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    ์ค‘์†Œ๊ธฐ์—…์€ํ–‰ ์‚ฌ๋ก€๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ณต๊ธฐ์—…์ •์ฑ…ํ•™๊ณผ, 2020. 8. ๊น€๋™์šฑ.๋ณธ ์—ฐ๊ตฌ๋Š” 2014๋…„ 7์›” ์ •๋ถ€๊ฐ€ ๊ธฐ์ˆ ๊ธˆ์œต์˜ ํ™œ์„ฑํ™”๋ฅผ ํ†ตํ•˜์—ฌ ์ค‘์†Œ๊ธฐ์—…์˜ ์ž๊ธˆ์กฐ๋‹ฌ๊ฒฝ๋กœ๋ฅผ ๋‹ค์–‘ํ™”ํ•  ๋ชฉ์ ์œผ๋กœ ๊ธฐ์กด์˜ ๊ธฐ์ˆ ๊ธˆ์œต์„ ํ™•๋Œ€โ‹…๊ฐœํŽธํ•˜์—ฌ ์ถ”์ง„์ค‘์ธ TCB(Technology Credit Bureau)ํ‰๊ฐ€ ๊ธฐ๋ฐ˜์˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ์˜ ํšจ์œจ์„ฑ๊ณผ ํ•„์š”์„ฑ์„ ํ™•์ธํ•˜๊ณ ์ž ์‹œ์ž‘๋˜์—ˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ์ฒซ์งธ, ๊ธฐ์ˆ ๋ ฅ์„ ํ™•๋ณดํ•œ ์ค‘์†Œ๊ธฐ์—…์„ ๋ฐœ๊ตด ๋ฐ ์ง‘์ค‘์œก์„ฑํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ถ”์ง„์ค‘์ธ TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜์˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ์„ ์ง€์›๋ฐ›์€ ์ค‘์†Œ๊ธฐ์—…์ด ์ผ๋ฐ˜๋Œ€์ถœ์„ ์ง€์›๋ฐ›์€ ์ค‘์†Œ๊ธฐ์—…๋ณด๋‹ค ์–‘ํ˜ธํ•œ ์žฌ๋ฌด์„ฑ๊ณผ๋ฅผ ๋‹ฌ์„ฑํ•˜๋„๋ก ๊ธฐ์—ฌํ•˜์˜€๋Š”์ง€ ์‚ดํŽด๋ณด์•˜๋‹ค. ๋‘˜์งธ, ๊ธฐ์ˆ ๊ธˆ์œต ํ™œ์„ฑํ™”๋ฅผ ์œ„ํ•˜์—ฌ ๊ธฐ์—… ๋Œ€์ถœ์‹ฌ์‚ฌ์— ํ™œ์šฉ๋˜๋Š” TCBํ‰๊ฐ€์˜ ํ•ต์‹ฌ์ธ ๊ธฐ์ˆ ํ‰๊ฐ€๋“ฑ๊ธ‰(T๋“ฑ๊ธ‰)์—์„œ ์ƒ์œ„๋“ฑ๊ธ‰์„ ๋ฐ›์€ ๊ธฐ์—…๊ตฐ์ด ํ•˜์œ„๋“ฑ๊ธ‰์„ ๋ฐ›์€ ๊ธฐ์—…๊ตฐ๋ณด๋‹ค ์–‘ํ˜ธํ•œ ์žฌ๋ฌด์„ฑ๊ณผ๋ฅผ ๋‹ฌ์„ฑํ•˜๋„๋ก ๊ธฐ์—ฌํ•˜์˜€๋Š”์ง€ ์‚ดํŽด๋ณด์•˜๋‹ค. ๋˜ํ•œ, ์„ฑ์žฅ์„ฑ, ์ˆ˜์ต์„ฑ, ์•ˆ์ •์„ฑ ์ธก๋ฉด์—์„œ ์ง€์› ์—ฐ๋„ ๋Œ€๋น„ T+1, T+2, T+3๊ธฐ์˜ ์–‘ ์ง‘๋‹จ๊ฐ„ ์žฌ๋ฌด์„ฑ๊ณผ์˜ ์ฐจ์ด๊ฐ€ ์กด์žฌํ•˜๋Š”์ง€ ์„ฑํ–ฅ์ ์ˆ˜๋งค์นญ(PSM : Propensity Score Matching)์„ ํ†ตํ•œ ๋Œ€์กฐ๊ตฐ ์„ ๋ณ„ ํ›„, ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„(Multiple regression)์„ ํ†ตํ•˜์—ฌ ์žฌ๋ฌด์„ฑ๊ณผ์— ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ๋Š”์ง€๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ์‹ค์ฆ์  ์žฌ๋ฌด์„ฑ๊ณผ ๋น„๊ต๋ถ„์„ ๊ฒฐ๊ณผ, ์„ฑ์žฅ์„ฑ ์ง€ํ‘œ์˜ ๋งค์ถœ์•ก์ฆ๊ฐ€์œจ๊ณผ ์ˆ˜์ต์„ฑ ์ง€ํ‘œ์˜ ์ž๊ธฐ์ž๋ณธ์˜์—…์ด์ต์œจ์˜ ๊ฒฝ์šฐ TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ ๋ฐ ๊ธฐ์ˆ ํ‰๊ฐ€(T)๋“ฑ๊ธ‰ ์ƒ์œ„๊ทธ๋ฃน ๋ชจ๋‘ ์ดˆ๊ธฐ์—๋Š” ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ฐœ๊ฒฌํ•˜์ง€ ๋ชปํ•˜์˜€์œผ๋‚˜, T+3๋…„์— ์ด๋ฅด๋Ÿฌ ์ผ์ • ์ˆ˜์ค€์˜ ๊ฐœ์„ ํšจ๊ณผ๋ฅผ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ์•ˆ์ •์„ฑ ์ง€ํ‘œ์˜ ์ž๊ธฐ์ž๋ณธ์ฆ๊ฐ€์œจ์˜ ๊ฒฝ์šฐ T+1๋…„์—๋Š” ์ผ๋ฐ˜ ์ง€์›๊ธฐ์—…๊ณผ ๋น„๊ตํ•˜์—ฌ ์—ด์œ„๋ฅผ ๋‚˜ํƒ€๋‚ด์—ˆ์œผ๋‚˜, ์ดํ›„์—๋Š” ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋‚˜ํƒ€๋‚ด์ง€ ์•Š์•„ ๋‹จ๊ธฐ์  ์—ด์œ„๋ฅผ ๋‹ค์†Œ ๊ฐœ์„ ํ•œ ๊ฒƒ์œผ๋กœ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฐ™์€ ํ•ญ๋ชฉ์—์„œ ๊ธฐ์ˆ ํ‰๊ฐ€(T)๋“ฑ๊ธ‰ ์ƒ์œ„๊ทธ๋ฃน์˜ ๊ฒฝ์šฐ ์ดˆ๊ธฐ์—๋Š” ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋‚˜ํƒ€๋‚ด์ง€ ์•Š์•˜์œผ๋‚˜ T+2๋…„ ์ดํ›„๋ถ€ํ„ฐ ๋น„๊ต์ง‘๋‹จ ๋Œ€๋น„ ๊ธ์ •์  ๊ฐœ์„ ํšจ๊ณผ๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜์˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ ์ง€์›๊ธฐ์—…์ด ์ผ๋ฐ˜ ์ค‘์†Œ๊ธฐ์—…์— ๋น„ํ•ด ์„ฑ์žฅ์„ฑ, ์ˆ˜์ต์„ฑ, ์•ˆ์ •์„ฑ์— ์ธก๋ฉด์—์„œ ๋‹จ๊ธฐ์  ํšจ๊ณผ๋ณด๋‹ค๋Š” ์ค‘๊ธฐ์  ํšจ๊ณผ๋ฅผ ๊ธฐ๋Œ€ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๊ธฐ์ˆ ํ‰๊ฐ€๋“ฑ๊ธ‰์„ ํ†ตํ•˜์—ฌ ๊ธฐ์ˆ ๋ ฅ์ด ๋” ์šฐ์ˆ˜ํ•˜๋‹ค๊ณ  ์ธ์ •๋ ์ˆ˜๋ก ๊ทธ ํšจ๊ณผ๋ฅผ ์ƒ๋Œ€์ ์œผ๋กœ ๋” ํฌ๊ฒŒ ๊ธฐ๋Œ€ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ผ์ • ๋ถ€๋ถ„ ์˜๋ฏธ ์žˆ๋Š” ๊ฒฐ๋ก ์„ ๋„์ถœํ•˜์˜€๋‹ค.In July 2014, the government expanded and reorganized existing technology financing to diversify the funding channels for small and medium enterprises through the revitalization of technology financing. This study was initiated to identify the efficiency and necessity of small business loans based on the Technology Credit Bureau (TCB) assessment. To this end, we first examined whether small and medium-sized enterprises that received TCB-based loans contributed to achieving better financial performance than those that received general loans. Second, to facilitate technology financing, we looked at whether the group of companies that received the highest rating in the technology evaluation (T-rated), which is the core of the TCB evaluation used in the corporate loan review, contributed to achieving better financial performance than the group of companies that received the lower grade. In addition, a control group screening (PSM) to determine whether there is a difference in financial performance between the two groups in terms of growth, profitability and stability compared to the support year(T+1, T+2 and T+3), and a multi-regression analysis to confirm whether there are significant differences in financial performance. Comparative analysis of empirical financial performance found no significant difference in the initial period between the TCB-based loan and the T-rated upper group for the growth index and the return on equity operations of the profitability index. However, a certain level of improvement could be estimated by T+3 and the equity increase rate in the stability index was inferior to that of the general support company in T+1, but later it was estimated that the short-term position was somewhat improved because it did not show any significant difference. In the same category, the T-rated higher groups did not initially show significant differences, but it could be estimated that there would be a positive improvement over the comparative group from T+2. This led to some meaningful conclusions that TCB-based loan-supporting entities could expect medium-term effects rather than short-term effects in terms of growth, profitability and stability over comparators, and that the more technology is recognized through technology ratings, the greater the effect.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ๊ณผ ๋ฐฉ๋ฒ• 5 ์ œ 2 ์žฅ ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  7 ์ œ 1 ์ ˆ ์ค‘์†Œ๊ธฐ์—… 7 ์ œ 2 ์ ˆ ์ค‘์†Œ๊ธฐ์—… ์ •์ฑ…๊ธˆ์œต 9 ์ œ 3 ์ ˆ ๊ธฐ์ˆ ๊ธˆ์œต 12 1. ๊ธฐ์ˆ ๊ธˆ์œต์˜ ์˜์˜ 12 2. ๊ธฐ์ˆ ๊ธˆ์œต ํ˜„ํ™ฉ 14 3. TCBํ‰๊ฐ€ ๊ฐœ์š” 16 4. TCB์˜ ํ‰๊ฐ€๋‚ด์šฉ 18 ์ œ 4 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  21 1. ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  21 2. ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 23 ์ œ 3 ์žฅ ์—ฐ๊ตฌ์„ค๊ณ„ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• 24 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ชจํ˜• ๋ฐ ๊ฐ€์„ค์„ค์ • 24 1. ์—ฐ๊ตฌ๋ชจํ˜• 24 2. ๊ฐ€์„ค์„ค์ • 26 ์ œ 2 ์ ˆ ๋ณ€์ˆ˜์„ค์ • 28 1. ์ข…์†๋ณ€์ˆ˜ 28 2. ๋…๋ฆฝ๋ณ€์ˆ˜ 29 3. ํ†ต์ œ๋ณ€์ˆ˜ 29 ์ œ 3 ์ ˆ ์ž๋ฃŒ์˜ ์ˆ˜์ง‘๊ณผ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 30 1. ์ž๋ฃŒ์˜ ์ˆ˜์ง‘ 30 2. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 31 2.1 ์„ฑํ–ฅ์ ์ˆ˜๋งค์นญ(Propensity Score Matching).................. 31 2.2 ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„(Multiple Regression)................................ 32 ์ œ 4 ์žฅ ์‹ค์ฆ๋ถ„์„๊ฒฐ๊ณผ 34 ์ œ 1 ์ ˆ ๊ธฐ์ˆ ์  ํ†ต๊ณ„๋ถ„์„ 34 ์ œ 2 ์ ˆ ๋ณ€์ˆ˜ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ 39 ์ œ 3 ์ ˆ TCBํ‰๊ฐ€ ๊ธฐ๋ฐ˜ ๋ฐ ์ผ๋ฐ˜ ์ค‘์†Œ๊ธฐ์—…๋Œ€์ถœ ์ง€์›๊ธฐ์—… ๋น„๊ต ๋ถ„์„ 45 1. ์„ฑ์žฅ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 45 1.1 ๋งค์ถœ์•ก์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 45 1.2 ์ด์ž์‚ฐ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 46 2. ์ˆ˜์ต์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 47 2.1 ์ž๊ธฐ์ž๋ณธ์˜์—…์ด์ต์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 47 3. ์•ˆ์ •์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 48 3.1 ๋ถ€์ฑ„์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 48 3.2 ์ž๊ธฐ์ž๋ณธ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 49 ์ œ 4 ์ ˆ ๊ธฐ์ˆ ํ‰๊ฐ€(T)๋“ฑ๊ธ‰ ์ƒํ•˜์œ„๊ทธ๋ฃน ๋น„๊ต๋ถ„์„ 51 1. ์„ฑ์žฅ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 51 1.1 ๋งค์ถœ์•ก์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 51 1.2 ์ด์ž์‚ฐ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 52 2. ์ˆ˜์ต์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 53 2.1 ์ž๊ธฐ์ž๋ณธ์˜์—…์ด์ต์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 53 3. ์•ˆ์ •์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 54 3.1 ๋ถ€์ฑ„์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 54 3.2 ์ž๊ธฐ์ž๋ณธ์ฆ๊ฐ€์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 55 ์ œ 5 ์žฅ ๊ฒฐ๋ก  57 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ ๋ฐ ์‹œ์‚ฌ์  57 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 59 ์ฐธ๊ณ ๋ฌธํ—Œ 61 Abstract 64Maste

    (A) study about building-related health symptoms of workers at dental collage hospitals in Seoul : ์„œ์šธ์‹œ๋‚ด ์†Œ์žฌ ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์„ ์ค‘์‹ฌ์œผ๋กœ

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    ํ™˜๊ฒฝ๋ณด๊ฑดํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์€ ๋งŽ์€ ๊ณ ๊ฐ(ํ™˜์ž)๋“ค์ด ์™•๋ž˜ํ•˜๊ณ , ๋‹ค์–‘ํ•œ ์œ ํ•ดํ™˜๊ฒฝ์ด ์กด์žฌํ•˜๊ณ  ์žˆ์–ด ์—ฌ๋Š ๋นŒ๋”ฉ์˜ ์‹ค๋‚ด๊ณต๊ฐ„๋ณด๋‹ค ๋” ๋งŽ์€ ์˜ค์—ผ๋ฌผ์งˆ์— ๋…ธ์ถœ๋  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์˜ ํšจ์œจ์ ์ธ ์‹ค๋‚ด๊ณต๊ธฐ์งˆ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์ข…์‚ฌ์ž๋“ค์ด ๊ฒฝํ—˜ํ•˜๋Š” ์‹ค๋‚ด์ž๊ฐ์ฆ์ƒ์„ ์กฐ์‚ฌํ•˜๊ณ , ๊ฐ ํŠน์„ฑ์„ ๋Œ€๋ณ€ํ•˜๋Š” ๋ณ€์ˆ˜๋“ค๊ณผ์˜ ๊ด€๋ จ์„ฑ์„ ํ‰๊ฐ€ํ•˜์—ฌ ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์˜ ์‹ค๋‚ดํ™˜๊ฒฝ ๊ฐœ์„ ์„ ๋„๋ชจํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์„œ์šธ์‹œ๋‚ด์— ์†Œ์žฌํ•œ ์„ธ ๊ฐœ์˜ ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์› ์ข…์‚ฌ์ž 682๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜์—ฌ 2004๋…„ 9์›” 20์ผ๋ถ€ํ„ฐ 10์›” 8์ผ๊นŒ์ง€ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ ์ง€ํ‘œ๋กœ๋Š” THI(Todai Health Index)์˜ ๋ฌธํ•ญ ์ค‘ ๋นŒ๋”ฉ์ฆํ›„๊ตฐ๊ณผ ๊ด€๋ จํ•œ 39๋ฌธํ•ญ์„ ๋ฐœ์ทŒํ•˜์—ฌ ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ, ํ†ต๊ณ„๋ถ„์„์€ SAS 8.01 ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•˜์—ฌ t-test, ๋ถ„์‚ฐ๋ถ„์„ ๋ฐ ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์› ์ข…์‚ฌ์ž๋“ค์€ ๋นŒ๋”ฉ ๋‚ด ์†Œ์Œ, ๋ถˆ์ถฉ๋ถ„ํ•œ ํ™˜๊ธฐ์ƒํƒœ, ๋จผ์ง€ ๋ฐ ๊ฑด์กฐํ•จ์œผ๋กœ ์ธํ•ด ์น˜๊ณผ๋ณ‘์› ๋‚ด ์‹ค๋‚ดํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์ธ์ง€๋„๋ฅผ ๋‚ฎ๊ฒŒ ํ‰๊ฐ€ํ•˜๊ณ  ์žˆ์—ˆ๋‹ค. ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ผ๋ฐ˜์  ํŠน์„ฑ๊ณผ ๊ด€๋ จํ•œ ์š”์ธ์œผ๋กœ๋Š” ์„ฑ๋ณ„, ์ง์ข…, ๊ทผ๋ฌด๋…„์ˆ˜, ์—…๋ฌด๋งŒ์กฑ, ์ˆ˜๋ฉด์‹œ๊ฐ„, ์ฝ˜ํ…ํŠธ๋ Œ์ฆˆ ์ฐฉ์šฉ์—ฌ๋ถ€๊ฐ€ ์˜๋ฏธ ์žˆ๋Š” ๋ณ€์ˆ˜๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋‚จ์ž์— ๋น„ํ•ด ์—ฌ์ž๊ฐ€, ์ผ๋ฐ˜์‚ฌ๋ฌด์ง์— ๋น„ํ•ด ์น˜๊ณผ์˜์‚ฌ๊ฐ€, ์˜ค๋ž˜ ๊ทผ๋ฌดํ•œ ์ข…์‚ฌ์ž๋ณด๋‹ค 1๋…„ ๋ฏธ๋งŒ์˜ ์ข…์‚ฌ์ž๊ฐ€, ์—…๋ฌด์— ๋งŒ์กฑํ•œ๋‹ค๊ณ  ์‘๋‹ตํ•œ ์ข…์‚ฌ์ž๋ณด๋‹ค ๋งŒ์กฑํ•˜์ง€ ์•Š๋Š”๋‹ค๊ณ  ์‘๋‹ตํ•œ ์ข…์‚ฌ์ž๊ฐ€, ๊ทธ๋ฆฌ๊ณ  ์ˆ˜๋ฉด์‹œ๊ฐ„์ด ์ ์„์ˆ˜๋ก, ์ฝ˜ํ…ํŠธ๋ Œ์ฆˆ๋ฅผ ์ฐฉ์šฉํ• ์ˆ˜๋ก ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ ํ‰๊ท  ์ ์ˆ˜๊ฐ€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๋‹ค. ๊ทผ๋ฌด์กฐ๊ฑด, ๊ฑด๋ฌผ ๋ฐ– ์™ธ์ถœํšŸ์ˆ˜, ์—ฌ๋ฆ„๊ณผ ๊ฒจ์šธ ์ž์—ฐํ™˜๊ธฐ, ์‹ค๋‚ด๊ณต๊ธฐํ™˜๊ฒฝ๊ณผ ๊ฐ™์€ ์ผ๋ฐ˜์  ๊ทผ๋ฌดํ™˜๊ฒฝ๊ณผ ๊ด€๋ จํ•œ ์š”์ธ๋„ ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ง„๋ฃŒ์‹ค์—์„œ ๊ทผ๋ฌดํ• ์ˆ˜๋ก, ๊ฑด๋ฌผ ๋ฐ– ์™ธ์ถœํšŸ์ˆ˜๊ฐ€ ์ ์„์ˆ˜๋ก, ์ž์—ฐํ™˜๊ธฐ ํšŸ์ˆ˜๊ฐ€ ์ ์„์ˆ˜๋ก, ์‹ค๋‚ด๊ณต๊ธฐ๊ฐ€ ๋ถˆ์พŒํ•˜๋‹ค๊ณ  ๋Š๋‚„์ˆ˜๋ก ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ ํ‰๊ท ์ ์ˆ˜๊ฐ€ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๋‹ค. ์น˜๊ณผ์˜๋ฃŒ ํ–‰์œ„์™€ ๊ด€๋ จ๋œ ์ง„๋ฃŒํ™˜๊ฒฝ ์ค‘์—์„œ๋Š” ์†Œ๋…์šฉ์•Œ์ฝœ๊ณผ ๋ ˆ์ง„๋ฅ˜(monomerํฌํ•จ)์‚ฌ์šฉ ์œ ๋ฌด๊ฐ€ ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ณ€์ˆ˜๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ด์ƒ์˜ ์—ฐ๊ตฌ์— ์˜ํ•˜๋ฉด, ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์›์€ ํŠน์ˆ˜ํ•œ ์น˜๊ณผ์˜๋ฃŒ ํ–‰์œ„๋กœ ์ธํ•ด ๋งŽ์€ ์†Œ์Œ, ๋ถ„์ง„ ๋ฐ ์•…์ทจ๋ฅผ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ๋Š” ์‹ค๋‚ดํ™˜๊ฒฝ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ์กฐ์‚ฌ๋˜์—ˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์‹ค๋‚ดํ™˜๊ฒฝ ์š”์ธ๋“ค์ด ์น˜๊ณผ๋Œ€ํ•™๋ณ‘์› ์ข…์‚ฌ์ž๋“ค์ด ๋Š๋ผ๋Š” ๋นŒ๋”ฉ๊ด€๋ จ ๊ฑด๊ฐ•์ž๊ฐ์ฆ์ƒ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ์—ˆ๋‹ค. ์ด์— ์น˜๊ณผ์˜๋ฃŒ ํ–‰์œ„์™€ ๊ด€๋ จ๋œ ํŠน์ˆ˜ํ•œ ์‹ค๋‚ดํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์ ์ ˆํ•œ ๊ด€๋ฆฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค๊ณ  ๋ณธ๋‹ค. [์˜๋ฌธ]Indoor air pollution has become a big concern at dental college hospitals, because patients are crowded and they have more harmful conditions than other buildings. In this study, building-related health recognition symptoms of various workers in dental college hospitals are surveyed and analyzed in order to improve indoor environment at dental college hospitals. The sample of this study is 682 workers in three dental college hospitals located in Seoul from September 20 to October 8, 2004. Sampled workers respond 39 Sick Building Syndrome-related items selected from Todai Health Index(THI), and the models of t-test, ANOVA, and multiple regression are applied for statistical analysis by using version sas 8.01. Most workers at dental hospitals complained about noise, poor ventilation, lots of dust, and air dryness. Building-related health recognition symptoms are significantly related to gender, tasks, working experience, job-satisfaction, sleeping hours and wearing contact lens. Females rather than males, dentists rather than office workers, less-than-1-year workers rather than more-than-1-year workers, less sleeping workers, less satisfied workers, and workers wearing contact lens tend to report more building-related health recognition symptoms. Also working places and ventilation are significantly related to the symptom. That is, workers report more building-related health recognition symptoms when working at a treatment office, less going out of a building, having less natural ventilation, and feeling uncomfortable about indoor air. Building-related health recognition symptoms scores are significantly high as using sterilization alcohol and resin type materials(including monomer). Based on the results, it can be said that special dental treatment causes undesirable environment such as noise, dust, and bad smell. It is also related to building related health recognition symptoms reported by workers at dental hospitals. So managemental efforts are needed to improve indoor environment which is related dental treatment. Keywords:sick building syndrome, indoor air quality, building related health recognition symptoms, natural ventilation.ope

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    A Study on Vocabulary Inference Strategy Education For Chinese Korean Learner

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฌ๋ฒ”๋Œ€ํ•™ ๊ตญ์–ด๊ต์œก๊ณผ(ํ•œ๊ตญ์–ด๊ต์œก์ „๊ณต),2020. 2. ๋ฏผํ˜„์‹.ํ•œ๊ตญ์–ด ํ•™์Šต์ž๊ฐ€ ์ˆ™๋‹ฌ๋„๊ฐ€ ์˜ฌ๋ผ๊ฐ์— ๋”ฐ๋ผ ๋ฐฉ๋Œ€ํ•œ ์–‘์˜ ๋‚ฏ์„  ์–ดํœ˜๋“ค์„ ๋งˆ์ฃผํ•˜๊ฒŒ ๋œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ์–ดํœ˜์˜ ๊ต์ˆ˜ยทํ•™์Šต์€ ๊ต์‚ฌ์˜ ์ง์ ‘ ์ง€๋„ ํ˜น์€ ์‚ฌ์ „ ์ฐพ๊ธฐ, ์•”๊ธฐ ๋“ฑ์„ ์ค‘์‹ฌ์œผ๋กœ ์ด๋ฃจ์–ด์ง„๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•™์Šต์ž๊ฐ€ ์ ‘ํ•˜๋Š” ๋ชจ๋“  ์–ดํœ˜์˜ ํ•™์Šต์„ ์ง์ ‘์ ์ด๊ณ  ๋ช…์‹œ์ ์ธ ๋ฐฉ๋ฒ•์—๋งŒ ์˜์กดํ•˜๊ธฐ์—๋Š” ์‹œ๊ฐ„์  ํ•œ๊ณ„๊ฐ€ ์žˆ์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์–ดํœ˜๊ฐ€ ์ฒ˜ํ•œ ๋‹ค์–‘ํ•œ ๋ฌธ๋งฅ์— ๋”ฐ๋ฅธ ์˜๋ฏธ๋“ค์„ ๋‘๋ฃจ ํŒŒ์•…ํ•˜๋Š” ๋ฐ์—๋Š” ์–ด๋ ค์›€์ด ์žˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•™์Šต์ž๋“ค์ด ๋Šฅ๋™์ ์œผ๋กœ ๋‚ฏ์„  ์–ดํœ˜์˜ ์˜๋ฏธ ํ•™์Šต์„ ๋ณด์กฐํ•  ์ˆ˜ ์žˆ๋Š” ํ•œ ๋ฐฉ์•ˆ์œผ๋กœ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์— ์ฃผ๋ชฉํ•˜๊ณ , ํ•™์Šต์ž๋“ค์ด ์ฐธ๊ณ ํ•  ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ๊ต์œก๋ฐฉ์•ˆ์„ ๋งˆ๋ จํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์€ ๋‚ฏ์„  ์–ดํœ˜์˜ ์˜๋ฏธ๋ฅผ ํ˜•์„ฑํ•˜๋Š” ๋ฐ ์˜ํ–ฅ์„ ์ฃผ๋Š” ๋‹ค์–‘ํ•œ ์š”์ธ๋“ค์„ ํ† ๋Œ€๋กœ ๊ทธ ์˜๋ฏธ๋ฅผ ํŒŒ์•…ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ๋งํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ „๋žต์—๋Š” ๋‹ค์–‘ํ•œ ๊ฐˆ๋ž˜๊ฐ€ ์žˆ์ง€๋งŒ, ๋ณธ๊ณ ์—์„œ๋Š” ๊ถ๊ทน์ ์œผ๋กœ ์ด๋Ÿฌํ•œ ์ „๋žต์„ ํ™œ์šฉํ•˜์—ฌ ์ž๊ธฐ์ฃผ๋„์ ์ธ ์–ดํœ˜ ํ•™์Šต์„ ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•˜์˜€์œผ๋ฏ€๋กœ, ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ๋ฒ”์œ„๋ฅผ ์ฝ๊ธฐ ํ…์ŠคํŠธ ์ƒ์˜ ๋‹จ์„œ๋ฅผ ํ™œ์šฉํ•œ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์œผ๋กœ ํ•œ์ •ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ด€์‹ฌ์„ ๋ฐ”ํƒ•์œผ๋กœ ๋จผ์ € ์–ดํœ˜๋ ฅ์˜ ๊ฐœ๋…๊ณผ ๊ตฌ์„ฑ์š”์†Œ๋ฅผ ์‚ดํŽด๋ด„์œผ๋กœ์จ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ์ด๋ก ์  ํ† ๋Œ€๋ฅผ ๋งˆ๋ จํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋‚˜์•„๊ฐ€ ์„ ํ–‰ ์—ฐ๊ตฌ์—์„œ ์ œ์‹œ๋œ ๋‹ค์–‘ํ•œ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ๊ฐœ๋…๊ณผ ๋ถ„๋ฅ˜๋ฅผ ์ •๋ฆฌํ•˜์—ฌ ํ•™์Šต์ž๋“ค์˜ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ์‚ฌ์šฉ ์–‘์ƒ์„ ํŒŒ์•…ํ•˜๋Š”๋ฐ ์ฐธ๊ณ ํ•  ๋งŒํ•œ ๊ธฐ์ค€์„ ์„ค์ •ํ•˜์˜€๋‹ค. ๋˜ ์‹ค์ œ ํ•œ๊ตญ์–ด ์–ดํœ˜ ๊ต์œก์—์„œ ์–ดํœ˜ ์ „๋žต์ด ์–ด๋–ป๊ฒŒ ์ œ์‹œ๋˜๋Š”์ง€๋ฅผ ์‚ดํ”ผ๊ธฐ ์œ„ํ•ด ์ค‘๊ตญ์–ด๊ถŒ ํ•™์Šต์ž์™€ ๊ต์‚ฌ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค. ์ „๋ฐ˜์ ์œผ๋กœ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์— ๋Œ€ํ•œ ๊ต์œก์ด ์ผ๋ถ€ ๊ธฐ๋Šฅ ์˜์—ญ์—์„œ, ํ˜น์€ ๊ต์‚ฌ์˜ ์žฌ๋Ÿ‰์— ๋”ฐ๋ผ ์ œ์‹œ๋˜๊ณ  ์žˆ๊ธฐ๋Š” ํ•˜๋‚˜, ๋ณธ๊ฒฉ์ ์œผ๋กœ๋Š” ๋‹ค๋ฃจ์–ด์ง€์ง€ ์•Š๊ณ  ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ต์‚ฌ์™€ ํ•™์Šต์ž๋“ค์€ ๋ชจ๋‘ ์ „๋žต์„ ํ™œ์šฉํ•œ ๋‚ฏ์„  ์–ดํœ˜์˜ ์˜๋ฏธ ์ถ”๋ก  ์ „๋žต์ด ์œ ์šฉํ•˜๋ฉฐ, ๊ต์‹ค ์ˆ˜์—…์—์„œ ํ•„์š”ํ•˜๋‹ค๊ณ  ์‘๋‹ตํ•˜์˜€๊ณ , ๋ณธ๊ณ ์—์„œ๋Š” ์ด๋ฅผ ํ†ตํ•ด ํ•œ๊ตญ์–ด ๊ต์œก์—์„œ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ํ•„์š”์„ฑ๊ณผ ์ด๋Ÿฌํ•œ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์— ๋‚˜์•„๊ฐ€์•ผ ํ•  ๋ฐฉํ–ฅ์— ๋Œ€ํ•ด ์„ค์ •ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ตฌ์ฒด์ ์œผ๋กœ ์–ด๋–ค ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์„ ๊ต์ˆ˜ํ•ด์•ผ ํ• ์ง€๋ฅผ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด ์ค‘๊ตญ์–ด๊ถŒ ํ•™์Šต์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์–ดํœ˜ ์ถ”๋ก  ํ…Œ์ŠคํŠธ๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๊ฐ ์ „๋žต์˜ ์œ ํ˜•๊ณผ ํŠน์ง•์„ ๋ฐํžˆ๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์ค‘๊ตญ์–ด๊ถŒ ํ•™์Šต์ž๊ฐ€ ํ•œ๊ตญ์–ด ๋ฌธ๋งฅ์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๋‚ฏ์„  ์–ดํœ˜์˜ ์˜๋ฏธ๋ฅผ ์ถ”๋ก ํ•  ๋•Œ ์‚ฌ์šฉํ•˜๋Š” ์ „๋žต์ƒ์˜ ๋ฌธ์ œ์ ์„ ํŒŒ์•…ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ํ•™์Šต์ž ์ง‘๋‹จ์„ ์„ฑ๊ณต์ ์œผ๋กœ ์–ดํœ˜ ์˜๋ฏธ๋ฅผ ์ถ”๋ก ํ–ˆ๋Š”์ง€์˜ ์—ฌ๋ถ€์— ๋”ฐ๋ผ ์ƒ์œ„ ํ•™์Šต์ž์™€ ํ•˜์œ„ ํ•™์Šต์ž๋กœ ํฌ๊ฒŒ ๋‚˜๋ˆ„์–ด ๋ณด์•˜๋‹ค. ํ•˜์œ„ ํ•™์Šต์ž๋“ค์˜ ์ฃผ๋œ ์–ดํœ˜ ์ถ”๋ก  ์‹คํŒจ์˜ ์›์ธ์€ โ‘ ์ „๋žต์— ๋Œ€ํ•œ ์ดํ•ด์˜ ๋ถ€์กฑ์œผ๋กœ ์ธํ•œ ์˜ค์šฉ, โ‘ก์ถ”๋ก ํ•œ ๋ชฉํ‘œ ์˜๋ฏธ์˜ ๊ณผ์ž‰ ์ผ๋ฐ˜ํ™”์— ์˜ํ•œ ์˜ค์šฉ, โ‘ข ๊ฐ€์ •-๊ฒ€์ฆ ๊ณผ์ •์˜ ๋ถ€์žฌ ๋“ฑ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๋˜ ์ค‘๊ตญ์–ด๊ถŒ ์ค‘๊ณ ๊ธ‰ ํ•™์Šต์ž๋“ค์ด ์šฐ์„ ์ ์œผ๋กœ ํ•™์Šตํ•ด์•ผ ํ•  ์ „๋žต์œผ๋กœ ์–ดํœ˜์˜ ํ˜•ํƒœ์†Œ๋ฅผ ๋ถ„์„ํ•˜๋Š” ํ˜•ํƒœ์†Œ ๋ถ„์„ ์ „๋žต, ์–ดํœ˜์˜ ์˜๋ฏธ ์—ฐ๊ฒฐ๋ง์„ ํ™œ์šฉํ•˜๋Š” ์–ดํœ˜ ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต, ํ…์ŠคํŠธ ๋‚ด์˜ ๋‹ดํ™” ํ‘œ์ง€, ๋ฌธ์žฅ์˜ ์œ„์น˜ ๋“ฑ์„ ํ™œ์šฉํ•œ ๋‹ดํ™” ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต์œผ๋กœ ์ •๋ฆฌํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋ณธ๊ณ ์—์„œ๋Š” ์ค‘๊ตญ์–ด๊ถŒ ์ค‘๊ณ ๊ธ‰ ํ•™์Šต์ž๋ฅผ ์œ„ํ•œ ๊ต์œก ๋‚ด์šฉ์„ ์„ค๊ณ„ํ•˜๊ณ , ์ „๋žต ์ค‘์‹ฌ ์ง€๋„๋ฒ•(Style and Strategy Based Instruction) ๋ชจํ˜•์„ ํ™œ์šฉํ•˜์—ฌ ๊ต์ˆ˜ํ•™์Šต ๋ฐฉ์•ˆ์„ ๊ตฌ์•ˆํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ค‘๊ตญ์–ด๊ถŒ ์ค‘๊ณ ๊ธ‰ ํ•œ๊ตญ์–ด ํ•™์Šต์ž์˜ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ์‚ฌ์šฉ ์–‘์ƒ์„ ์–ด์ข…๋ณ„๋กœ, ๊ตญ๊ฐ€ ๋ณ„๋กœ ๋‚˜๋ˆ„์–ด ์‚ดํŽด๋ณด์•˜๋‹ค๋Š” ์ , ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ๋ถ„์„์„ ํ† ๋Œ€๋กœ ํ•™์Šต์ž๋“ค์ด ๋‚ฏ์„  ์–ดํœ˜์˜ ์˜๋ฏธ๋ฅผ ์ถ”๋ก ํ•˜๋Š” ๋ฐ ์ฐธ๊ณ ํ• ๋งŒํ•œ ๊ต์œก ๋ฐฉ์•ˆ์„ ์ œ์•ˆํ•˜์˜€๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ์žˆ๋‹ค.As Korean learners become more proficient, they face a huge amount of unfamiliar vocabulary. Teaching and learning of these words is centered on direct teacher guidance, dictionary search, memorization, etc. However, not only is there a time limit for learners to rely on direct and explicit methods of learning all the words they encounter, but there are also difficulties in grasping the meanings of the various contexts in which the vocabulary is in its various contexts. The purpose of this study was to focus on vocabulary reasoning strategies as a way to assist learners in learning the meaning of words that are not actively familiar to learners, and to prepare education methods for vocabulary reasoning strategies to be referenced by learners. vocabulary inference strategy refers to how to grasp the meaning based on various factors that influence the formation of the meaning of unfamiliar vocabulary. Although there are many different branches of these strategies, the scope of the vocabulary inference strategy was limited to the lexical reasoning strategy using the clues in the reading text, since the original goal was ultimately to take advantage of these strategies for self-directed vocabulary learning. Based on this interest, we first looked at the concepts and components of vocabulary to lay the theoretical foundation for our vocabulary inference strategy. Furthermore, the concepts and classifications of various lexical reasoning strategies presented in the preceding study were compiled to establish a basis for reference in identifying the use patterns of the learners' vocabulary reasoning strategies. We also conducted a survey of Chinese learners and teachers to examine how vocabulary strategies are presented in actual Korean vocabulary education. Overall, it has been confirmed that training on vocabulary inference strategies is not being addressed in full swing, although it is presented in some functional areas or at the discretion of teachers. Teachers and learners all responded that the strategy for inferring meaning of unfamiliar vocabulary using strategies was useful and needed in classroom classes, which allowed us to set up the need for a strategy for reasoning words in Korean language education and the direction in which we should move forward with these vocabulary inference strategies. In addition, a vocabulary inference test was conducted on Chinese learners to find out which vocabulary inference strategies should be taught specifically. The types and characteristics of each strategy were revealed, and the purpose was to identify the strategic problems that Chinese learners use when inferring the meaning of unfamiliar words in the Korean context. To analyze the results of the experiment, a large group of learners was divided into upper and lower learners depending on whether they successfully deduced the meaning of the vocabulary. The main reasons for the failure of vocabulary inference by lower learners were found to be misuse due to a lack of understanding of the first strategy, misuse by excessive generalization of the meaning of the two inferring goals, and absence of the 3 family-verification process. In addition, it was outlined as a plot analysis strategy that analyzes the morphology of vocabulary as a strategy that Chinese intermediate and advanced learners should learn first, strategies to utilize vocabulary clues using a network of meanings, and strategies to utilize discourse signs and sentence locations within text. Based on these results, we designed the educational content for intermediate and advanced Chinese learners and designed the teaching method using the Style and Strategy Based Instrumentation model. The study is meaningful in that it looked at the use of the vocabulary inference strategy of Chinese-speaking intermediate and advanced level Korean learners by fish species and countries, and based on this analysis, it suggested educational methods that learners can use to infer the meaning of unfamiliar vocabulary.โ… . ์„œ๋ก  1 1. ๋ฌธ์ œ ์ œ๊ธฐ ๋ฐ ์—ฐ๊ตฌ์˜ ๋ชฉ์  1 2. ์„ ํ–‰ ์—ฐ๊ตฌ 3 2.1. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ๊ฐœ๋…๊ณผ ๋ถ„๋ฅ˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ 4 2.2. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต ์ง€๋„๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ 7 3. ์—ฐ๊ตฌ ๋Œ€์ƒ ๋ฐ ๋ฐฉ๋ฒ• 10 3.1. ์—ฐ๊ตฌ ๋Œ€์ƒ 10 3.2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 13 (1) ๋ชฉํ‘œ ์–ดํœ˜ ์„ ์ •ํ‰๊ฐ€ 14 (2) ์–ดํœ˜ ์ถ”๋ก  ์‹คํ—˜์ง€ 17 โ…ก. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ์ด๋ก ๊ณผ ๊ต์œก์˜ ํ˜„ํ™ฉ 19 1. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ์ด๋ก  19 1.1. ์–ดํœ˜๋ ฅ์˜ ๊ฐœ๋…๊ณผ ๊ตฌ์„ฑ์š”์†Œ 19 1.2. ๋ฌธ๋งฅ์„ ํ†ตํ•œ ์–ดํœ˜ ํ•™์Šต์˜ ๊ฐœ๋… 22 1.3. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ๊ฐœ๋…๊ณผ ์ข…๋ฅ˜ 25 2. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ๊ต์œก ํ˜„ํ™ฉ ๊ฒ€ํ†  33 2.1. ๊ต์‚ฌ ์„ค๋ฌธ 34 2.2. ํ•™์Šต์ž ์„ค๋ฌธ 42 โ…ข. ์ค‘๊ตญ์–ด๊ถŒ ํ•™์Šต์ž์˜ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต ์‚ฌ์šฉ ์–‘์ƒ 51 1. ํ•™์Šต์ž์˜ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์˜ ์œ ํ˜• 51 1.1. ์Œ์„ฑ ๋ฐ ํ‘œ๊ธฐ ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต 54 (1) ์ค‘๊ตญ์–ด ๋ฐœ์Œ์˜ ์œ ์‚ฌ์„ฑ ํ™œ์šฉํ•˜๊ธฐ 54 (2) ํ•œ๊ตญ์–ด ๋ฐœ์Œ ๋ฐ ํ‘œ๊ธฐ์˜ ์œ ์‚ฌ์„ฑ ํ™œ์šฉํ•˜๊ธฐ 56 (3) ์™ธ๊ตญ์–ด ๋ฐœ์Œ์˜ ์œ ์‚ฌ์„ฑ ํ™œ์šฉํ•˜๊ธฐ 58 1.2. ์–ดํœ˜ ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต 59 (1) ์˜๋ฏธ์†Œ ๋ถ„์„ํ•˜๊ธฐ 59 (2) ์–ดํœ˜์˜ ์˜๋ฏธ ๊ด€๊ณ„ ํ™œ์šฉํ•˜๊ธฐ 61 (3) ์ฃผ๋ณ€ ๋‹จ์–ด ํ™œ์šฉํ•˜๊ธฐ 64 1.3. ํ†ต์‚ฌ ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต 66 (1) ํ’ˆ์‚ฌ ๋ถ„์„ํ•˜๊ธฐ 66 (2) ์—ฐ์–ด ๋‹จ์„œ ํ™œ์šฉํ•˜๊ธฐ 67 1.4. ๋‹ดํ™” ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต 69 (1) ์˜ˆ์‹œยท์„ค๋ช… ์ฐพ๊ธฐ 69 (2) ๋…ผ๋ฆฌ์  ์ „๊ฐœ์™€ ํ๋ฆ„ ํ™œ์šฉํ•˜๊ธฐ 70 (3) ๋ฐฐ๊ฒฝ ์ง€์‹ ํ™œ์šฉํ•˜๊ธฐ 72 2. ํ•™์Šต์ž์˜ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์–‘์ƒ๊ณผ ์ฐจ์ด 74 2.1. ์–ด์ข…๋ณ„ ์ „๋žต ์‚ฌ์šฉ ์–‘์ƒ์˜ ์ฐจ์ด 79 (1) ํ•œ์ž์–ด 80 (2) ๊ณ ์œ ์–ด 87 (3) ์™ธ๋ž˜์–ด 94 2.2. ํ•™์Šต์ž ๊ตญ์ ์— ๋”ฐ๋ฅธ ์ „๋žต ์‚ฌ์šฉ ์–‘์ƒ์˜ ์ฐจ์ด 98 3. ๋…ผ์˜ ๋ฐ ๊ต์œก์  ์‹œ์‚ฌ์  100 โ…ฃ. ํ•œ๊ตญ์–ด ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต ๊ต์œก์˜ ์‹ค์ œ 104 1. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต ๊ต์œก์˜ ๋ชฉ์ ๊ณผ ๋ชฉํ‘œ 104 2. ์ค‘๊ตญ์–ด๊ถŒ ํ•™์Šต์ž์˜ ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต ๊ต์œก ๋‚ด์šฉ๊ณผ ๋ฐฉ๋ฒ• 107 2.1. ํ˜•ํƒœ์†Œ ๋ถ„์„ ์ „๋žต์˜ ์ œ์‹œ ๋ฐฉ๋ฒ• 109 2.2. ์–ดํœ˜ ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต์˜ ์ œ์‹œ ๋ฐฉ๋ฒ• 112 2.3. ๋ฌธ๋งฅ ๋‹จ์„œ ํ™œ์šฉ ์ „๋žต์˜ ์ œ์‹œ ๋ฐฉ๋ฒ• 113 2.4. ์ดˆ์ธ์ง€์  ์ „๋žต์˜ ์ œ์‹œ ๋ฐฉ๋ฒ• 115 3. ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต ๊ต์œก์˜ ์‹ค์ œ 118 3.1. ์ „๋žต ์ค€๋น„(Strategy Preparation) 119 3.2. ์ „๋žต ์ž๊ฐ€ ์ธ์‹ ํ•จ์–‘(Strategy Awareness-Raising) 120 3.3. ์ „๋žต ํ›ˆ๋ จ(Strategy Training) 122 3.4. ์ „๋žต ์—ฐ์Šต(Strategy Practice) 124 3.5. ์ „๋žต ๊ฐœ์ธํ™”(Personalization of Strategies) 126 โ…ค. ๊ฒฐ๋ก  128 ์ฐธ๊ณ ๋ฌธํ—Œ 131 ๋ถ€๋ก1 ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต์— ๊ด€ํ•œ ์„ค๋ฌธ ์กฐ์‚ฌ์ง€ 139 ๋ถ€๋ก2 ์–ดํœ˜ ์ถ”๋ก  ์ „๋žต ํ…Œ์ŠคํŠธ 144 Abstract 149Maste
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