54 research outputs found

    An Integrated Problem Solving Environment for Numerical Study of Mechanical Aerospace Application

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    ๊ณผํ•™์—ฐ๊ตฌ ๋ถ„์•ผ์™€ IT ๊ธฐ์ˆ ์„ ์œตํ•ฉํ•˜์—ฌ ์—ฐ๊ตฌ์˜ ์ƒ์‚ฐ์„ฑ์„ ๋†’์ด๊ณ ์ž ํ•˜๋Š” e-์‚ฌ์ด์–ธ์Šค ํ™˜๊ฒฝ ๊ตฌ์ถ•์ด ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ํ™œ๋ฐœํ•˜๊ฒŒ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‘์šฉ๋งˆ๋‹ค e-์‚ฌ์ด์–ธ์Šค ์ „์šฉ ํ™˜๊ฒฝ ๊ตฌ์ถ•์œผ๋กœ ์ธํ•ด ๊ณตํ†ต์˜ ์ธํ„ฐํŽ˜์ด์Šค์˜ ๋ถ€์žฌ๋กœ ๊ฐ๊ฐ์˜ ์‘์šฉ๋“ค์ด ์œ ์‚ฌํ•จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๊ฐœ๋ฐœ๋œ ๊ธฐ์ˆ ์˜ ๊ณต์œ ์™€ ์žฌ์‚ฌ์šฉ์„ ๊ธฐ๋Œ€ํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ๋”ฐ๋ผ์„œ e-์‚ฌ์ด์–ธ์Šค ์‘์šฉ ๊ธฐ์ˆ ์˜ ์ง€์†์ ์ธ ๋ฐœ์ „์„ ์œ„ํ•ด์„œ๋Š” ์‘์šฉ ๊ธฐ์ˆ ๋“ค ๊ฐ„ ํ‘œ์ค€ํ™”๋œ ์„œ๋น„์Šค๋ฅผ ํ†ตํ•˜์—ฌ ๋‹จ์ผ ํ™˜๊ฒฝ์—์„œ์˜ ์‹คํ—˜ํ™˜๊ฒฝ์ด ์ œ๊ณต๋˜์–ด์•ผ ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ˆ˜์น˜ํ•ด์„ ๊ธฐ๋ฒ•์„ ์—ฐ๊ตฌํ•˜๋Š” 3๊ฐœ์˜ ๊ณผํ•™ ์‘์šฉ ๋ถ„์•ผ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์‘์šฉ๋งˆ๋‹ค ์œ ์‚ฌํ•˜๊ฒŒ ์ ์šฉ๋˜๋Š” ์ˆ˜๋ฆฌ๊ณผํ•™ ํ˜„์ƒ์„ ํ•ด์„ํ•˜๊ธฐ ์œ„ํ•œ UNICORE ๊ธฐ๋ฐ˜์˜ ๊ธฐ๋ณธํ˜• ํ†ตํ•ฉ ์—ฐ๊ตฌ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค.๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ์—ฐ๊ตฌ์žฌ๋‹จ์„ ํ†ตํ•ด ๊ต์œก๊ณผํ•™๊ธฐ์ˆ ๋ถ€์˜ ์šฐ์ฃผ๊ธฐ์ดˆ์›์ฒœ๊ธฐ์ˆ ๊ฐœ๋ฐœ ์‚ฌ์—…(NSL, National Space Lab, ๊ณผ์ œ๋ฒˆํ˜ธ 20090091724), 2010 ๋…„๋„ ์ •๋ถ€(๊ต์œก๊ณผํ•™๊ธฐ์ˆ ๋ถ€)์˜ ์žฌ์›์œผ๋กœ ๊ตญ๊ฐ€์ˆ˜๋ฆฌ๊ณผํ•™์—ฐ๊ตฌ์†Œ์˜ ์ฃผ์š”์‚ฌ์—… (No. A21001), ๊ตญํ† ํ•ด์–‘๋ถ€ ๊ฑด์„ค๊ธฐ์ˆ ํ˜์‹ ์‚ฌ์—… ์ดˆ์žฅ๋Œ€๊ต๋Ÿ‰์‚ฌ์—…๋‹จ(08 ๊ธฐ์ˆ ํ˜์‹  E01) ๋ฐ ๊ตญ๋ฐฉ๊ณผํ•™์—ฐ๊ตฌ์†Œ ์žฅ๊ธฐ๊ธฐ์ดˆ์—ฐ๊ตฌ์‚ฌ์—…์˜ ์ง€์›์œผ๋กœ๋ถ€ํ„ฐ ์ง€์›๋ฐ›์•„ ์ˆ˜ํ–‰๋˜์—ˆ์Œ.OAIID:oai:osos.snu.ac.kr:snu2010-01/104/0000004648/35SEQ:35PERF_CD:SNU2010-01EVAL_ITEM_CD:104USER_ID:0000004648ADJUST_YN:NEMP_ID:A001138DEPT_CD:446CITE_RATE:0FILENAME:๊ธฐ๊ณ„์šฐ์ฃผ์‘์šฉ_์ˆ˜์น˜ํ•ด์„์„_์œ„ํ•œ_ํ†ตํ•ฉํ˜•_๋ฌธ์ œํ’€์ดํ™˜๊ฒฝ.pdfDEPT_NM:๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€EMAIL:[email protected]:

    An e-Science Experiment Framework based on UNICORE for Numerical Analysis

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    ์œ ๋™ ๋ถ„์•ผ์˜ ์‹คํ—˜์€ ์ฃผ๋กœ ๋ณต์žกํ•œ ์ˆ˜์น˜ํ•ด์„ ๋ฐฉ์ •์‹์˜ ๊ณ„์‚ฐ ๊ณผ์ •์œผ๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ์œผ๋ฏ€๋กœ ๊ณ ์„ฑ๋Šฅ ์ปดํ“จํŒ…์ด ๊ฐ€๋Šฅํ•œ ๊ฑฐ๋Œ€ํ•œ ๊ณ„์‚ฐ ์ž์›์„ ์š”๊ตฌํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ˆ˜์น˜ํ•ด์„์ด๋‚˜ ์œ ๋™ ๋“ฑ ๊ฐ๊ฐ์˜ ์‘์šฉ์„ ์œ„ํ•œ e-์‚ฌ์ด์–ธ์Šค ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ์ง„ํ–‰๋˜๊ณ  ์žˆ์œผ๋‚˜, ๋‹ค์–‘ํ•œ ์œ ๋™ ํ•ด์„์„ ์œ„ํ•œ ์ˆ˜์น˜ํ•ด์„ ์—ฐ๊ตฌ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๊ฐœ๋ฐœํ•œ ์‚ฌ๋ก€๋Š” ๋“œ๋ฌผ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ทธ๋ฆฌ๋“œ์ž์›์„ ํšจ์œจ์ ์œผ๋กœ ์ด์šฉํ•  ์ˆ˜ ์žˆ๋Š” UNICORE ๋ฆฌ์น˜ ํด๋ผ์ด์–ธํŠธ(URC)๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ณ ์† ์œ ๋™, ๋‚œ๋ฅ˜ ์œ ๋™, ๋‹ค์ƒ ์œ ๋™์˜ ์„ธ ๊ฐ€์ง€ ์œ ๋™ ์‘์šฉ์— ๋Œ€ํ•œ ์ˆ˜์น˜ ํ•ด์„ ์—ฐ๊ตฌ๋ฅผ ๋‹จ์ผ ํ™˜๊ฒฝ์—์„œ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” e-์‚ฌ์ด์–ธ์Šค ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค.OAIID:oai:osos.snu.ac.kr:snu2011-01/104/0000004648/35SEQ:35PERF_CD:SNU2011-01EVAL_ITEM_CD:104USER_ID:0000004648ADJUST_YN:NEMP_ID:A001138DEPT_CD:446CITE_RATE:0FILENAME:์œ ๋‹ˆ์ฝ”์–ด_๊ธฐ๋ฐ˜_์ˆ˜์น˜ํ•ด์„_์‹คํ—˜์„_์œ„ํ•œ_e-์‚ฌ์ด์–ธ์Šค_ํ”„๋ ˆ์ž„์›Œํฌ.pdfDEPT_NM:๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€EMAIL:[email protected]:

    A Web-based Workflow Environment for CFD Analysis and Design

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    ์ปดํ“จํ„ฐ ์ธํ”„๋ผ์˜ ๋น ๋ฅธ ๋ฐœ์ „๊ณผ ์ „์‚ฐ ๊ธฐ๋ฒ•์˜ ๋ฐœ๋‹ฌ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๊ฐœ๊ฐœ์ธ์˜ ๊ณผํ•™ ์‘์šฉ ์—ฐ๊ตฌ์ž ์ธก๋ฉด์—์„œ๋Š” ์—ฌ์ „ํžˆ ๋น„ํšจ์œจ์ ์ด๊ณ , ํŠน์ • ๋ถ„์•ผ์˜ ์—ฐ๊ตฌ๋งŒ ์ˆ˜ํ–‰ ํ•  ์ˆ˜ ์žˆ๋Š” ์ œํ•œ์„ฑ ๋•Œ๋ฌธ์— ์œ ์—ฐํ•œ ์—ฐ๊ตฌ ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์š”๊ตฌ๊ฐ€ ๋†’์•„์ง€๊ณ  ์žˆ๋‹ค. e-Science ๊ธฐ๋ฐ˜์˜ ์—ฐ๊ตฌ ํ™˜๊ฒฝ์„ ๊ณต๋™์œผ๋กœ ํ™œ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋‹ค๋ถ„์•ผ ๊ฐ„ ์—ฐ๊ตฌ ํ™œ์šฉ๋„๋ฅผ ๊ณ ๋ คํ•œ ๋งž์ถคํ˜• ์—ฐ๊ตฌ ํ™˜๊ฒฝ์„ ๊ตฌ์„ฑํ•˜๋Š” ๊ธฐ์ˆ ์ด ํ•„์š”ํ•˜๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์—ฌ๋Ÿฌ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” e-Science ์—ฐ๊ตฌ ํ™˜๊ฒฝ์˜ ๊ถ๊ทน์  ๋ชฉํ‘œ์— ๋ถ€ํ•ฉํ•˜๋Š” ์œ ์—ฐํ•œ ํ†ตํ•ฉ ์—ฐ๊ตฌ ํ™˜๊ฒฝ์„ ์ œ์‹œํ•œ๋‹ค. ํŠนํžˆ ์—ฌ๋Ÿฌ ๊ณผํ•™ ์‘์šฉ ์—ฐ๊ตฌ ๋ถ„์•ผ ์ค‘์—์„œ๋„ ๊ณ„์‚ฐ ๋ฐ˜๋ณต์ ์ด๊ณ  ๊ฐœ๋ฐœ ๊ณผ์ • ์ค‘์— ๋น„์šฉ ๋ฐ ์‹œ๊ฐ„ ์†Œ๋น„๊ฐ€ ํฐ ํ•ญ๊ณต์šฐ์ฃผ ๋ถ„์•ผ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜์—ฌ ํ™•์žฅ๋œ ๋งž์ถคํ˜• ์ „์—ญ ์—ฐ๊ตฌ ํ™˜๊ฒฝ์„ ์ œ์•ˆํ•œ๋‹ค. ์ด๋Š” ์—ฐ๊ตฌ์ž๋“ค์ด ์ถ”๊ฐ€์  ์ง€์‹ ์—†์ด ์‰ฝ๊ณ  ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ ํ™œ๋™์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋ฉฐ, ์‹คํ—˜ ๊ทœ๋ชจ ํ™•์žฅ์— ๋”ฐ๋ฅธ ํ•œ๊ณ„๋ฅผ ๊ฐœ์„ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ์›Œํฌํ”Œ๋กœ์šฐ ๊ธฐ๋ฐ˜์˜ ์„ค๊ณ„ ํ™˜๊ฒฝ์„ ์ œ์•ˆํ•˜์—ฌ ๋‹ค๋‹จ๊ณ„ ๋น„ํ–‰์ฒด ์„ค๊ณ„ ํ™˜๊ฒฝ์„ ํฌํ„ธ์— ํ™•์žฅํ•จ์œผ๋กœ์จ ๋”์šฑ ์ •ํ™•ํ•˜๊ณ  ์ƒ์‚ฐ์„ฑ์„ ๋†’์ด๋Š” ํ™˜๊ฒฝ์„ ์ง€์›ํ•œ๋‹ค. ์ด๊ฐ™์ด ์ œ์•ˆ๋œ ํ™˜๊ฒฝ์€ ๊ฐ ์—ฐ๊ตฌ์ž์˜ ์‹คํ—˜๊ณผ ์„ค๊ณ„์˜ ์ •ํ™•๋„๋ฅผ ๋†’์—ฌ ๊ธฐ์กด ํ™˜๊ฒฝ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๋ฉฐ ์ „๋ฌธ์„ฑ์„ ๋†’์ด๋„๋ก ๋„์™€์ค€๋‹ค.OAIID:oai:osos.snu.ac.kr:snu2010-01/104/0000004648/27SEQ:27PERF_CD:SNU2010-01EVAL_ITEM_CD:104USER_ID:0000004648ADJUST_YN:NEMP_ID:A001138DEPT_CD:446CITE_RATE:0FILENAME:์ „์‚ฐ์œ ์ฒด_ํ•ด์„_๋ฐ_์„ค๊ณ„๋ฅผ_์œ„ํ•œ_์›น๊ธฐ๋ฐ˜_์›Œํฌํ”Œ๋กœ์šฐ_ํ™˜๊ฒฝ.pdfDEPT_NM:๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€EMAIL:[email protected]:

    ํ† ์–‘์„ฑ๋ถ„๋ณ€ํ™”๋ฅผ ๊ณ ๋ คํ•œ ๋†์—…์ƒ์‚ฐ์„ฑ๋ณ€ํ™” ๋ถ„์„ : ๋น„๋ชจ์ˆ˜์  ์ ‘๊ทผ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋†๊ฒฝ์ œํ•™๊ณผ,1999.Maste

    A Study on the Design of Robot Control System using Artificial Intelligence

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    Recently, according to the advance of technological skills, robots many parts of our life. As such, the study has been proceeding to adapt in the real life the intellectual robot which was used only in the space probe or deep ocean probe. โ€˜MITSUBISHIโ€˜ Laboratory in Japan has predicted in its prediction materials of 1999 that in 2020, robot market will account for I.4 trillion dollars which will be equivalent to IT and BT market and every household have one robot. With the advancement of this intellectual robot industry, the pioneer countries such as Korea('Crubo' by Samsung Electronics, 'Robosense' by Basicrobot Co., Ltd), USA('Rumba' by Irobot Co.,), Sweden('Trilobite' by ELECTRO LUX Co.) and Japan etc have developed and supplied the robots for cleaning up. This is because there has been prediction of the increase in the demand of personal robot due to the change in life pattern recently. Recently, there has been a lot of construction of the super high-rise buildings like apartments with their wall being glasses. In case of high rise building in particular, the cleaning expenses takes a great portion in its building maintenance overhead. Cleaning the glass walls of the building is very risky. It is not even easy to secure the manpower for cleaning the glass walls and this fact contributes to the development of the most of robots.์ œ 1 ์žฅ ์„œ๋ก  = 1 ์ œ 2 ์žฅ ํผ์ง€์ด๋ก  = 3 2.1 ํผ์ง€์ด๋ก ์˜ ๊ฐœ์š” = 3 2.2 ํผ์ง€์ถ”๋ก  = 5 2.3 ๋‹ค๋ณ€์ˆ˜ ๊ตฌ์กฐ ํผ์ง€ ์‹œ์Šคํ…œ = 9 ์ œ 3 ์žฅ ์ฐฝ๋ฌธ ์ฒญ์†Œ ๋กœ๋ด‡ ์‹œ์Šคํ…œ = 13 3.1 MCU ๋ณด๋“œ = 14 3.2 ๋ชจํ„ฐ ์ œ์–ด์‹œ์Šคํ…œ ์„ค๊ณ„ = 16 3.3 ์ดˆ์ŒํŒŒ ์„ผ์„œ ๋ชจ๋“ˆ = 18 3.4 ํ†ต์‹  ์‹œ์Šคํ…œ = 22 3.5 ์กฐ์ด์Šคํ‹ฑ ์ œ์–ด๊ธฐ = 23 ์ œ 4 ์žฅ ์ธ๊ณต์ง€๋Šฅํ˜• ์ฐฝ๋ฌธ ์ฒญ์†Œ ๋กœ๋ด‡ ์‹œ์Šคํ…œ = 28 4.1 ๋กœ๋ด‡์˜ ๊ถค์  ์˜ค์ฐจ ๋ถ„์„ = 28 4.2 ๊ฒฝ๋กœ ์ถ”์ ์„ ์œ„ํ•œ ํผ์ง€์ œ์–ด ์‹œ์Šคํ…œ = 30 4.3 ์žฅ์• ๋ฌผ ํšŒํ”ผ๋ฅผ ์œ„ํ•œ ํผ์ง€ ์ œ์–ด๊ธฐ = 33 ์ œ 5 ์žฅ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ์‹คํ—˜ = 35 5.1 ์ฒญ์†Œ ๋กœ๋ด‡์˜ ๊ฒฝ๋กœ ์ถ”์  = 36 5.2 ์ฒญ์†Œ ๋กœ๋ด‡์˜ ์žฅ์• ๋ฌผ ํšŒํ”ผ = 37 ์ œ 6 ์žฅ ๊ฒฐ๋ก  = 39 ์ฐธ๊ณ ๋ฌธํ—Œ = 40 ๋ถ€๋ก = 4

    Exploration of Autonomy's Domainality : Based on Academic Autonomy and Career Decision-Making Autonomy

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    ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์ž์œจ์„ฑ์˜ ์˜์—ญ์„ฑ์„ ํƒ์ƒ‰ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ด ์—ฐ๊ตฌ์— ํฌํ•จ๋œ ์ž์œจ์„ฑ์€ ํ•™๊ตํ˜„์žฅ์—์„œ ์ฃผ๋ชฉํ•˜๋Š” ํ•™์—…๊ณผ ์ง„๋กœ๊ฒฐ์ • ์ž์œจ์„ฑ ๋“ฑ ๋‘ ๊ฐ€์ง€์˜€๋‹ค. ์ž์œจ์„ฑ์˜ ์˜์—ญ์„ฑ์€ ํ•™์—… ์ž์œจ์„ฑ ๋ฐ ์ง„๋กœ๊ฒฐ์ • ์ž์œจ์„ฑ ์ฒ™๋„์˜ ํ™•์ธ๋œ ์กฐ์ ˆ๊ณผ ๋‚ด์ ์กฐ์ ˆ ๊ฐ„์˜ ์ƒ๊ด€ํ–‰๋ ฌ์„ ๋น„๊ตํ•˜๊ณ , ๋„ค ์š”์ธ์‚ฌ์ด์˜ ํ‰๊ท ์ฐจ์ด ๋ถ„์„ ๋ฐ ๋ชจํ˜•์˜ ์š”์ธ๊ตฌ์กฐ ๋ถ„์„ ๋“ฑ ์„ธ ๊ฐ€์ง€๋ฅผ ์ข…ํ•ฉ์ ์œผ๋กœ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ์ƒ๊ด€ํ–‰๋ ฌ ๋ฐ ํ‰๊ท ์ฐจ์ด๋ฅผ ๊ฒ€ํ† ํ•˜๊ธฐ ์œ„ํ•ด ์ฒ™๋„์ ์ˆ˜๋ฅผ ํ™œ์šฉํ•˜์˜€๊ณ , ์š”์ธ๊ตฌ์กฐ๋ชจํ˜•์€ ๋ฌธํ•ญ๊พธ๋Ÿฌ๋ฏธ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋Œ€์ƒ์€ ๊ณ ๋“ฑํ•™์ƒ 563๋ช…(1ํ•™๋…„ 195๋ช…, 2ํ•™๋…„ 193๋ช…, 3ํ•™๋…„ 175๋ช…)์ด์—ˆ๊ณ , ์ด์ค‘ 404๋ช…์€ ํƒ์ƒ‰์ง‘๋‹จ, 159๋ช…์€ ๊ต์ฐจ์ง‘๋‹จ์œผ๋กœ ํ™œ์šฉํ•˜์˜€๋‹ค. ์ƒ๊ด€ํ–‰๋ ฌ๋ถ„์„ ๊ฒฐ๊ณผ, ํ•™์—… ์ž์œจ์„ฑ๊ณผ ์ง„๋กœ๊ฒฐ์ • ์ž์œจ์„ฑ ๊ฐ„์˜ ์ƒ๊ด€์€ ๋ชจ๋‘ ์œ ์˜ํ•˜์˜€๊ณ  ํ•™์—… ์ž์œจ์„ฑ์˜ ํ™•์ธ๋œ ์กฐ์ ˆ๊ณผ ๋‚ด์  ์กฐ์ ˆ์˜ ์ƒ๊ด€์ด ๊ฐ€์žฅ ๋†’์•˜์œผ๋ฉฐ, ์ง„๋กœ๊ฒฐ์ •์ž์œจ์„ฑ์˜ ํ™•์ธ๋œ ์กฐ์ ˆ๊ณผ ํ•™์—… ์ž์œจ์„ฑ์˜ ๋‚ด์  ์กฐ์ ˆ ์ƒ๊ด€์ด ๊ฐ€์žฅ ๋‚ฎ์•˜๋‹ค. ํ‰๊ท ์ฐจ์ด ๋ถ„์„์—์„œ๋Š” ๋„ค ์š”์ธ์˜ ํ‰๊ท ์ฐจ์ด๊ฐ€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‘ ๊ฐ€์ง€ ์˜์—ญ์ผ๋ฐ˜์„ฑ ๋ชจํ˜•, ์˜์—ญํŠน์ˆ˜์„ฑ๋ชจํ˜•, ์˜์—ญ๋ณตํ•ฉ์„ฑ ๋ชจํ˜•์˜ ๋„ค ๊ฐ€์ง€ ์š”์ธ ๊ตฌ์กฐ๋ชจํ˜•์„ ๋น„๊ตํ•œ ๊ฒฐ๊ณผ, ์˜์—ญ๋ณตํ•ฉ์„ฑ ๋ชจํ˜•์˜ ์ ํ•ฉ๋„๊ฐ€ ๊ฐ€์žฅ ๋†’์•˜๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ๋ฅผ ์ข…ํ•ฉ์ ์œผ๋กœ ๊ฒ€ํ† ํ•˜๋ฉด ์ž์œจ์„ฑ์€ ์˜์—ญ๋ณตํ•ฉ์„ฑ ๋ชจํ˜•์ด์—ˆ๋‹ค. ์ด ์—ฐ๊ตฌ์˜ ์˜์˜ ๋ฐ ์ œํ•œ์ ์ด ๋…ผ์˜๋˜์—ˆ๋‹ค.The purpose of this study is to explore the 'domainality' of autonomy. Two autonomies of academic and career area which payed attention to in school field were measured. It was comprehensively reviewed whether autonomies are domain-specificity, domain-generality, domain-complexity through the utilization of correlation analysis, repeated measures ANOVA, and structural equation modeling with identified and internal regulation in academic autonomy and career decision- making autonomy scales, The subjects were 563 high school students (195 first grade students, 193 second grade students, 175 third grade students), 404 students were utilized as exploration group whereas the other 159 students were cross-validation group. The correlation between academic autonomy and career decision autonomy was all significant. The highest correlation is between identified and internal regulation of academic autonomy, the lowest correlation is between identified regulation of career decision-making autonomy and internal regulation of academic autonomy. The mean difference of the four factors was statistically significant and structural equation modeling supported the domain-complex model rather than the others. According to three results, autonomy was the domain-complex. The implications and limitations of this study were discussed

    ๋ผ๋‹ˆํ‹ฐ๋”˜๊ณผ ๋‹ˆ์žํ‹ฐ๋”˜์˜ ๋ณต์šฉ์ด ์†Œํ™”๊ธฐ์•” ๋ฐœ์ƒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

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    ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ: ์†Œํ™”๊ธฐ์•”์€ ์œ„, ๋Œ€์žฅ, ๊ฐ„, ์‹๋„, ๊ทธ๋ฆฌ๊ณ  ์ทŒ์žฅ ๋“ฑ๊ณผ ๊ฐ™์€ ์†Œํ™”๊ธฐ ๊ธฐ๊ด€์— ๋ฐœ์ƒํ•˜๋Š” ์•”์œผ๋กœ, ํ•œ๊ตญ์—์„œ๋งŒ 2020๋…„ ํ•œ ํ•ด ๋™์•ˆ ์•ฝ 8,3034๊ฑด ์ •๋„๊ฐ€ ๋ฐœ์ƒํ•˜์˜€๋‹ค. ์ด๋Š” ๊น€์น˜๋‚˜ ์žฅ์•„์ฐŒ์™€ ๊ฐ™์ด ์ฑ„์†Œ๋ฅผ ์†Œ๊ธˆ์— ์ ˆ์—ฌ ๋จน๋Š” ํ•œ๊ตญ์ธ๋“ค์˜ ์‹์Šต๊ด€๊ณผ ๊ธฐ๋ฆ„์ง„ ์Œ์‹, ๋นˆ๋ฒˆํ•œ ํญ์Œ, ๊ทธ๋ฆฌ๊ณ  ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ๋“ฑ์ด ์˜ํ–ฅ์„ ์ค€๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์ข‹์ง€ ๋ชปํ•œ ์‹์Šต๊ด€๊ณผ ์ŠคํŠธ๋ ˆ์Šค ๋“ฑ์€ ์ธ์ฒด์— ์—ญ๋ฅ˜์„ฑ ์‹๋„์—ผ, ์œ„๊ถค์–‘, ์œ„์—ผ ๋“ฑ๊ณผ ๊ฐ™์€ ์งˆ๋ณ‘๋“ค์˜ ๋ฐœ์ƒ๋ฅ ์„ ๋†’์ด๊ณ , ์ด๋Š” ์†Œํ™”๊ธฐ์•”์œผ๋กœ ๋ฐœ์ „ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ง€๋‚œ 2019๋…„, ๋ฏธ๊ตญ์˜ FDA์—์„œ๋Š” ์†Œํ™”๊ธฐ ์งˆํ™˜ ์•ฝ๋ฌผ์ธ ๋ผ๋‹ˆํ‹ฐ๋”˜(Ranitidine)๊ณผ ๋‹ˆ์žํ‹ฐ๋”˜(Nizatidine)์— ๋ฐœ์•”๋ฌผ์งˆ์ด ํ•จ์œ ๋˜์–ด ์žˆ๋‹ค๋Š” ์‹คํ—˜ ๊ฒฐ๊ณผ๋ฅผ ๋ฐํ˜”๋‹ค. ์ด๋Š” N-nitrosodimethylamine ์ด๋ผ๊ณ  ์•Œ๋ ค์ง„ ๋ฌผ์งˆ๋กœ, ๊ณต์—… ํ˜„์žฅ์—์„œ ์ฃผ๋กœ ์‚ฌ์šฉ๋œ๋‹ค. ํ•˜์ง€๋งŒ, ์ดํ›„ ์ง„ํ–‰๋œ ์—ฐ๊ตฌ๋“ค์—์„ , ๋ผ๋‹ˆํ‹ฐ๋”˜ ๋˜๋Š” ๋‹ˆ์žํ‹ฐ๋”˜์ด ์•” ๋ฐœ์ƒ์˜ ์œ„ํ—˜์„ ๋†’์ธ๋‹ค๋Š” ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•ด๋‚ด์ง€ ๋ชปํ•˜์˜€๋‹ค. ์ด์— ๋”ฐ๋ผ, ๋ณธ ์—ฐ๊ตฌ์—์„  ํ•œ๊ตญ์˜ ํ›„ํ–ฅ์  ์ฝ”ํ˜ธํŠธ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ, ํ•œ๊ตญ ์„ฑ์ธ์—๊ฒŒ์„œ ๋ผ๋‹ˆํ‹ฐ๋”˜๊ณผ ๋‹ˆ์žํ‹ฐ๋”˜์˜ ์„ญ์ทจ๊ฐ€ ์†Œํ™”๊ธฐ์•” ๋ฐœ์ƒ์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ์•Œ์•„๋ณด๊ณ ์ž ํ•œ๋‹ค. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•: ๋ณธ ์—ฐ๊ตฌ์—์„œ ์‚ฌ์šฉํ•œ ์ž๋ฃŒ๋Š” ๊ตญ๋ฏผ๊ฑด๊ฐ•๋ณดํ—˜๊ณต๋‹จ์˜ ํ‘œ๋ณธ ์ฝ”ํ˜ธํŠธ๋กœ, ๊ฑด๊ฐ•๋ณดํ—˜์— ๊ฐ€์ž…๋œ ๋Œ€ํ•œ๋ฏผ๊ตญ ๊ตญ๋ฏผ์˜ ์•ฝ 2% ์ •๋„๋ฅผ ์ถ”์ถœํ•˜์—ฌ ๊ตฌ์ถ•ํ•œ ํ›„ํ–ฅ์  ์ž๋ฃŒ์ด๋‹ค. ํ‘œ๋ณธ ๋ฐ์ดํ„ฐ์—์„œ 2002๋…„์—์„œ 2004๋…„ ์‚ฌ์ด์— ์‚ฌ๋งํ•˜์ง€ ์•Š์•˜๊ณ , ์•” ๊ฒฝ๋ ฅ์ด ์—†์œผ๋ฉฐ, ํ•ญํžˆ์Šคํƒ€๋ฏผ ์ˆ˜์šฉ์ฒด ์ฐจ๋‹จ์ œ(H2RAs)๊ฐ€ ์ฒญ๊ตฌ๋œ ์ ์ด ์—†๋Š” ์‚ฌ๋žŒ๋“ค์„ ๋Œ€์ƒ์œผ๋กœ, 3๋…„๊ฐ„์˜ ๋žœ๋“œ๋งˆํฌ ๊ธฐ๊ฐ„(Landmark period) ๋™์•ˆ ๋ˆ„์  ๋ณต์šฉ์ผ์ˆ˜๊ฐ€ 30์ผ ์ด์ƒ์ธ ๋Œ€์ƒ์ž๋“ค์„ 1:1 ์„ฑํ–ฅ์ ์ˆ˜๋งค์นญ(Propensity score mathicng)์‹œ์ผฐ๋‹ค. ์ด๋•Œ, ๋…ธ์ถœ ๊ตฐ์€ ๋…ธ์ถœ ๊ธฐ๊ฐ„ ๋™์•ˆ ๋ผ๋‹ˆํ‹ฐ๋”˜๊ณผ ๋‹ˆ์žํ‹ฐ๋”˜์„ ํ•œ ๋ฒˆ์ด๋ผ๋„ ์ฒ˜๋ฐฉ ๋ฐ›์€ ์ ์ด ์žˆ๋Š” ์‚ฌ๋žŒ์ด๋ฉฐ, ๋น„๋…ธ์ถœ ๊ตฐ์€ ํ•ด๋‹น ์•ฝ๋ฌผ๋“ค์„ ์ฒ˜๋ฐฉ๋ฐ›์€ ์ ์ด ์—†๋Š” ์‚ฌ๋žŒ๋“ค์ด์—ˆ๋‹ค. ์ดํ›„, ๋žœ๋“œ๋งˆํฌ ๊ธฐ๊ฐ„ ๋™์•ˆ ๋ผ๋‹ˆํ‹ฐ๋”˜๊ณผ ๋‹ˆ์žํ‹ฐ๋”˜์˜ ํ‰๊ท  ์œ ์ง€ ์šฉ๋Ÿ‰(DDD, Defined daily dose)๋ฅผ ๊ณ„์‚ฐํ•˜์—ฌ, ๊ถค์  ๋ถ„์„(Trajectory analysis)์„ ํ†ตํ•ด ๊ถค์  ๊ทธ๋ฃน์„ ๋‚˜๋ˆ„์—ˆ๊ณ , ํ•ด๋‹น ๊ทธ๋ฃน๋“ค์„ ์‚ฌ์šฉํ•ด ์ฝ•์Šค ํšŒ๊ท€๋ถ„์„(Cox proportional hazard regression analysis)์„ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ๋กœ, ์†Œํ™”๊ธฐ์•”์ด ๋ฐœ์ƒํ•œ ๋Œ€์ƒ์ž๋ฅผ ํ™˜์ž๊ตฐ์œผ๋กœ ์ •์˜ํ•˜๊ณ , ๊ฐ™์€ ์‹œ์ ์— ์•” ๋ฐœ์ƒ ์œ„ํ—˜์— ๋†“์—ฌ ์žˆ์—ˆ์œผ๋‚˜ ๊ฒฐ๊ณผ์ ์œผ๋กœ ์•”์ด ๋ฐœ์ƒํ•˜์ง€ ์•Š์•˜๋˜ ์‚ฌ๋žŒ๋“ค์„ ๋Œ€์กฐ๊ตฐ์œผ๋กœ ํ•˜์—ฌ, ํ™˜์ž๊ตฐ์˜ ์•”์ด ์ง„๋‹จ ์‹œ์ ์˜ ์„ฑ๋ณ„, ์—ฐ๋ น์œผ๋กœ ์„ฑํ–ฅ์ ์ˆ˜ ๋งค์นญ์„ 1:5 ๋น„์œจ๋กœ ์‹œํ–‰ํ•˜์˜€๋‹ค. ์ดํ›„, ์กฐ๊ฑด๋ถ€ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€ ๋ถ„์„ ๋ฐฉ๋ฒ•(Conditional logistic regression analysis)์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ: ๋…ธ์ถœ ๋งค์นญ ํ™˜์ž-๋Œ€์กฐ๊ตฐ ์—ฐ๊ตฌ ๋””์ž์ธ(Risk-set matching study design)์œผ๋กœ ๊ถค์  ๊ทธ๋ฃน์„ ๋‚˜๋ˆ  ์ฝ•์Šค ํšŒ๊ท€๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๋˜ ๊ฒฐ๊ณผ์™€ ์ฝ”ํ˜ธํŠธ ๋‚ด ํ™˜์ž-๋Œ€์กฐ๊ตฐ ์—ฐ๊ตฌ ๋””์ž์ธ(Nested case-control study design)์œผ๋กœ ์กฐ๊ฑด๋ถ€ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๋˜ ๊ฒฐ๊ณผ ๋ชจ๋‘ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ฒฐ๊ณผ๋ฅผ ์–ป์ง€ ๋ชปํ•˜์˜€๋‹ค. ์ด๋Š” ๋Œ€์ƒ์ž๋“ค์˜ ์ˆ˜์— ๋น„ํ•ด ์†Œํ™”๊ธฐ์•” ๋ฐœ์ƒ ๋น„์œจ์ด ํ˜„์ €ํžˆ ๋‚ฎ์•„ ๋ฐœ์ƒํ•œ ๊ฒฐ๊ณผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. ์ถ”๊ฐ€๋กœ ์ง„ํ–‰ํ•œ ํ•˜์œ„๊ทธ๋ฃน ๋ถ„์„ ๊ฒฐ๊ณผ, ์—ฌ์„ฑ์—์„œ ์•ฝ๋ฌผ์„ ๋ณต์šฉํ•˜์ง€ ์•Š์•˜๋˜ ๊ตฐ(Nonusers) ๋Œ€๋น„ ์ค‘๊ฐ„ ์šฉ๋Ÿ‰์—์„œ ์„œ์„œํžˆ ์šฉ๋Ÿ‰์„ ์ค„์—ฌ๊ฐ”๋˜ ๊ตฐ(Moderate to slightly decreased)์ด ์†Œํ™”๊ธฐ์•” ๋ฐœ์ƒ ์œ„ํ—˜์ด ๋” ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค (HR=2.29, 95% CI=1.11-4.76). ์—ฐ๊ตฌ ๊ฒฐ๋ก : ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด์ „์— ์ง„ํ–‰๋˜์—ˆ๋˜ ์—ฐ๊ตฌ๋“ค๊ณผ ๋‹ฌ๋ฆฌ, ์—ฌ๋Ÿฌ ์—ฐ๊ตฌ ๋””์ž์ธ๋“ค๊ณผ ๋ถ„์„ ๋ฐฉ๋ฒ•๋“ค์„ ์‚ฌ์šฉํ•˜์—ฌ ํŽธํ–ฅ๋œ ๊ฒฐ๊ณผ๋ฅผ ์ตœ์†Œํ™”ํ•˜๋ ค๊ณ  ๋…ธ๋ ฅํ•˜์˜€๋‹ค. ํ•˜์ง€๋งŒ, ์ž๋ฃŒ์˜ ํŠน์„ฑ์ƒ ์•” ํ™˜์ž์— ๋Œ€ํ•œ ์ •๋ณด๊ฐ€ ์ ์–ด, ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•˜๋Š”๋ฐ ํ•œ๊ณ„์ ์ด ์žˆ์—ˆ๋‹ค. ๋”๋ถˆ์–ด, ๋ผ๋‹ˆํ‹ฐ๋”˜๊ณผ ๋‹ˆ์žํ‹ฐ๋”˜์€ ์ฒ˜๋ฐฉ์ „ ์—†์ด๋„ ์•ฝ๊ตญ์—์„œ ๊ตฌ์ž…ํ•  ์ˆ˜ ์žˆ๋Š” OTC(over-the-counter) ์•ฝ๋ฌผ๋กœ, ์ฒญ๊ตฌ ์ž๋ฃŒ์—์„œ ๊ณ ๋ คํ•˜์ง€ ๋ชปํ•œ ํˆฌ์•ฝ ๊ธฐ๋ก์ด ์žˆ์„ ์ˆ˜ ์žˆ๋‹ค. ์ถ”ํ›„ ์—ฐ๊ตฌ์—์„ , ๋Œ€์ƒ์ž๋“ค์˜ ์ž„์ƒ์  ๋ณ€์ˆ˜๋“ค๊ณผ ๊ฒ€์ง„ ์ž๋ฃŒ, ๋”๋ถˆ์–ด ์•” ๋“ฑ๋ก ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ข€ ๋” ๋ฐœ์ „๋œ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. Background: Gastrointestinal (GI) cancer develops in digestive organs such as the stomach, colon, liver, esophagus, and pancreas. About 83,034 cases of GI cancer was reported in Korea in 2020. Food habits of Korean individuals, such as consuming pickled vegetables such as kimchi and oily foods, and engaging in frequent drinking, could increase the risks of developing metabolic syndromes. Poor eating habits and stress increase the incidence of diseases such as gastroesophageal reflux disease, gastric ulcer, and gastritis in the human body, which can develop into GI cancer. However, in 2019, the US Food and Drug Administration (FDA) reported that the drugs ranitidine and nizatidine contain N-nitrosodimethylamine, which is primarily used in industrial fields and is a known carcinogen. However, in subsequent studies, it could not be conclusively proven that ranitidine or nizatidine increased the risk of cancer. Accordingly, in this study, we used retrospective cohort data from Republic of Korea to investigate the effect of ranitidine and nizatidine intake on the development of GI cancer in Korean adults. Methods: The data used in this study was a sample cohort of the National Health Insurance Corporation. The data is retrospective, constructed by extracting data from approximately 2% of the Korean population who are enrolled in health insurance. The data included people who did not die between 2002 and 2004, had no history of cancer, and had not previously claimed antihistamine receptor blockers (H2RAs). During the landmark period of 3 years, participants with 30 or more cumulative dosing days were subjected to propensity score matching. At this time, the exposed group was a person who had been prescribed ranitidine or nizatidine at least once during the exposure period, and the non-exposed group was a person who had never been prescribed these drugs. Thereafter, the defined daily dose (DDD) of ranitidine and nizatidine was calculated during the landmark period, and the groups were classified through trajectory analysis, following which the Cox regression analysis was performed. Secondly, the participants who developed GI cancer were defined as cases, and those who did not develop cancer were denoted as the control group. Matching was performed in the ratio 1:5 with the sex and age of the participants. Thereafter, conditional logistic regression analysis was performed. Results: In the landmark study design, the results of Cox regression analysis using trajectory groups showed a statistically significant relationship with GI cancer risk. The โ€œModerate to slightly increasedโ€ users (HR=1.73, 95% CI=1.13-2.66) and the โ€œConstantly highโ€ users (HR=1.78, 95% CI=1.14-2.79) had a higher risk of GI cancer incidence. When subgroup analyses were performed, the โ€œConstantly highโ€ users (HR=2.09, 95% CI=1.04-4.09) and the โ€œModerate to slightly decreasedโ€ users (HR=2.29, 95% CI=1.11-4.76) had a higher risk of GI cancer in women (landmark period 1-year). Also, the โ€œModerate to slightly increasedโ€ users (HR=2.04, 95% CI=1.03-4.05) and the โ€œConstantly highโ€ users (HR=3.12, 95% CI=1.62-6.00) had a higher risk of GI cancer incidence in the participants who were below 60 years of age. However, no significant results were observed in the nested case-control study design. Conclusions: This study tried to minimize biased results using various study designs and analysis methods. However, due to the nature of the data, there was a limitation in deriving the study results. In addition, ranitidine and nizatidine are over-the-counter (OTC) drugs that can be purchased without a prescription. Thus, there may be medication records that are not considered in the claimed data. However, an effort was made to minimize selection bias using a nested case-control study design. In future research, it will be possible to derive more advanced research results using the clinical variables, health screening data, and cancer registration data of the participants.open์„

    Exploring the Structural Relationship among Academic Stress, Hope, Intrinsic Motivation and Academic Burn-out of High School Student and the Gender Difference

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    ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์ผ๋ฐ˜๊ณ„ ๊ณ ๋“ฑํ•™์ƒ์„ ๋Œ€์ƒ์œผ๋กœ ํ•™์—…์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ํ•™์—…์†Œ์ง„์— ์ด๋ฅด๋Š” ๊ณผ์ •์—์„œ ๊ฐœ์ธ์˜ ์‹ฌ๋ฆฌ ๋‚ด์  ํŠน์„ฑ์ธ ๋‚ด์žฌ์  ๋™๊ธฐ์™€ ํฌ๋ง์˜ ๊ตฌ์กฐ์  ๊ด€๊ณ„๋ฅผ ํƒ์ƒ‰ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ ์ด๋“ค ๋ณ€์ธ๋“ค ๊ฐ„์˜ ๊ตฌ์กฐ์  ๊ด€๊ณ„๊ฐ€ ์„ฑ๋ณ„์— ๋”ฐ๋ผ ์–ด๋– ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ๋Š”์ง€ ํ™•์ธํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๊ฒฝ๊ธฐ, ์˜๋‚จ, ํ˜ธ๋‚จ ์ง€์—ญ ์ผ๋ฐ˜๊ณ„ ๋‚จ๋…€ ๊ณ ๋“ฑํ•™์ƒ 443๋ช…์˜ ์„ค๋ฌธ์‘๋‹ต ๊ฒฐ๊ณผ๋ฅผ ๋ถ„์„ํ•˜๊ณ , ํ•™์—…์ŠคํŠธ๋ ˆ์Šค์™€ ํ•™์—…์†Œ์ง„๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ๋‚ด์žฌ์  ๋™๊ธฐ์™€ ํฌ๋ง์ด ๋งค๊ฐœํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๊ฐ€์„ค๋ชจํ˜•์„ ์„ค์ •ํ•˜์—ฌ ๋‚ด์žฌ์ ๋™๊ธฐ์™€ ํฌ๋ง๊ณผ์˜ ๊ด€๊ณ„์— ๋ฐฉํ–ฅ์„ ์„ค์ •ํ•œ 2๊ฐ€์ง€ ๊ฒฝ์Ÿ๋ชจํ˜•๊ณผ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ํ•™์—…์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ํ•™์—…์†Œ์ง„์— ๋ฏธ์น˜๋Š” ์ง์ ‘์ ์ธ ์˜ํ–ฅ๋ ฅ์ด ํ™•์ธ๋˜์—ˆ๊ณ , ํ•™์—…์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ํ•™์Šต์ž์˜ ํฌ๋ง์„ ๊ฑฐ์ณ ๋‚ด์žฌ์  ๋™๊ธฐ์— ์˜ํ–ฅ์„ ์ฃผ์–ด ํ•™์—…์†Œ์ง„์— ์ด๋ฅด๊ฒŒ ๋˜๋Š” ๊ฐ„์ ‘๊ฒฝ๋กœ์˜ ํ†ต๊ณ„์  ์œ ์˜์„ฑ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํ•™์—…์ŠคํŠธ๋ ˆ์Šค์—์„œ ํฌ๋ง์œผ๋กœ ๊ฐ€๋Š” ๊ฒฝ๋กœ๊ณ„์ˆ˜์—์„œ ๋‚จํ•™์ƒ๋ณด๋‹ค ์—ฌํ•™์ƒ์˜ ํ•™์—…์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ํฌ๋ง์— ๋” ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚˜ ์„ฑ๋ณ„๊ฐ„์˜ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ์ผ๋ฐ˜๊ณ„ ๊ณ ๋“ฑํ•™์ƒ์˜ ํ•™์—… ์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ํ•™์—… ์†Œ์ง„์œผ๋กœ ์ด์–ด์ง€๋Š” ์ •๋„๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•ด ์ฃผ๋ชฉํ•ด์•ผ ํ•  ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ๋ณ€์ˆ˜ ์ค‘ ํฌ๋ง๊ณผ ๋‚ด์žฌ์  ๋™๊ธฐ๋„ ํฌํ•จ๋˜์–ด์•ผ ํ•จ์„ ์‹œ์‚ฌํ•œ๋‹ค. The purpose of this research was to investigate the structural relationships among academic stress, academic burn-out, intrinsic motivation, and hope of Korean high school students by gender. To achieve the purpose, a survey was administered to male (N=222) and female (N=221) high school students in Kyunggi, Youngnam, and Honam province in South Korea. The results were as follows; Academic stress had a direct effect on academic burn-out. And academic stress also had a significant indirect effect on academic burnout. i.e., the influence of academic stress on the academic burnout was reduced by hope and intrinsic motivation. The results also indicated that female high school students academic stress had some more negative influence on their hope as compared to males. Both limitations of this study and suggestions for further studies were discussed with the implications of these findings
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