋ฅผ ๊ฐ€์ง€๊ณ  ์˜์‹์ ์ธ ๊ต์ˆ˜ ํ™œ๋™์„ ํ•ด๊ฐ€๋ฉด์„œ ์‹ค์ฒœ์„ ๊ฐœ์„ ํ•œ๋‹ค. ์ด์–ด์„œ ๋ณด์กฐ์‹ํ™” ๊ณผ์ •์—์„œ ๋‹ค์‹œ ๋ฌด์˜์‹์ ์ธ ๊ต์ˆ˜ ํ™œ๋™์„ ํ•˜๊ฒŒ ๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•œ ๊ต์‚ฌ๋Š” ์˜์‹ํ™”์™€ ๋ฐ˜์„ฑ์— ์˜ํ•œ ์ดˆ์ ์‹ํ™” ๊ทธ๋ฆฌ๊ณ  ์ด๋ฅผ ๋‹ค์‹œ ๋ณด์กฐ์‹ํ™” ๊ณผ์ •์„ ๊ต๋Œ€๋กœ ๊ฑฐ์น˜๋ฉด์„œ ์‹ค์ฒœ์  ์ง€์‹์„ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ณ€ํ™”๋œ ๊ต์ˆ˜ ํ™œ๋™์ด ์Šต๊ด€ํ™”๋˜์–ด ์•ˆ์ •์ ์œผ๋กœ ๊ต์‚ฌ์˜ ์•”๋ฌต์  ์ฐจ์›์œผ๋กœ ์ž๋ฆฌ ์žก๊ธฐ ์œ„ํ•ด์„œ๋Š” ์žฅ์‹œ๊ฐ„์ด ํ•„์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ด์— ๋Œ€ํ•ด์„œ๋Š” ํ–ฅํ›„ ์ถ”์  ๊ด€์ฐฐ์ด ํ•„์š”ํ•  ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์•”๋ฌต์  ์ง€์‹์— ๋Œ€ํ•œ ๋ฉด๋ฐ€ํ•œ ๋ถ„์„์„ ํ†ตํ•ด ์‹ค์ฒœ์  ์ง€์‹์˜ ์˜๋ฏธ๋ฅผ ๊ตฌ์ฒด์ ์œผ๋กœ ๋ฐํžˆ๊ณ  ์ด๋ฅผ ํ† ๋Œ€๋กœ ์‹ค์ฒœ์  ์ง€์‹ ๊ตฌ์„ฑ์„ ์ง€์›ํ•˜๋Š” ์ ˆ์ฐจ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ค‘ํ•™๊ต ์ˆ˜ํ•™๊ต์‚ฌ๊ฐ€ ์ด ์ ˆ์ฐจ์— ๋”ฐ๋ผ ์‹ค์ฒœ์  ์ง€์‹์„ ๊ตฌ์„ฑํ•˜๋Š” ๊ณผ์ •์— ๋Œ€ํ•˜์—ฌ ์‚ดํŽด๋ด„์œผ๋กœ์จ ์‹ค์ฒœ์  ์ง€์‹์— ๊ด€ํ•œ ์ด๋ก ์ ์ด๊ณ  ์‹ค์ œ์ ์ธ ์ ‘๊ทผ์„ ์‹œ๋„ํ•˜์˜€๋‹ค. ์‹ค์ฒœ์  ์ง€์‹์€ ๊ทธ ํŠน์„ฑ์ด ๋‹ค๋ฉด์ ์ด๊ณ  ๋ชจํ˜ธํ•˜์—ฌ ๋‹ค๋ฃจ๋Š” ๊ฒƒ์ด ์‰ฝ์ง€ ์•Š๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ฒœ์  ์ง€์‹์€ ์ˆ˜ํ•™๊ต์‚ฌ์˜ ์ „๋ฌธ์„ฑ์„ ์ด๋ฃจ๋Š” ํ•ต์‹ฌ์ ์ธ ์š”์†Œ์ด๋ฏ€๋กœ ๋‹ค๊ฐ๋„๋กœ ์ดํ•ดํ•˜๊ณ  ๋ถ„์„ํ•˜์—ฌ ๊ทธ ํŠน์„ฑ์„ ๋ฐํžˆ๊ณ  ๊ตฌ์„ฑ ๋ฐฉ์•ˆ์„ ๋ชจ์ƒ‰ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค.CHAPTER โ… . INTRODUCTION 1 1. Background on the study 1 2. Research questions 10 3. Outline of the study 11 CHAPTER โ…ก. TACIT KNOWLEDGE 13 1. The meaning of tacit knowledge 14 2. The structure of tacit knowing and construction of knowledge 18 3. Tacit knowing and teaching 25 3.1. Tacit knowing and awareness 30 3.1.1. Awareness and noticing 32 3.1.2. Importance of mathematics teacher awareness 38 3.2. Tacit knowledge and socio-cultural environment 40 CHAPTER โ…ข. CONSTRUCTION OF MATHEMATICS TEACHERS PRACTICAL KNOWLEDGE 48 1. The concept of mathematics teachers practical knowledge and its components 48 2. Strategies for the reinforcement of mathematics teacher awareness 54 2.1. Reflection 55 2.1.1. Process of reflection 56 2.1.2. Content of reflection 58 2.2. Noticing 60 3. Teacher training procedures for the construction of mathematics teachers practical knowledge 65 3.1. Learning theory 65 3.2. Task design 67 3.3. Thought experiment 73 3.4. Conduct of class 78 3.5. Analysis of class with colleagues 79 CHAPTER โ…ฃ. THE CONDUCT OF RESEARCH 81 1. Method 82 1.1. Research participants 82 1.2. Data gathering process 84 1.3. Analysis of data 88 2. Task design on similarity of figures and teachers noticing in thought experiment 90 2.1. Purpose of task design 90 2.2. Noticing during the task design and thought experiment 92 3. Noticing and reflection in class 102 3.1. When noticing from thought experiment is reflected 103 3.1.1. Inducing understanding of similarity concept by systematically proposing examples 103 3.1.2. Recognizing the concept of similarity that exists behind diverse methods 117 3.1.3. Expansion of perspective through utilization of mathematical tool 121 3.2. A case in which the noticing from thought experiment is not well-reflected 133 3.2.1. A case in which the noticing at mathematical dimension does not lead to psychological and management of teaching dimensions 133 3.2.1.1. Unable to accurately identify the students level of understanding 133 3.2.1.2. The interaction with the students is not adequate 138 3.2.2. The case in which the previous way of teaching appears 142 3.2.2.1. Unable to provide enough opportunities to inquiry 142 3.2.2.2. The teacher asks dichotomy or short-answer questions 146 4. Noticing and reflection from class analysis 150 4.1. Recognition of the necessity to understand the students 150 4.2. Recognition of the teachers orientation 153 4.3. Teachers recognition of her purpose 156 5. Discussion 158 CHAPTER โ…ค. SUMMARY AND DISCUSSION 166Docto

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    Technological knowledge plays a role in academic writing such as assisting in finding suitable references, checking plagiarism, and publishing the article. However, technological knowledge does not always provide benefits in academic writing. Technological knowledge may affect the writersโ€™ mentality to take shortcut in finishing and checking their writing. The objectives of this study were: (1) to find out the technological knowledge level of English education study program students, (2) to find out how English education study program students applied their technological knowledge in academic writing, and (3) to find out the problems English education study program students encountered in applying their technological knowledge in academic writing. The studyโ€™s participant was 13 students from class B 2016 Palembang of English Education Undergraduate Program along with the latest lecturer that teaches them writing. This research used descriptive qualitative design. The data were collected by questionnaire, observation, interview, and document gathering. Percentage calculation, transcribing, and triangulation were used to analyze data. The findings showed that (1) The technological knowledge level of the participants is level two Technical Maxim, (2) the participants applied technological knowledge on academic particularly in finding references and structuring idea, and (3) the participants have several problems in applying technological knowledge in academic writing, such as in citing references correctly, avoiding tendency to copy-and-paste, structural error due to using automatic correction, and paper formatting

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    In the late nineteenth century, economic analysis of law experienced an outright rejection by the German-speaking legal community. In the second half of the twentieth century, it became a dominant approach in American legal inquiry. We argue that this success was partly due to the insights of Austrian economics which the second wave of law and economics has incorporated. We argue that Austrian legal and economic scholars marked the two cornerstones between which the subsequent discussion oscillated: social planning versus evolution (spontaneous order

    Wissenswertes Wissen โ€“ lehrwertes Wissens

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    Povijest znanja u uvodnom dijelu ilustrira poveฤ‡avanje znanja kao sveukupnog ljudskog iskustva koje u obrazovni sustav ulazi u oblicima znanja strukturiranoga prema znanostima i znanstvenim disciplinama. U tradicionalnom obrazovanju znanja vrijedna znanja su propozicionalna i proceduralna znanja. Njihova struktura u formalnom obrazovanju je substantivna i sintaktiฤka. Pristupi strukturama znanja usmjereni su na proลกlost, sadaลกnjost i buduฤ‡nost. Na ovim premisama autorica raspravlja o znanju vrijednom znanja u suvremenim obrazovnim promjenama: u organizaciji i reorganizaciji propozicionalnih i proceduralnih znanja, znaฤenju tacitnog znanja, znaฤenju, ciljevima obrazovanja i pristupa prema uฤeniku, uฤenju i pouฤavanju. Zakljuฤak se odnosi na znanstveni i praktiฤni prostor pedagogije i pedagoga.The introductory part of the history of knowledge explains knowledge augmentation. Knowledge is defined as common human experience that enters education systems in forms of knowledge structured according to sciences and scientific disciplines. In traditional education, knowledge worth knowing is propositional and procedural knowledge. Its structure in formal education is substantive and syntactic. Approaches to knowledge structures are focused on the past, the present, or the future. Those premises are the bases for the authorโ€™s discussion on knowledge worth knowing in the context of modern education changes and when faced with the organisation and reorganisation of propositional and procedural knowledge, the meaning of tacit knowledge, the meaning and goals of education and approach to students, as well as with learning and teaching. The conclusion refers to both scientific and practical aspect of pedagogy and pedagogues.Die Geschichte des Wissens im einfรผhrenden Teil veranschaulicht die Zunahme des Wissens als allumfassender menschlicher Erfahrung, die ihren Eingang in das Bildungssystem in Form von nach den Wissenschaften und wissenschaftlichen Disziplinen strukturirertem Wissen findet. In der traditionellen Bildung galt als wissenswert propositionelles und prozedurelles Wissen. Dessen Struktur war in der formalen Bildung substantiv und syntaktisch. Zugรคnge zu Wissensstrukturen waren auf die Vergangenheit, Gegenwart und Zukunft ausgerichtet. Die Autorin erรถrtert das wissenswerte Wissen im gegenwรคrtigen Bildungswandel unter folgenden Voraussetzungen: Organisation und Reorganisation des propositionellen und prozedurellen Wissens, Bedeutung des taziten Wissens, Bedeutung und Ziele der Bildung bzw. lernerorientierter Ansatz zum Lernen und Lehren. Die Schlussfolgerung bezieht sich aut den wissenschaftlichen und praktischen Raum der Erziehungswissenschaft und der Pรคdagogen
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