22 research outputs found

    ๋ฌผ๋ถ€์กฑ ํ•ด์†Œ๋ฅผ ์œ„ํ•œ ์ˆ˜์ž์› ๊ด€๋ฆฌ๋ฐฉ์•ˆ ์—ฐ๊ตฌ(A study on the management method for resolving water stress)

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    ๋…ธํŠธ : ์ด ์—ฐ๊ตฌ๋ณด๊ณ ์„œ์˜ ๋‚ด์šฉ์€ ๊ตญํ† ์—ฐ๊ตฌ์›์˜ ์ž์ฒด ์—ฐ๊ตฌ๋ฌผ๋กœ์„œ ์ •๋ถ€์˜ ์ •์ฑ…์ด๋‚˜ ๊ฒฌํ•ด์™€๋Š” ์ƒ๊ด€์—†์Šต๋‹ˆ๋‹ค

    ๊ฐ์ฒด์ง€ํ–ฅ ์ •๋ณด์ €์žฅ์†Œ์—์„œ์˜ ํ™•์žฅ๋œ XLink ์‹œ๋งจํ‹ฑ์Šค ์„ค๊ณ„์™€ ๊ตฌํ˜„

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2002.Maste

    ์ฝœ๋ฆฌ์ง€์™€ ์›Œ์ฆˆ์›Œ์Šค์˜ ๋Œ€ํ™”์‹œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜์–ด์˜๋ฌธํ•™๊ณผ ๋ฌธํ•™์ „๊ณต,2007.Maste

    The change in modeling ability of science gifted students through model-based instruction

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณผํ•™๊ต์œก๊ณผ, 2015. 2. ์ตœ์Šน์–ธ.๋†’์€ ์ˆ˜์ค€์˜ ๊ณผํ•™์  ์‚ฌ๊ณ  ๋Šฅ๋ ฅ์„ ๊ธฐ๋ฅด๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ณผํ•™ ๊ฐœ๋… ํ•™์Šต ๋ฟ ๋งŒ ์•„๋‹ˆ๋ผ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ(modeling ability)์„ ๊ธฐ๋ฅด๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ํ•™์ƒ์ด ๋ชจํ˜• ๊ตฌ์„ฑ ๊ณผ์ •์— ์ง์ ‘ ์ฐธ์—ฌํ•˜๋Š” ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์ด ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ์ค„ ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€๋˜๊ณ  ์žˆ์ง€๋งŒ, ์‹ค์ œ๋กœ ์ด๋Ÿฌํ•œ ์ˆ˜์—…์„ ํ†ตํ•ด ํ•™์ƒ๋“ค์˜ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์ด ํ–ฅ์ƒํ•˜๋Š”์ง€๋Š” ํ™•์ธํ•ด๋ณผ ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์ด์— ๋”ฐ๋ผ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์„ ๊ฒฝํ—˜ํ•˜๊ธฐ ์ „๊ณผ ํ›„์— ํ•™์ƒ์˜ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์˜ ๋ณ€ํ™”๋ฅผ ์‚ดํŽด๋ณด๊ณ  ๋ณ€ํ™” ์œ ํ˜•๋ณ„ ํŠน์ง•์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด, ์ค‘ํ•™๊ต ๊ณผํ•™ ์˜์žฌ ํ•™์ƒ์„ ๋Œ€์ƒ์œผ๋กœ ์ฒœ๋ฌธํ•™ ๋‚ด์šฉ๊ณผ ๊ด€๋ จํ•˜์—ฌ ๊ณผํ•™์  ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์„ ์‹ค์‹œํ•˜๊ณ , ์‚ฌ์ „๊ณผ ์‚ฌํ›„์— ๊ฐ๊ฐ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ ๊ฒ€์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์˜ ๋ณ€ํ™”๋Š” ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹(metamodeling knowledge)๊ณผ ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰(modeling practice)์˜ ๋‘ ๊ฐ€์ง€ ์ธก๋ฉด์œผ๋กœ ๋‚˜๋ˆ„์–ด ๋ถ„์„ํ•˜์˜€๋‹ค. Chittleborough et al. (2005)์˜ VOMMS์™€ Beak et al. (2011)์˜ ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰ ์ง€ํ•„ํ‰๊ฐ€๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ฒ€์‚ฌ ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜์˜€์œผ๋ฉฐ ํŒŒ์ผ๋Ÿฟ ๊ฒ€์‚ฌ๋ฅผ ํ†ตํ•ด ์ˆ˜์ •, ์ ์šฉํ•˜์˜€๋‹ค. ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์˜ ๋ณ€ํ™”๋Š”, ๋” ๋†’์€ ์ˆ˜์ค€์˜ ์ดํ•ด๋ฅผ ์„ ํƒํ•œ ํ•™์ƒ์˜ ๋น„์œจ์„ ๋น„๊ตํ•˜์—ฌ ์–‘์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๊ณ  ์„ ํƒ ์‚ฌ์œ ์„œ์™€ ์ธํ„ฐ๋ทฐ๋ฅผ ํ†ตํ•ด ์งˆ์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์˜ ๋ณ€ํ™”๋Š”, ๋ชจํ˜• ๊ตฌ์„ฑ, ๋ชจํ˜• ํ‰๊ฐ€, ๋ชจํ˜• ์ ์šฉ์˜ ์„ธ ๊ฐ€์ง€ ์˜์—ญ์œผ๋กœ ๋‚˜๋ˆ„์–ด ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ, ๊ฐ ์˜์—ญ๋ณ„ ํ‰๊ฐ€ ๋„๊ตฌ์™€ ์ฑ„์  ๊ธฐ์ค€์€ ๋ฌธํ—Œ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๊ฐ ์˜์—ญ์˜ ์ˆ˜์ค€์€ ์„ธ ๋‹จ๊ณ„๋กœ ๋ถ„๋ฅ˜ ๋˜์—ˆ์œผ๋ฉฐ, ๋Œ€์‘ํ‘œ๋ณธ t-๊ฒ€์ •์„ ํ†ตํ•ด ์‹คํ–‰์˜ ๋ณ€ํ™”๋ฅผ ์–‘์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋ณ€ํ™” ์œ ํ˜•์— ๋”ฐ๋ผ ๋„ค ๊ฐ€์ง€ ์‚ฌ๋ก€๋ฅผ ์„ ํƒํ•˜์—ฌ ํ™œ๋™์ง€, ์‚ฌ์ „ยท์‚ฌํ›„ ๊ฒ€์‚ฌ์ง€, ์ธํ„ฐ๋ทฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์‚ฌ๋ก€๋ณ„ ๋ณ€ํ™”์˜ ํŠน์ง•์„ ์งˆ์ ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์— ๊ด€ํ•˜์—ฌ ๋งŽ์€ ํ•™์ƒ๋“ค์ด ์ˆ˜์—… ํ›„ ๋” ์ง„๋ณด๋œ ๊ด€์ ์œผ๋กœ ๊ณผํ•™์  ๋ชจํ˜•๊ณผ ๋ชจํ˜• ๊ตฌ์„ฑ์„ ์ดํ•ดํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ๊ทธ ๋ณ€ํ™”์˜ ๋ชจ์Šต์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๊ทœ๋ชจ ๋ชจํ˜•์— ๊ตญํ•œ๋œ ์ƒ์‹์ ์ธ ์ƒ๊ฐ์—์„œ ๋ฒ—์–ด๋‚˜ ๋งŽ์€ ํ•™์ƒ๋“ค์ด ํ‘œ์ƒ์œผ๋กœ์จ์˜ ๋ชจํ˜•(models as a representations)์„ ์ดํ•ดํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋‘˜์งธ, ๋ชจํ˜•์€ ์œ ์ผํ•˜๋‹ค๋Š” ์ƒ๊ฐ์—์„œ ๋ฒ—์–ด๋‚˜ ํ•™์ƒ ์ „์›์ด ๋ชจํ˜•์˜ ๋‹ค์–‘์„ฑ(the multiplicity of models)์„ ์ดํ•ดํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์…‹์งธ, ์†Œ๋ฐ•ํ•œ ์‹ค์žฌ๋ก ์—์„œ ๋ฒ—์–ด๋‚˜ ๋งŽ์€ ํ•™์ƒ๋“ค์ด ๋ชจํ˜•์˜ ์—ญ๋™์  ๋ณธ์„ฑ(the dynamic nature of models)์„ ์ดํ•ดํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์„ ํ•™์Šต ๋ชฉํ‘œ๋กœ ์‚ผ์ง€ ์•Š์•˜์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์ด๋Ÿฌํ•œ ๊ธ์ •์  ๋ณ€ํ™”๊ฐ€ ์ผ์–ด๋‚  ์ˆ˜ ์žˆ์—ˆ๋˜ ์ด์œ ๋Š”, ์ˆ˜์—… ๋„์ž…๋ถ€์— ์‹ค์‹œํ•œ ์ˆ˜์—… ์ค€๋น„ ์šด๋™์˜ ํšจ๊ณผ๊ฐ€ ์ปธ๋˜ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•™์ƒ๋“ค์€ ์ด๋ฅผ ํ†ตํ•ด ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์„ ์–ป๊ฒŒ ๋˜๊ณ , ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์— ์ž์‹ ๊ฐ ์žˆ๊ฒŒ ์ž„ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜์—ˆ๋‹ค๊ณ  ์‘๋‹ตํ•˜์˜€๋‹ค. ์ด๊ฒƒ์€ ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์„ ๋ช…์‹œ์ ์œผ๋กœ ์ œ์‹œํ•˜๋Š” ๊ฒƒ์ด ํ•™์ƒ์—๊ฒŒ ๊ณผ๋„ํ•œ ๋ถ€๋‹ด ๋‚ด์ง€ ๋˜ ํ•˜๋‚˜์˜ ๋ฐฐ์šธ ๊ฑฐ๋ฆฌ๊ฐ€ ๋  ๊ฒƒ์ด๋ผ๋Š” ๊ธฐ์กด์ด ์šฐ๋ ค์™€๋Š” ๋‹ฌ๋ฆฌ ์ˆ˜์—… ์ค€๋น„ ์šด๋™์ด ํ•™์ƒ๋“ค์—๊ฒŒ ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ์ค€๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์—์„œ๋„ ์‚ฌ์ „์— ๋น„ํ•ด ์‚ฌํ›„์— ์‹คํ–‰์˜ ์ˆ˜์ค€์ด ํ–ฅ์ƒํ•˜์˜€๋‹ค. ํ•˜์ง€๋งŒ, ์ˆ˜์—… ์‹œ๊ฐ„์— ๋ฐฐ์šด ๋‚ด์šฉ๊ณผ ๋ฐฐ์šฐ์ง€ ์•Š์€ ๋‚ด์šฉ์œผ๋กœ ๋‚˜๋ˆ„์–ด ๋น„๊ตํ•ด ๋ณด์•˜์„ ๋•Œ, ๊ธฐ์กด์˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์™€๋Š” ๋‹ฌ๋ฆฌ ๋ฐฐ์šฐ์ง€ ์•Š์€ ๋‚ด์šฉ์œผ๋กœ ์‹คํ–‰์˜ ์ „์ด๋Š” ์–ด๋ ค์šด ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์˜ ๋ณ€ํ™” ์œ ํ˜•๋ณ„ ํŠน์ง•์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์ˆ˜์ค€์ด ์ƒ์Šนํ•œ ํ•™์ƒ์˜ ๊ฒฝ์šฐ, ๋ณธ์ธ์˜ ๋ชจํ˜• ๊ตฌ์„ฑ์— ๋น„ํ•ด ๋†’์€ ์ˆ˜์ค€์˜ ํ‰๊ฐ€ ๋Šฅ๋ ฅ์„ ๋ณด์˜€์œผ๋ฉฐ, ํ‰๊ฐ€๋ฅผ ํ†ตํ•ด ๊ณ ๋ คํ•˜๊ฒŒ ๋œ ์ œ์•ฝ์กฐ๊ฑด์„ ์‚ฌํ›„ ์ž์‹ ์˜ ๋ชจํ˜• ๊ตฌ์„ฑ์— ๋ฐ˜๋ฐ•(rebuttal) ๋ฐฉ์‹์œผ๋กœ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋‘˜์งธ, ์ˆ˜์ค€์ด ํ•˜๊ฐ•ํ•œ ๊ฒฝ์šฐ์—๋Š” ํ•™์ƒ์ด ์ด๋ฏธ ์ •๋‹ต์„ ์•Œ๊ณ  ์žˆ์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ์ž๋ฃŒ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ชจํ˜•์„ ๊ตฌ์„ฑํ•˜์ง€ ์•Š์•˜์œผ๋ฉฐ, ์ˆ˜์—… ํ›„์—๋Š” ์ •๋‹ต์— ๋”์šฑ ํ™•์‹ ์„ ๊ฐ–๊ฒŒ ๋˜์–ด ๋ชจํ˜•๊ณผ ์ž๋ฃŒ์˜ ์—ฐ๊ฒฐ ๊ณ ๋ฆฌ๊ฐ€ ๋”์šฑ ์•ฝํ•ด์ง€๋ฉฐ ์ •๋‹ต์„ ์ ๋Š” ๊ฒƒ์—๋งŒ ์ง‘์ค‘ํ•˜์˜€๋‹ค. ์…‹์งธ, ๋†’์€ ์ˆ˜์ค€์„ ์œ ์ง€ํ•œ ํ•™์ƒ์˜ ๊ฒฝ์šฐ, ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰ ์ˆ˜์ค€์ด ๋†’์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์ž˜๋ชป๋œ ์ดˆ๊ธฐ์ž์›์œผ๋กœ ์ธํ•ด ๋น„๊ณผํ•™์ ์ธ ๋ชจํ˜•์„ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ํ•˜์ง€๋งŒ, ์ˆ˜์—…์„ ํ†ตํ•ด ์ดˆ๊ธฐ์ž์›์ด ์˜ณ๊ฒŒ ๋ฐ”๋€Œ๋ฉด์„œ ๊ณผํ•™์ ์ธ ๋ชจํ˜•์„ ๊ตฌ์„ฑํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋„ท์งธ, ๋‚ฎ์€ ์ˆ˜์ค€์„ ์œ ์ง€ํ•œ ํ•™์ƒ์˜ ๊ฒฝ์šฐ, ์‚ฌ์ „ ์‚ฌํ›„ ๋ชจ๋‘์—์„œ ์ฃผ์–ด์ง„ ์ž๋ฃŒ์™€ ๋ฌด๊ด€ํ•œ ๊ณผํ•™ ์šฉ์–ด์™€ ๊ฐœ๋…์„ ๋‹จ์ˆœํžˆ ๋‚˜์—ดํ•˜๋Š” ๊ฒƒ์— ๊ทธ์น˜๋Š” ๋ชจ์Šต์„ ๋ณผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์„ ํ†ตํ•ด ํ•™์ƒ๋“ค์˜ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์ด ํ–ฅ์ƒ๋˜์—ˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ๋” ๋‚˜์€ ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์„ ์œ„ํ•ด ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์ถ”๊ฐ€์ ์ธ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค. ์†Œ์ง‘๋‹จ ํ† ๋ก  ๊ณผ์ •์—์„œ ํ‰๊ฐ€์™€ ์ˆ˜์ • ๊ณผ์ •์„ ๋”์šฑ ๊ฐ•์กฐํ•  ํ•„์š”์„ฑ์ด ์žˆ์œผ๋ฉฐ, ์ •๋‹ต์„ ์•Œ๊ณ  ์žˆ๋Š” ํ•™์ƒ์ด๋ผ ํ•˜๋”๋ผ๋„ ์ฃผ์–ด์ง„ ์ž๋ฃŒ๋ฅผ ๊ทผ๊ฑฐ๋กœ ํ•˜์—ฌ ๋ชจํ˜•์„ ๊ตฌ์„ฑํ•ด ๋ณด๋„๋ก ์œ ๋„ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ, ๊ต์‚ฌ๋Š” ์ˆ˜์—… ์ „ ํ•™์ƒ์ด ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋น„๊ณผํ•™์ ์ธ ์ดˆ๊ธฐ ์ž์›์„ ํŒŒ์•…ํ•˜์—ฌ ์ด๋ฅผ ๊ณผํ•™์ ์œผ๋กœ ๋ณ€ํ™”์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๊ธฐํšŒ๋ฅผ ์ œ๊ณตํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์„ ์ˆ˜์—… ์ดˆ๋ฐ˜์— ๋ช…์‹œ์ ์œผ๋กœ ์ œ์‹œํ•˜๋Š” ๊ฒƒ๋„ ํ•™์ƒ๋“ค์˜ ์ธ์‹๋ณ€ํ™”๋ฅผ ์œ„ํ•ด ํ•„์š”ํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•™์ƒ๋“ค์˜ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋” ๋‚˜์€ ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—… ์ „๋žต์„ ์„ธ์šฐ๋Š”๋ฐ ์‹œ์‚ฌ์ ์„ ์ค€๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ๋น„๊ต ์ง‘๋‹จ ์—†์ด ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์„ ํ†ตํ•ด์„œ๋งŒ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์˜ ๋ณ€ํ™”๋ฅผ ์•Œ์•„๋ณด์•˜๋‹ค๋Š” ํ•œ๊ณ„์ ์„ ์ง€๋‹ˆ๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋™์ผํ•œ ์ฃผ์ œ๋ฅผ ๊ฐ€์ง€๊ณ  ๊ฐ•์˜์‹ ์ˆ˜์—…, ์‹คํ—˜์‹ ์ˆ˜์—…, ๋ชจํ˜• ๊ธฐ๋ฐ˜ ์ˆ˜์—…์œผ๋กœ ์ง„ํ–‰ํ•˜์˜€์„ ๋•Œ, ๊ฐ๊ฐ์˜ ์ˆ˜์—…์ด ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ์ฃผ๋Š”์ง€ ๊ทธ ์ฐจ์ด๋ฅผ ๋น„๊ตํ•ด ๋ณด๋Š” ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์€ ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์˜ ์ „์ด๋ฅผ ์œ„ํ•œ ๋ฐฉ์•ˆ์„ ๋ชจ์ƒ‰ํ•  ํ•„์š”๊ฐ€ ์žˆ์œผ๋ฉฐ, ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์˜ ๋ณ€ํ™”๊ฐ€ ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ์ฃผ๋Š”์ง€์— ๋Œ€ํ•ด์„œ๋„ ์—ฐ๊ตฌํ•ด ๋ณผ ํ•„์š”๊ฐ€ ์žˆ๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๋ฌธ์ œ 3 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 4 ์ œ 1 ์ ˆ ๊ณผํ•™์  ๋ชจํ˜•๊ณผ ๊ณผํ•™๊ต์œก 4 1. ๊ณผํ•™์  ๋ชจํ˜• 4 2. ๊ณผํ•™๊ต์œก์—์„œ์˜ ๊ณผํ•™์  ๋ชจํ˜•๊ณผ ๋ชจํ˜• ๊ตฌ์„ฑ 5 ์ œ 2 ์ ˆ ๊ณผํ•™์  ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ 10 1. ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹(metamodeling knowledge) 11 2. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰(modeling practice) 13 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 14 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ์ฐธ์—ฌ์ž 14 ์ œ 2 ์ ˆ ์ž๋ฃŒ ์ˆ˜์ง‘ 16 ์ œ 3 ์ ˆ ๋ชจํ˜• ๊ตฌ์„ฑ ๋Šฅ๋ ฅ ๊ฒ€์‚ฌ ๋„๊ตฌ 18 1. ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์„ ์œ„ํ•œ ๊ฒ€์‚ฌ ๋„๊ตฌ 18 2. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์„ ์œ„ํ•œ ๊ฒ€์‚ฌ ๋„๊ตฌ 20 ์ œ 4 ์ ˆ ๋ถ„์„ ๋ฐฉ๋ฒ• 23 1. ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์„ ์œ„ํ•œ ๋ถ„์„ ๋ฐฉ๋ฒ• 23 2. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์„ ์œ„ํ•œ ๋ถ„์„ ๋ฐฉ๋ฒ• 24 ์ œ 4 ์žฅ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ 31 ์ œ 1 ์ ˆ ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹์˜ ๋ณ€ํ™” 31 1. ํ‘œ์ƒ์œผ๋กœ์จ์˜ ๋ชจํ˜•(Models as representations) 33 2. ๋ชจํ˜•์˜ ๋‹ค์–‘์„ฑ(The multiplicity of models) 38 3 ๋ชจํ˜•์˜ ์—ญ๋™์  ๋ณธ์„ฑ(The dynamic nature of models) 41 ์ œ 2 ์ ˆ ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์˜ ๋ณ€ํ™” 49 1. ๊น€์ƒ์Šน ํ•™์ƒ์˜ ์‚ฌ๋ก€ 51 2. ์ดํ•˜๊ฐ• ํ•™์ƒ์˜ ์‚ฌ๋ก€ 58 3. ๋ฐ•๋†’์Œ ํ•™์ƒ์˜ ์‚ฌ๋ก€ 67 4. ์ตœ๋‚ฎ์Œ ํ•™์ƒ์˜ ์‚ฌ๋ก€ 78 ์ œ 5 ์žฅ ๊ฒฐ๋ก  ๋ฐ ๋…ผ์˜ 86 ์ฐธ๊ณ ๋ฌธํ—Œ 91 ๋ถ€ ๋ก 97 1. ํƒœ์–‘ ํ‘์ ์„ ํ†ตํ•œ ํƒœ์–‘ ์ž์ „ ๋ชจํ˜• ๊ตฌ์„ฑ ํ•™์Šต์ง€ 97 2. ๋ชจํ˜• ๊ตฌ์„ฑ์— ๊ด€ํ•œ ์ง€์‹ ๊ฒ€์‚ฌ์ง€ 102 3. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰ ๊ฒ€์‚ฌ์ง€ 105 4. ๋ชจํ˜• ๊ตฌ์„ฑ ์‹คํ–‰์„ ์œ„ํ•œ ์ฑ„์  ๊ธฐ์ค€ 118 Abstract 119Maste

    V-Model: A Model for Chronological Visualization of Narrative Medical Events

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ˜‘๋™๊ณผ์ • ์˜์šฉ์ƒ์ฒด๊ณตํ•™์ „๊ณต, 2015. 2. ์ตœ์ง„์šฑ.์„œ๋ก  EMR์˜ ๋„๋ž˜๋กœ ํ™˜์ž ๋ฐ์ดํ„ฐ๊ฐ€ ํ’๋ถ€ํ•˜๊ฒŒ ์ถ•์ •๋˜๊ณ  ์žˆ์ง€๋งŒ, ์ž์—ฐ์–ด ์˜๋ฌด๊ธฐ๋ก์ง€์˜ ๊ฒฝ์šฐ ๋‹ค๋Ÿ‰์˜ ๋ฐ์ดํ„ฐ๋ฅผ ํŒŒ์•…ํ•˜๋Š”๋ฐ ์‹œ๊ฐ„์ด ๋งŽ์ด ์†Œ์š”๋˜์–ด ์ง„๋ฃŒ์— ์ถฉ๋ถ„ํžˆ ํ™œ์šฉ๋˜์ง€ ๋ชปํ•˜๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž์—ฐ์–ด ์˜๋ฌด๊ธฐ๋ก์ง€์˜ ํ™œ์šฉ๋„๋ฅผ ๋†’์ด๊ธฐ ์œ„ํ•ด ์‹œ๊ฐ„ ์ •๋ณด๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ํƒ€์ž„๋ผ์ธ์— ์˜๋ฃŒ๋ฐ์ดํ„ฐ๋ฅผ ์‹œ๊ฐํ™”ํ•  ์ˆ˜ ์žˆ๋Š” V-Model์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ฐฉ๋ฒ• V-Model์€ โ€˜vโ€™์ž ํ˜•ํƒœ์˜ ๊ตฌ์กฐ๋กœ ์˜๋ฃŒ์‚ฌ๊ฑด์„ ์‹œ๊ฐํ™”ํ•˜๋Š” ๋ชจ๋ธ์ด๋‹ค. ์„ค๊ณ„์‹œ ํ‘œํ˜„์ , ์ถ”๋ก ์ , ์‹œ๊ฐ์  ์ธก๋ฉด์„ ๊ณ ๋ คํ•˜์˜€๋‹ค. V-Model์€ ๊ธฐ์กด์˜ point, interval ์ค‘์‹ฌ์˜ ํ‘œํ˜„์—์„œ ํ•ด๊ฒฐํ•˜์ง€ ๋ชปํ–ˆ๋˜ ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ ๋ฌธ์ œ์ธ causality, non-explicit temporal information, and granularity issues ์„ ๋‹ค๋ฃฐ ์ˆ˜ ์žˆ๋Š” ํ‹€์„ ์ œ๊ณตํ•˜๋ฉด์„œ๋„, ์‹œ๊ฐ„ ์ •๋ณด ์œ ์ถ”๊ฐ€ ๊ฐ€๋Šฅํ•˜๋ฉฐ, ์ง๊ด€์ ์ธ ํƒ€์ž„๋ผ์ธ์„ ์ œ๊ณตํ•œ๋‹ค. V-Model์€ ์ „ํ†ต์ ์ธ ํƒ€์ž„๋ผ์ธ๊ณผ์˜ ๋น„๊ต๋ฅผ ํ†ตํ•ด ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์ด 3๋‹จ๊ณ„๋กœ ๊ตฌ์„ฑ๋œ ์‹คํ—˜์—์„œ, V-Model์ด ์ œ์•ˆํ•œ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๊ฒ€์ฆ์„ ํ•˜์˜€๊ณ , ์‚ฌ์šฉ์„ฑ์— ๋Œ€ํ•œ ์„ค๋ฌธ ์กฐ์‚ฌ, ํ”ผ๋“œ๋ฐฑ์„ ๋ฐ›๊ธฐ ์œ„ํ•œ ์ธํ„ฐ๋ทฐ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์‹คํ—˜์—๋Š” 40๋ช…์˜ ์ „๊ณต์˜์™€ 40๋ช…์˜ ์˜๋Œ€์ƒ์ด ์ฐธ์—ฌํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ V-Model์€ ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ ๋ฌธ์ œ๋ฅผ ํ‘œํ˜„ํ•˜๊ณ  ์ „๋‹ฌํ•˜๋Š” ๋ฐ ๊ธฐ์กด ํƒ€์ž„๋ผ์ธ๋ณด๋‹ค ํƒ์›”ํ•˜๋ฉฐ, ์‹œ๊ฐ„ ์ถ”๋ก ์„ ์œ„ํ•œ ์ •๋ณด๋ฅผ ์ถฉ๋ถ„ํžˆ ์ œ๊ณตํ•˜๊ณ , ๊ฐ€๋…์„ฑ์ด ๋” ๋›ฐ์–ด๋‚จ์ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ์‚ฌ์šฉ์„ฑ๊ณผ ๊ด€๋ จํ•ด์„œ๋„ ๊ธ์ •์ ์ธ ๋‹ต๋ณ€์„ ๋ฐ›์•˜์œผ๋ฉฐ, ํ™˜์ž์˜ ๋ณ‘๋ ฅ์„ ํŒŒ์•…ํ•˜๋Š”๋ฐ ํšจ๊ณผ์ ์ด๋ผ๋Š” ํ‰๊ฐ€๋ฅผ ๋ฐ›์•˜๋‹ค. ๊ฒฐ๋ก  V-Model์€ ์‹คํ—˜์„ ํ†ตํ•ด ์ž์—ฐ์–ด์˜ ๋ฌธ์ œ์ ์„ ํ‘œํ˜„ํ•˜๊ณ  ์ „๋‹ฌํ•  ์ˆ˜ ์žˆ๊ณ , ์ •๋Ÿ‰์ , ์ •์„ฑ์  ์‹œ๊ฐ„๊ด€๊ณ„๋ฅผ ์ถ”๋ก ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ด์ฃผ๋ฉฐ, ์‹œ๊ฐ์ ์œผ๋กœ ๊ฐ€๋…์„ฑ์ด ์ข‹๋‹ค๋Š” ์ ์ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ์‚ฌ์šฉ์„ฑ ํ‰๊ฐ€ ํ…Œ์ŠคํŠธ์—์„œ ๊ธ์ •์ ์ธ ํ‰๊ฐ€๋ฅผ ๋ฐ›์•„ ํ–ฅํ›„ ์ง„๋ฃŒ ๋ฐ ์—ฐ๊ตฌ์—์„œ์˜ ํ™œ์šฉ์„ฑ์ด ๊ธฐ๋Œ€๋œ๋‹ค.Objective Visualizing narrative medical events into a timeline can have positive effects on clinical environments. However, Current timeline systems, which are based on a point/interval representation, have difficulties in representing narrative clinical events. The purpose of this paper is to propose an innovative time model for visualizing narrative patient history and evaluate our solutions. Materials and Methods The V-Model models clinical situation effectively based on v-like graphical structure. The model visualizes patient history on a timeline in a simple and intuitive way. For the design, the representation, reasoning, and visualization (readability) aspects were considered. Furthermore, the unique graphical notation helps to find hidden patterns of a specific patient group. It provides solutions for the unresolved natural language problemscausality, non-explicit temporal information, and granularity issues. For evaluation, we verified our distinctive solutions, surveyed usability, and interviewed the subjects for qualitative comments. The experiments were carried out for the V-Model group and the conventional timeline model group. Overall fourty medical students and fourty physicians participated in this evaluation. Results The V-Model was proven to be superior in representing narrative medical events, provide sufficient information for temporal reasoning, and outperform in readability compared to a conventional timeline model. The usability of the V-Model was assessed positively. And prominent number of the participants commented that the model is very effective for understanding a patientโ€™s history. Conclusion With a novel graphical concept time frame, the V-Model innovatively resolves visualization issues of clinical documents. The V-Model successfully solves the modeling requirements and has better usability compared to conventional timeline models. The work presented here has profound implications for future clinical environment.์ œ 1 ์žฅ ์„œ๋ก  1 1.1 ๋ฌธ์ œ์ œ๊ธฐ 1 1.2 ์˜๋ฃŒ์‚ฌ๊ฑด์˜ ์—ฐ๋Œ€๊ธฐ์  ํ‘œํ˜„์˜ ์ค‘์š”์„ฑ 2 1.3 ๊ด€๋ จ ์—ฐ๊ตฌ 3 1.4 ์ „ํ†ต์  ํƒ€์ž„๋ผ์ธ 12 1.5 ์ž์—ฐ์–ด ์˜๋ฃŒ์‚ฌ๊ฑด์˜ ์—ฐ๋Œ€๊ธฐ์  ํ‘œํ˜„์— ๋”ฐ๋ฅธ ๋ฌธ์ œ์  12 1.5.1 Causality 12 1.5.2 Non-explicitness 13 1.5.3 Temporal Granularity 17 1.5.4 Reasoning 18 1.6 ๋ชฉ์  20 ์ œ 2 ์žฅ ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ• 20 2.1 ์„ค๊ณ„์‹œ ๊ณ ๋ ค์‚ฌํ•ญ 20 2.2 V-Model 22 2.2.1 V-Model ์†Œ๊ฐœ 22 2.2.2 ์‚ฌ๊ฑด(Event)์˜ ํ‘œํ˜„ 23 2.2.3 ์‹œ๊ฐ„ ํ‘œํ˜„ (Time Achoring Point, TAP) 34 2.3 V-Model์˜ ํŠน์ง• 42 2.3.1 ํ‘œํ˜„(Representation) ์ธก๋ฉด 43 2.3.2 ์ถ”๋ก (Reasoning) ์ธก๋ฉด 50 2.3.3 ์‹œ๊ฐ (Visualization) ์ธก๋ฉด 54 2.4 V-Model์„ ์ด์šฉํ•œ ํŒจํ„ด ์ธ์‹ 62 2.5 ์‹คํ—˜ ์„ค๊ณ„ 63 2.5.1 ์‹คํ—˜ I: ๊ฒ€์ฆ ์‹คํ—˜ 66 2.5.2 ์‹คํ—˜ II: ์‚ฌ์šฉ์„ฑ ์„ค๋ฌธ ํ‰๊ฐ€ 72 2.5.3 ์‹คํ—˜ III: ์ธํ„ฐ๋ทฐ 74 ์ œ 3 ์žฅ ๊ฒฐ๊ณผ 75 3.1 ์‹คํ—˜ I ๊ฒฐ๊ณผ 75 3.1.1 ํ‘œํ˜„(Representation) ์ธก๋ฉด 77 3.1.2 ์ถ”๋ก (Reasoning) ์ธก๋ฉด 78 3.1.3 ์‹œ๊ฐ์ (Visualization) ์ธก๋ฉด 79 3.1.4 ์ข…ํ•ฉ ํ‰๊ฐ€ 80 3.2 ์‚ฌ์šฉ์„ฑ ํ‰๊ฐ€ 82 3.2.1 ์ •๋Ÿ‰์  ํ‰๊ฐ€ (์„ค๋ฌธ ํ‰๊ฐ€) 82 3.2.2 ์ •์„ฑ์  ํ‰๊ฐ€ (์ธํ„ฐ๋ทฐ) 85 ์ œ 4 ์žฅ ๊ณ ์ฐฐ 93 ์ œ 5 ์žฅ ๊ฒฐ๋ก  103 APPENDIX. ํ™˜์ž ๋ณ‘๋ ฅ์˜ ์‹œ๊ฐํ™” ๋น„๊ต 105 ์ฐธ๊ณ ๋ฌธํ—Œ 115 Abstract 117Docto

    Oral lichen planus: REU scoring system correlates with pain

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    Objectives. The objectives of this study were to correlate a semiquantitative scoring system for oral lichen planus (OLP) with pain before versus after treatment and to analyze sites of involvement and candidal status of patients in a retrospective study.Study Design. Reticulation/keratosis, erythema, and ulceration (REU) scores and numerical rating scale (NRS) for pain were used. Correlation was tested using Spearman rank correlation, and the change in REU and NRS scores using the paired t test.Results. One hundred fifteen patients were evaluable with 55 follow-up visits. Pain showed positive correlation with the total weighted score (r = .40), erythema (r = .35), ulceration (r = .31), and reticulation scores (r = .29), all at P < .005. There was improvement in REU and NRS scores before versus after treatment (P < .0001). The internal consistency reliability analysis yielded good reliability with Cronbach coefficient alpha of 0.70. The ventral tongue, floor of mouth, and soft palate were never the only sites affected. Candidal carriage was present in 24% of cases but candidiasis developed in only 10% of carriers.Conclusions. The REU system is easy to use, correlates with an NRS for pain, and reliably reflects improvement attributable to treatment. Ventral tongue, floor of mouth, and soft palate were sites of OLP only if other sites were involved and candidiasis did not always develop in patients who were carriers. (Oral Surg Oral Med Oral Pathol Oral Radiol 2012;114:75-82)OAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000047106/1SEQ:1PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000047106ADJUST_YN:YEMP_ID:A077052DEPT_CD:861CITE_RATE:1.457FILENAME:OLP-REU scoring-park-2012.pdfDEPT_NM:์น˜์˜ํ•™๊ณผEMAIL:[email protected]_YN:YCONFIRM:
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