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    ๋‡Œ์ˆ˜์ˆ ์„ ๋ฐ›๋Š” ์„ฑ์ธํ™˜์ž์—์„œ ์ˆ˜์ˆ  ์ค‘ ์‹ ๊ฒฝ์ƒ๋ฆฌํ•™์  ๊ฐ์‹œ๋ฅผ ์œ„ํ•œ ์šด๋™์œ ๋ฐœ์ „์œ„ ๊ฒ€์‚ฌ ์‹œ ์˜ˆ์ธกํ•˜์ง€ ๋ชปํ•œ ์›€์ง์ž„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ธ์ž

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ, 2018. 8. ์ „์˜ํƒœ.์„œ๋ก : ์‹ ๊ฒฝ๋‚ดํ˜ˆ๊ด€ ๊ธฐ์ˆ ์˜ ๋ฐœ์ „์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋‡Œ ์ˆ˜์ˆ ์„ ํ†ตํ•ด ์—ฌ๋Ÿฌ ํ•ฉ๋ณ‘์ฆ์ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ ์ค‘์—์„œ๋„ ๊ฐ€์žฅ ๋ฌด์„œ์šด ํ•ฉ๋ณ‘์ฆ์€ ์ˆ˜์ˆ  ํ›„ ๋ฐœ์ƒํ•˜๋Š” ์šด๋™ ์žฅ์• ์ด๋‹ค. ์ˆ˜์ˆ  ์ค‘ ์‹ ๊ฒฝ์ƒ๋ฆฌํ•™์  ๋ชจ๋‹ˆํ„ฐ๋ง์˜ ์ผ์ข…์ธ ์šด๋™์œ ๋ฐœ์ „์œ„ ๊ฒ€์‚ฌ๋Š” ์šด๋™ ์žฅ์• ๋ฅผ ๊ฐ์ง€ํ•˜๋Š” ์•ˆ์ „ํ•œ ๊ฒ€์‚ฌ์ด์ง€๋งŒ, ์—ญ์œผ๋กœ ์œ„ํ•ด๋ฅผ ๊ฐ€ํ•  ์ˆ˜๋„ ์žˆ๋‹ค. ์ด๋Š” ์‹ ๊ฒฝํฅ๋ถ„๋…์„ฑ, ์ „๊ธฐํ™”ํ•™์  ์†์ƒ, ์—ด์†์ƒ, ๋ฌผ๋ฆผ ์†์ƒ, ๋ฐœ์ž‘, ์นจ์Šต์  ์ „๊ทน์— ์˜ํ•œ ํ•ฉ๋ณ‘์ฆ, ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๋Š” ์›€์ง์ž„์— ์˜ํ•œ ์†์ƒ, ๋ถ€์ •๋งฅ์„ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฐ ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๊ณ  ๋ฐ›์•„๋“ค์ด๊ธฐ ์–ด๋ ค์šด ์›€์ง์ž„์€ ๋‘๋ถ€์˜ ํ•€ ๊ณ ์ • ๋ถ€์œ„์˜ ์†์ƒ, ๊ฒฝ์ถ” ์†์ƒ, ๊ณผ๋„ํ•œ ์ˆ˜์ˆ  ์‹œ์•ผ์˜ ์›€์ง์ž„์„ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ๊ณ , ๋‚˜์œ ์ˆ˜์ˆ  ๊ฒฐ๊ณผ๋ฅผ ์ดˆ๋ž˜ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฐ ์›€์ง์ž„์— ๋Œ€ํ•œ ์œ„ํ—˜ ์š”์†Œ๋Š” ์•Œ๋ ค์ ธ ์žˆ์ง€ ์•Š๋‹ค. ๋”ฐ๋ผ์„œ ์ด ํ›„ํ–ฅ์  ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ๋ถ€๋ถ„์  ์‹ ๊ฒฝ๊ทผ ์ฐจ๋‹จ์ œ๋ฅผ ์‚ฌ์šฉํ•˜๋ฉฐ ์ „์‹ ๋งˆ์ทจ ํ•˜์— ์šด๋™์œ ๋ฐœ์ „์œ„๋ฅผ ๊ฐ์‹œํ•˜๋ฉฐ ๋‡Œ ์ˆ˜์ˆ ์„ ๋ฐ›์€ ํ™˜์ž์˜ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•˜๊ณ  ๋ฐ›์•„๋“ค์ด๊ธฐ ์–ด๋ ค์šด ์›€์ง์ž„๊ณผ ๊ด€๋ จ๋œ ์œ„ํ—˜ ์š”์†Œ๋ฅผ ์•Œ์•„๋ณด๋Š” ๊ฒƒ์ด๋‹ค. ๋ฐฉ๋ฒ•: ๋ณธ ์—ฐ๊ตฌ์—์„œ ์—ฐ๊ตฌ์ž๋Š” ํ›„ํ–ฅ์ ์œผ๋กœ ๋Œ€์ƒ ํ™˜์ž์˜ ์—ฐ๋ น, ์‹ ์žฅ, ์ฒด์ค‘, ์ฒด์งˆ๋Ÿ‰ ์ง€์ˆ˜, ์ง„๋‹จ๋ช…, ์ˆ˜์ˆ ๋ช…, ๋งˆ์ทจ ์‹œ๊ฐ„, ์ˆ˜์ˆ  ์‹œ๊ฐ„, ๊ธฐ์ € ์งˆํ™˜ (์˜ˆ : ๊ณ ํ˜ˆ์••, ๋‹น๋‡จ, ์‹ ๊ฒฝ๊ณ„ ์งˆํ™˜, ํ˜ธํก๊ธฐ๊ณ„ ์งˆํ™˜), ์ˆ˜์ˆ ์ „ ํ•ญ๊ฒฝ๋ จ์ œ ํˆฌ์—ฌ์—ฌ๋ถ€๋ฅผ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋งˆ์ทจ ์œ ๋„ ์งํ›„ ๋™๋งฅํ˜ˆ ์ฑ„ํ˜ˆ๊ฒ€์‚ฌ๋ฅผ ํ†ตํ•ด ํ—ค๋ชจ๊ธ€๋กœ๋นˆ, ํ—ค๋งˆํ† ํฌ๋ฆฟ, ๋‚˜ํŠธ๋ฅจ, ์นผ๋ฅจ, ํฌ๋„๋‹น, ์ด์˜จํ™”๋œ ์นผ์Š˜, ์ด์˜จํ™”๋œ ๋งˆ๊ทธ๋„ค์Š˜, ์ –์‚ฐ์—ผ ์ˆ˜์น˜๋„ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. ์ˆ˜์ˆ  ์ค‘ ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๊ณ  ๋ฐ›์•„๋“ค์ผ ์ˆ˜ ์—†๋Š” ์›€์ง์ž„์ด ์žˆ๋Š” ํ™˜์ž์™€ ์—†๋Š” ํ™˜์ž์—์„œ ์–ป์€ ์œ„ ๋ฐ์ดํ„ฐ๋ฅผ ํ›„ํ–ฅ์ ์œผ๋กœ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด 768๋ช… ํ™˜์ž๋ฅผ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๋Š” ์›€์ง์ž„์ด ๋ฐœ์ƒํ•œ ๊ตฐ์ด 278๋ช… (36.2%)์ด์—ˆ๋‹ค. ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๋Š” ์›€์ง์ž„์ด ๋ฐœ์ƒํ•œ ๋นˆ๋„๋Š” ์ €์นผ์Š˜ํ˜ˆ์ฆ๊ตฐ ๋ณด๋‹ค ์ •์ƒ์นผ์Š˜ํ˜ˆ์ฆ๊ตฐ์—์„œ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜์œผ๋ฉฐ(P<0.001), ์ด์˜จํ™”๋œ ์นผ์Š˜์€ ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๋Š” ์›€์ง์ž„์— ๋Œ€ํ•œ ๋…๋ฆฝ์ ์ธ ์œ„ํ—˜ ์š”์†Œ์˜€๋‹ค(odds ratio [OR] 368.519, 95% ์‹ ๋ขฐ๊ตฌ๊ฐ„ [CI] 25.319, 5348.585). ๋‚˜์ด, ํ‚ค, ๋ชธ๋ฌด๊ฒŒ, ์‹ ๊ฒฝ๊ณ„ ์งˆํ™˜๋„ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•œ ์›€์ง์ž„์˜ ๋‹ค๋ฅธ ๋…๋ฆฝ์ ์ธ ์œ„ํ—˜ ์š”์ธ์ด์—ˆ๋‹ค. ๊ฒฐ๋ก : ๋ถ€๋ถ„์ ์ธ ์‹ ๊ฒฝ๊ทผ ์ฐจ๋‹จ์ œ๋ฅผ ์‚ฌ์šฉํ•˜๋ฉฐ ์ „์‹ ๋งˆ์ทจ ํ•˜์— ์šด๋™์œ ๋ฐœ์ „์œ„ ๊ฒ€์‚ฌ๋ฅผ ๊ฐ์‹œํ•˜๋ฉฐ ๋‡Œ์ˆ˜์ˆ ์„ ๋ฐ›๋Š” ํ™˜์ž์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๋Š” ์›€์ง์ž„์—์„œ ํ˜ˆ์ฒญ ์ด์˜จํ™” ์นผ์Š˜ ๋†๋„๋Š” ์ด๋Ÿฐ ์›€์ง์ž„๊ณผ ๊ด€๋ จ๋œ ์œ„ํ—˜ ์ธ์ž์˜€๋‹ค. ------------------------------------- ์ฃผ์š”์–ด: ์šด๋™์œ ๋ฐœ์ „์œ„, ๋‡Œ์ˆ˜์ˆ , ์˜ˆ์ธกํ•˜์ง€ ๋ชปํ•œ ์›€์ง์ž„, ์นผ์Š˜์ด์˜จBackground: Despite advances in neuroendovascular techniques, several complications can occur by brain surgery. Among them, the most frightful complication is the postoperative motor deficit. Motor evoked potential (MEP) as a kind of intraoperative neurophysiologic monitoring (IONM) is a safe monitoring method for detecting the motor deficit, but this could inadvertently cause harms. It can cause excitotoxicity, electrochemical injury, thermal injury, bite injuries, seizures, invasive electrode complications, unpredictable and unacceptable movement-induced injury, and arrhythmia. The unpredictable and unacceptable can cause injuries in site of rigid pin fixation of the head, cervical spine injuries, excessive surgical field movement, and deterioration of surgical outcome. However, risk factors associated with unpredictable and unacceptable movement remain unclear. The aim of this retrospective study was to evaluate risk factors associated with unpredictable and unacceptable movement in the patients who underwent brain surgery with MEP monitoring under general anesthesia while using partial neuromuscular blocker (NMB). Methods: We recorded demographic data including age, sex, height, weight, body mass index, diagnosed disease, performed surgical procedure, duration of anesthesia, duration of surgery, underlying disease (e.g. hypertension, diabetes, neurologic disease, respiratory disease), preoperative anticonvulsant infusion. Laboratory data immediately after induction of anesthesia was also collected including arterial blood gas analysis, hematocrit, hemoglobin, sodium, potassium, glucose, ionized calcium, ionized magnesium, and lactate. We retrospectively compare the data of patients with and without unpredictable and unacceptable movement during surgery. Results: The study was enrolled and analysis 768 patients, an unpredictable and unacceptable movement was observed 278 patients (36.2%). The incidence of unpredictable and unacceptable movement was significantly higher in patients in normocalcemia group than in those in hypocalcemia group (P < 0.001). Ionized calcium (odds ratio [OR] 368.519, 95% confidence interval [CI] 25.391, 5348.585) was independent risk factors for an unpredictable and unacceptable movement. Age (odds ratio [OR] 0.987, 95% confidence interval [CI] 0.965, 0.992), height (odds ratio [OR] 1.059, 95% confidence interval [CI] 1.033, 1.085), weight (odds ratio [OR] 0.969, 95% confidence interval [CI] 0.952, 0.987), and neurologic disease (odds ratio [OR] 0.205, 95% confidence interval [CI] 0.049, 0.911) were other independent risk factors for an unpredictable and unacceptable movement. Conclusion: Serum ionized calcium concentration was the risk factors associated with unpredictable and unacceptable movement in the patients who underwent brain surgery with MEP monitoring under general anesthesia while using partial NMB. ---------------------------------------------------------------------------------------------------- Keywords: Motor evoked potential, Unpredicted movement, Brain surgery, Ionized calcium.Abstract - i Contents - iii List of tables - iv Introduction - 1 Methods - 3 Study design and inclusion criteria - 3 Anesthesia and MEP monitoring - 3 Data collection - 6 Statistical analysis - 6 Results - 8 Discussion - 14 References - 19 Abstract in Korean - 24Maste

    Alteration analysis on the Status and Roles of the North Korea's National Defense Commission

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    ๊ตญ๋ฐฉ์œ„์›ํšŒ๋Š” ๊น€์ผ์„ฑ ์‹œ๋Œ€ ์ค‘์•™์ธ๋ฏผ์œ„์›ํšŒ์˜ ๊ตฐ์‚ฌ ๋ถ„์•ผ ์ž„๋ฌด๋ฅผ ๋ณด์ขŒํ•˜๊ธฐ ์œ„ํ•ด ์ฐฝ์„ค๋˜์–ด ํฌ๊ฒŒ ๋ˆˆ์— ๋„์ง€ ์•Š์•˜๋˜ ๊ธฐ๊ด€์ด์—ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊น€์ •์ผ ์‹œ๋Œ€ ์ดํ›„์—๋Š” ๊ตญ๋ฐฉ ๋ถ„์•ผ๋Š” ๋ฌผ๋ก  ๊ตญ๊ฐ€์‚ฌํšŒ์ƒํ™œ ์ „๋ฐ˜์„ ์กฐ์ง, ์ง€ํœ˜ํ•˜๋Š” ๊ตญ๋ฐฉ์ค‘์‹œ ๊ตญ๊ฐ€๊ด€๋ฆฌ์ฒด๊ณ„์˜ ์ค‘์‹ฌ๊ธฐ๊ด€์ด์—ˆ๋‹ค. ๊น€์ •์€ ์‹œ๋Œ€์—๋Š” ๊ทธ๊ฐ€ ๋‹น์„ ์ค‘์‹ฌ์œผ๋กœ ๊ตญ์ •์„ ์šด์˜ํ•˜์—ฌ ์œ„์ƒ์ด ์ด์ „๋งŒํผ์€ ์•„๋‹ˆ์—ˆ์ง€๋งŒ ๊ธฐ๋ณธ์—ญํ• ์€ ๋ณ€ํ•จ์—†์—ˆ๋‹ค. ์˜คํžˆ๋ ค ๊ธฐ์กด์—๋Š” ๋ณผ ์ˆ˜ ์—†์—ˆ๋˜ ๋Œ€์™ธ์„ ์ „๊ธฐ๊ตฌ์˜ ๋ชจ์Šต๊ณผ ๋‚จ๋ถ๋ฌธ์ œ ๋‚˜ ์™ธ๊ต์—์„œ๋Š” ์ง์ ‘ ์ „๋ฉด์— ๋‚˜์„œ๋Š” ๋“ฑ ๊ทธ ์—ญํ• ์€ ํ™•๋Œ€๋˜์—ˆ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ตญ๋ฐฉ์œ„์›ํšŒ๋ฅผ ๋Œ€์ฒดํ•œ ๊ตญ๋ฌด์œ„์›ํšŒ์˜ ์œ„์ƒ์€ ๋‹น ์ค‘์‹ฌ ์ •์ฑ…์„ ํŽผ์น˜๊ณ  ์žˆ๋Š” ์ƒํ™ฉ ํ•˜์—์„œ ๋‹น๊ณผ์˜ ๊ด€๊ณ„๋Š” ๋ณ„๋‹ค๋ฅธ ๋ณ€ํ™”๊ฐ€ ์—†์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋˜๋‚˜ ๊ตญ๊ฐ€์ฒด์ œ ๋‚ด์—์„œ๋Š” ์œ„์ƒ๊ณผ ์—ญํ•  ๋ชจ๋‘ ๋”์šฑ ์„ฑ์žฅํ•  ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค.National Defense Commission was an unnoticed organization created to assist defense-related works of the Central People's Committee in Kim Il-sung era. But the organization had become a central organ mainly constituting and guiding not only defense areas, but also the overall national and social systems during the Kim Jong-il era. While its status degraded during the Kim Jong-un era as Kim runs state affairs mainly in his party, its main roles remain unchanged. Rather, its roles have become widened considering its role as an organ of propaganda or its coming to the front of diplomacy. Although the relation between the Office of State Affairs, which substituted National Defense Commission, and the party is expected to be unchanged, the status and role of the Office of State Affairs will be considered to be improved in the system of state

    Efficient Synthesis of 2-O-Ester Alphitolic Acid Derivatives

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์•ฝํ•™๋Œ€ํ•™ ์•ฝํ•™๊ณผ,2020. 2. ๊น€์ƒํฌ.Alphitolic acid๋Š” lupane ๊ณจ๊ฒฉ ๊ตฌ์กฐ๋ฅผ ๊ฐ–๋Š” pentacyclic triterpenoid ๊ณ„์—ด์˜ ์ฒœ์—ฐ๋ฌผ๋กœ ๋‹ค์–‘ํ•œ ์‹๋ฌผ ์ข…์—์„œ ๋ฐœ๊ฒฌ๋˜๊ณ  ์žˆ๋‹ค. ์ตœ๊ทผ alphitolic acid์— ๊ด€ํ•œ ์ƒˆ๋กœ์šด ์ฒœ์—ฐ๋ฌผ ๋ฐœ๊ฒฌ ๋ฐ ํ•ญ์—ผ์ฆ, ํ•ญ๊ท  ๋ฐ ํ•ญ์•” ๋“ฑ์˜ ๊ด‘๋ฒ”์œ„ํ•œ ์ƒ๋ฆฌํ™œ์„ฑ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๊ฐ€ ๋ณด๊ณ ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•™๋ฌธ์  ๋ฐฐ๊ฒฝ์„ ๋ฐ”ํƒ•์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ์ง„์€ ์ €๋ ดํ•˜๊ฒŒ ๊ตฌ์ž…ํ•  ์ˆ˜ ์žˆ๋Š” betulonic acid๋กœ๋ถ€ํ„ฐ ํ•ฉ์„ฑ์„ ์‹œ์ž‘ํ•˜์—ฌ Rubottom oxidation์„ ํ†ตํ•ด ์ž…์ฒด ์„ ํƒ์ , ํ™”ํ•™ ์„ ํƒ์ ์œผ๋กœ a-hydroxy ketone ์ž‘์šฉ๊ธฐ๋ฅผ ๋„์ž…ํ•˜์˜€๊ณ , ์ดํ›„ ์ž…์ฒด ์„ ํƒ์  ํ™˜์›์œผ๋กœ alphitolic acid ๋ฐ ๊ด€๋ จ ์ฒœ์—ฐ๋ฌผ ์œ ๋„์ฒด๋“ค์˜ ํ•ฉ์„ฑ์„ ์ง„ํ–‰ํ•œ ๊ฒฝํ—˜์ด ์žˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์ž๋Š” ์ถ”๊ฐ€์ ์ธ 2-O-ester ๊ตฌ์กฐ ๊ธฐ๋ฐ˜์˜ ํ•ฉ์„ฑ ์œ ๋„์ฒด๋“ค์„ ๋””์ž์ธ ํ•˜์˜€๊ณ , a-hydroxy ketone ์ž‘์šฉ๊ธฐ๋ฅผ ํฌํ•จํ•œ ๋ฌผ์งˆ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜์—ฌ ์—์Šคํ…Œ๋ฅดํ™” ๋ฐ˜์‘์„ ์ง„ํ–‰ํ•˜๊ณ  ์ด๋ฅผ ํ†ตํ•ด 2-O-ester-3-ketone ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง„ ๋‹ค์–‘ํ•œ ํ•ฉ์„ฑ ์œ ๋„์ฒด๋“ค์„ ํšจ์œจ์ ์œผ๋กœ ํ•ฉ์„ฑํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ketone ์ž‘์šฉ๊ธฐ์˜ ์ž…์ฒด ์„ ํƒ์  ํ™˜์› ๋ฐ˜์‘์œผ๋กœ 2-O-ester-3-alcohol ์ž‘์šฉ๊ธฐ๋ฅผ ๊ฐ€์ง„ ์œ ๋„์ฒด๋“ค์˜ ํ•ฉ์„ฑ์—๋„ ์„ฑ๊ณตํ•˜์˜€๋‹ค. ํ•ฉ์„ฑ๋œ 2-O-ester-3-ketone ๋ฐ 2-O-ester-3-alcohol ์œ ๋„์ฒด๋“ค์„ ์ด์šฉํ•ด ์ƒ๋ฌผํ•™์  ํ™œ์„ฑ์— ๊ด€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ ์ค‘์ด๋‹ค.Alphitolic acid has a pentacyclic triterpenoid with a lupine skeleton and has been found in various plant species. Alphitolic acid displays a broad spectrum of interesting biological effects, including anti-inflammatory, antiparasitic, and antimicrobial. We planned to synthesize 2-O-ester alphitolic acid derivatives from readily commercially available botulin via Rubottom oxidation and diastereoselective reduction. A Rubottom oxidation delivered an a-hydroxy group in a stereo- and chemoselective manner. The diastereoselective reduction of the -hydroxy ketone is one of key step. Our concise and steroselective synthesis of 2-O-ester alphitolic acid derivatives facilitate biological evaluations.I. Introduction 1 II. Results and Discussion 3 III. Conclusion 9 IV. Experimental Section 10 V. References 23 VI. Spectrum Data 25 Abstract in English 38Maste

    Exploring learner clusters to support personalized learning in elementary school blended learning

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    ์ฝ”๋กœ๋‚˜19 ํŒฌ๋ฐ๋ฏน์œผ๋กœ ์ธํ•ด ๋น„๋Œ€๋ฉด ์˜จ๋ผ์ธ ํ•™์Šต์ด ์ „์„ธ๊ณ„์ ์œผ๋กœ ์‹œํ–‰๋˜์—ˆ๋‹ค. ์ตœ๊ทผ์—๋Š” โ€˜์œ„๋“œ ์ฝ”๋กœ๋‚˜โ€™ ์ •์ฑ…๊ณผ ํ•จ๊ป˜ ํ•™๊ต์— ๋“ฑ๊ตํ•˜์—ฌ ์ˆ˜์—…์„ ๋“ฃ๋Š” ์˜คํ”„๋ผ์ธ ํ•™์Šต๊ณผ ๊ฐ€์ •์—์„œ์˜ ์˜จ๋ผ์ธ ํ•™์Šต์„ ๋ณ‘ํ–‰ํ•˜๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์ด ์‹ค์‹œ๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋ ‡๊ฒŒ ๋ณ€ํ™”๋œ ํ•™์Šต ํ™˜๊ฒฝ์€ ํ•™์ƒ๋“ค์˜ ํ•™์Šต๊ฒฉ์ฐจ๋ฅผ ์‹ฌํ™”์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•™์Šต๊ฒฉ์ฐจ๋ฅผ ํ•ด์†Œํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ํ•™์Šต์ž๋“ค์˜ ๊ต์œก์  ์š”๊ตฌ์— ๊ธฐ๋ฐ˜์„ ๋‘” ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค. ๊ต์‚ฌ๊ฐ€ ํ•™์Šต์ž๋“ค์„ ์œ„ํ•ด ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ํ•™์Šต์ž์˜ ์—ฌ๋Ÿฌ ์ธก๋ฉด์„ ์ •ํ™•ํ•˜๊ฒŒ ์ธ์‹ํ•˜๊ณ  ์ง„๋‹จํ•  ํ•„์š”๊ฐ€ ์žˆ์ง€๋งŒ, ์ตœ๊ทผ ์‹œํ–‰๋˜๊ณ  ์žˆ๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ๋Š” ํ•™์Šต์ž๋“ค์˜ ๋‹ค์–‘ํ•œ ํŠน์„ฑ์„ ๊ต์‚ฌ๊ฐ€ ์ด์ฒด์ ์œผ๋กœ ํŒŒ์•…ํ•˜๊ธฐ๋Š” ์–ด๋ ต๋‹ค. ๋”ฐ๋ผ์„œ ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๊ต์‚ฌ๊ฐ€ ํ•™์Šต์ž์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ์ดํ•ด์™€ ์ธ์‹์„ ๋ฐ”ํƒ•์œผ๋กœ ๋งž์ถคํ˜• ํ•™์Šต์„ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋„๋ก ์ถ”๊ฐ€์ ์ธ ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค. ์˜จ๋ผ์ธ๊ณผ ์˜คํ”„๋ผ์ธ ํ•™์Šต์ด ๋™์‹œ์— ์ง„ํ–‰๋˜๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๊ต์‚ฌ์˜ ์ •ํ™•ํ•œ ํ•™์Šต์ž ํŒŒ์•…์„ ๋•๊ธฐ ์œ„ํ•ด์„œ๋Š” ์˜จยท์˜คํ”„๋ผ์ธ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ํ•™์Šต์ž ํŒŒ์•…์ด ์ œ๊ณต๋  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•™์Šต์ž ํŒŒ์•…์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ํ•  ๋•Œ, 1๋Œ€ ๋‹ค์ˆ˜์ธ ๊ณต๊ต์œก์—์„œ๋Š” ๋น„์Šทํ•œ ์š”๊ตฌ๋ฅผ ์ง€๋‹Œ ํ•™์Šต์ž๋“ค์„ ๊ตฐ์ง‘ํ™”ํ•ด์„œ ๊ตฐ์ง‘๋ณ„๋กœ ์ ์ ˆํ•œ ์ฒ˜๋ฐฉ์„ ์ œ๊ณตํ•˜๋Š” ๊ฒƒ์ด ํ˜„์‹ค์ ์ธ ๋ฐฉ์•ˆ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ํ•™์Šต์ž ํŠน์„ฑ ๋ฐ ํ•™์Šต ํ–‰๋™ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ดˆ๋“ฑํ•™๊ต ํ•™์Šต์ž ์œ ํ˜•์„ ํƒ์ƒ‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ตฌ์ฒด์ ์ธ ์—ฐ๊ตฌ๋ฌธ์ œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ์œ„ํ•ด ํ•™์Šต์ž๋ฅผ ์–ด๋–ป๊ฒŒ ๊ตฐ์ง‘ํ™”ํ•  ์ˆ˜ ์žˆ๋Š”๊ฐ€? ๋‘˜์งธ, ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๊ตฐ์ง‘ ๊ฐ„ ๊ต๊ณผ์ง€์‹, ์ •์„œ, ์ž๊ธฐ์กฐ์ ˆํ•™์Šต, ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ์— ์–ด๋– ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ๋Š”๊ฐ€? ์…‹์งธ, ์ดˆ๋“ฑํ•™๊ต ๊ต์‚ฌ๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ํ•™์Šต์ž ๊ตฐ์ง‘์˜ ํƒ€๋‹น์„ฑ๊ณผ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์— ๋Œ€ํ•ด ์–ด๋–ป๊ฒŒ ์ธ์‹ํ•˜๋Š”๊ฐ€? ์ด์ƒ์˜ ์—ฐ๊ตฌ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋จผ์ € ์—ฐ๊ตฌ ์ฐธ์—ฌ์— ๋™์˜ํ•œ ์ดˆ๋“ฑํ•™๊ต 4ํ•™๋…„ ํ•™์ƒ 70๋ช…์— ๋Œ€ํ•œ ์ˆ˜ํ•™ ๊ต๊ณผ์—์„œ์˜ ํ‰๊ฐ€ ๊ฒฐ๊ณผ, ์ •์„œ ๋ฐ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์— ๋Œ€ํ•œ ์„ค๋ฌธ ๊ฒฐ๊ณผ, ํ•™์Šต๊ด€๋ฆฌ์‹œ์Šคํ…œ์—์„œ์˜ ํ™œ๋™ ๊ธฐ๋ก์„ ์ˆ˜์ง‘ํ•˜์˜€์œผ๋ฉฐ, ๊ตฐ์ง‘๊ฒฐ๊ณผ์˜ ๊ต์œกํ•™์  ํ•ด์„์„ ์œ„ํ•ด ๋ณ€์ˆ˜๋“ค์— ๋Œ€ํ•œ ์ฃผ์„ฑ๋ถ„๋ถ„์„์„ ์‹ค์‹œํ•œ ๋’ค ๋„์ถœ๋œ ์ฃผ์„ฑ๋ถ„๋“ค์˜ ์ ์ˆ˜๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ตฐ์ง‘๋ถ„์„์„ ์‹ค์‹œํ–ˆ๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์ด 3๊ฐ€์ง€ ๊ตฐ์ง‘์ด ๋„์ถœ๋˜์—ˆ์œผ๋ฉฐ, ๊ฐ ๊ตฐ์ง‘์€ ๋ชจ๋‘ ๊ต์œก์  ์š”๊ตฌ๋ฅผ ์ง€๋‹ˆ๊ณ  ์žˆ์—ˆ๋‹ค. ๊ตฐ์ง‘1์€ ์„ฑ์ , ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ, ์ •์„œ, ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์ด ๋ชจ๋‘ ๋‚ฎ์€ โ€˜ํ†ตํ•ฉ ์ง€์› ํ•„์š”ํ˜•โ€™์ด์—ˆ์œผ๋ฉฐ ๊ตฐ์ง‘2๋Š” ์„ฑ์ ๊ณผ ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ๊ฐ€ ๋†’์ง€๋งŒ ์ •์„œ์™€ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์ด ๋‚ฎ์€ โ€˜์ •์„œ ๋ฐ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต ์ง€์› ํ•„์š”ํ˜•โ€™์— ํ•ด๋‹นํ–ˆ๋‹ค. ๊ตฐ์ง‘3์€ ์ •์„œ์™€ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์ด ๋†’์ง€๋งŒ ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ๊ฐ€ ๋‚ฎ์€ โ€˜์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ ์ง€์› ํ•„์š”ํ˜•โ€™์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ตฐ์ง‘๋ณ„๋กœ ์ฃผ์„ฑ๋ถ„๊ณผ ์„ธ๋ถ€ ๋ณ€์ธ์—์„œ ๋ชจ๋‘ ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๊ตฐ์ง‘์˜ ํƒ€๋‹น์„ฑ ๋ฐ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ ์กฐ์‚ฌ ๊ฒฐ๊ณผ, ๊ต์‚ฌ๋“ค์€ ๊ตฐ์ง‘์˜ ๊ฒฐ๊ณผ๊ฐ€ ํ•™์Šต์ž๋“ค์— ๋Œ€ํ•œ ์ž์‹ ์˜๊ธฐ์กด ์ธ์‹๊ณผ ์ฐจ์ด๊ฐ€ ์žˆ๋‹ค๊ณ  ๋Š๊ผˆ์œผ๋‚˜ ๋™์‹œ์— ์œ ์šฉํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ตฐ์ง‘๋ณ„๋กœ ์š”๊ตฌ์— ๊ธฐ๋ฐ˜ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€์œผ๋ฉฐ, ๊ตฐ์ง‘ ๊ฒฐ๊ณผ์— ๋”ฐ๋ผ ์ˆ˜์—… ์„ค๊ณ„ ๋ฐ ์ƒํ™œ์ง€๋„๋ฅผ ๋งž์ถคํ˜•์œผ๋กœ ์ง€์›ํ•  ๊ฒƒ์œผ๋กœ ์ธ์‹ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ์œ„ํ•ด ๋งž์ถคํ˜• ์ฝ˜ํ…์ธ  ์ œ๊ณต, ์—…๋ฌด ๊ฐ์†Œ ๋“ฑ์˜ ์ถ”๊ฐ€์ ์ธ ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ํ•™์Šต์ž ์œ ํ˜•ํ™”๋ฅผ ํ†ตํ•ด ์ถ•์ ๋œ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•œ ์ด์ฒด์ ์ธ ํ•™์Šต์ž ์ดํ•ด์™€ ๋ชจ๋“  ํ•™์Šต์ž๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ๊ตฐ์ง‘๋ณ„ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ์œ„ํ•ด์„œ๋Š” ๊ต์œก ์‹œ์Šคํ…œ ๊ตฌ์ถ•์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํƒ์ƒ‰ํ•œ ๋‚ด์šฉ์ด ํ–ฅํ›„ ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ์—ฐ๊ตฌ์— ์œ ์šฉํ•˜๊ฒŒ ํ™œ์šฉ๋œ๋‹ค๋ฉด ํ•™์Šต๊ฒฉ์ฐจ ํ•ด์†Œ ๋ฐ ํ•™์Šต์ž ์ดํ•ด์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.Due to the COVID-19 pandemic, non-face-to-face online learning has been implemented worldwide. Recently, along with the 'With Corona' policy, blended learning, which combines offline learning at school and online learning at home, is being implemented. However, this changed learning environment has been shown to deepen the learning gap among students. To bridge this learning gap, personalized learning support based on the educational needs of learners is required. For teachers to provide personalized learning support for learners, it is necessary to accurately recognize and diagnose various aspects of learners. However, in blended learning, it is difficult for teachers to grasp the various characteristics of learners holistically. Therefore, additional support is needed in blended learning so that teachers can provide personalized learning support based on accurate understanding and recognition of learners. For this, it is necessary to identify learners based on online and offline data. In addition, when providing personalized learning support based on learner identification, especially in public education, which is one-to-many, it is a realistic method to cluster learners with similar needs and provide appropriate educational prescriptions for each group. Therefore, in this study, elementary school learner types were explored based on learner characteristics and learning behavior data in blended learning. The specific research questions of this study are as follows. First, how can learners be clustered to support personalized learning in elementary school blended learning? Second, is there any difference in subject knowledge, affective domain, self-regulated learning, and online learning participation between groups in elementary school blended learning? Third, how do elementary school teachers perceive the validity of the learner cluster and personalized learning support methods in blended learning? To solve the above research problem, first, the evaluation results in math subjects, the results of the questionnaire on affective domain and self-regulated learning, and the online activity records in the learning management system were collected for 4th grade students of elementary school who agreed to participate in the research. (n=70) For pedagogical interpretation of the results, principal component analysis was conducted on the variables, and then cluster analysis was performed using the derived scores of principal components. As a result of the study, a total of three clusters were derived, and every cluster had educational needs. Cluster 1 was the 'integrated support type' with low grades, online learning participation, emotion, and self-regulated learning, and Cluster 2 was the 'emotional and self-regulated learning support type' with high grades and online learning participation but low emotional and self-regulated learning. Cluster 3 was found to be a โ€˜online learning participation support typeโ€™ with high score in affective domain and self-regulated learning but low score in online learning participation. In addition, it was found that there were significant differences in both the main component and the detailed variables by cluster. As a result of the survey on teachers' perceptions about the validity of clusters and personalized learning support methods, teachers perceived that the results of clustering were different from their existing perceptions of learners, but recognized that they were useful at the same time. In addition, it was founded that personalized learning support based on the needs of each cluster was necessary, and personalized support for instructional design and child guidance would be provided according to the results of the group. In addition, it was recognized that additional support such as recommendation system that provides customized learning contents according to the need of clusters and teacherโ€™s work reduction were necessary to support personalized learning. This study confirmed that it is necessary to understand the overall learner using the accumulated data in elementary school blended learning through learner clustering and to support personalized learning for all learners. In addition, it was confirmed that it was necessary to establish an education system to support personalized learning and provided educational prescriptions for each clusters. If the contents explored through this study are usefully used for further research on personalized learning support in blended learning in the future, it is expected to contribute to bridging the learning gap and understanding learners.โ… . ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 2. ์—ฐ๊ตฌ๋ฌธ์ œ 5 3. ์šฉ์–ด์˜ ์ •๋ฆฌ 6 ๊ฐ€. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹ 6 ๋‚˜. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› 6 ๋‹ค. ํ•™์Šต์ž ๊ตฐ์ง‘ 6 โ…ก. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 8 1. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹ 8 ๊ฐ€. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์˜ ๊ฐœ๋… ๋ฐ ์œ ํ˜• 8 ๋‚˜. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์˜ ํšจ๊ณผ์™€ ์ œํ•œ์  10 2. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› 12 ๊ฐ€. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์˜ ๊ฐœ๋… ๋ฐ ํŠน์ง• 12 ๋‚˜. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์—์„œ ๊ณ ๋ คํ•ด์•ผํ•  ํ•™์Šต์ž ํŠน์„ฑ 13 3. ํ•™์Šต๋ถ„์„ 16 ๊ฐ€. ํ•™์Šต๋ถ„์„์˜ ๊ฐœ๋… ๋ฐ ํŠน์ง• 16 ๋‚˜. ํ•™์Šต๋ถ„์„์˜ ์ ˆ์ฐจ 18 ๋‹ค. ํ•™์Šต์ž ๊ตฐ์ง‘์˜ ์œ ํ˜• 19 โ…ข. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 22 1. ์—ฐ๊ตฌ ์ฐธ์—ฌ์ž 22 2. ์—ฐ๊ตฌ์ ˆ์ฐจ 24 3. ์ž๋ฃŒ ์ˆ˜์ง‘ 26 ๊ฐ€. ํ•™์Šต์ž ์ž๋ฃŒ ์ˆ˜์ง‘ 26 ๋‚˜. ๊ต์‚ฌ ๋ฉด๋‹ด ์ž๋ฃŒ ์ˆ˜์ง‘ 29 4. ์ž๋ฃŒ ๋ถ„์„ 29 ๊ฐ€. ํ•™์Šต์ž ์ž๋ฃŒ ๋ถ„์„ 29 ๋‚˜. ๊ต์‚ฌ ๋ฉด๋‹ด ์ž๋ฃŒ ๋ถ„์„ 33 โ…ฃ. ์—ฐ๊ตฌ๊ฒฐ๊ณผ 34 1. ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ํ•™์Šต์ž ๊ตฐ์ง‘ํ™” 34 2. ํ•™์Šต์ž ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 36 ๊ฐ€. ์ฃผ์„ฑ๋ถ„์—์„œ์˜ ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 36 ๋‚˜. ์„ธ๋ถ€ ๋ณ€์ธ์—์„œ์˜ ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 37 3. ๊ต์‚ฌ์˜ ๊ตฐ์ง‘ํ™”์— ๋Œ€ํ•œ ์ธ์‹ 40 ๊ฐ€. ๊ตฐ์ง‘์˜ ํƒ€๋‹น์„ฑ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ 40 ๋‚˜. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ 43 โ…ค. ๋…ผ์˜ ๋ฐ ๊ฒฐ๋ก  51 1. ๋…ผ์˜ 51 ๊ฐ€. ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ํ•™์Šต์ž ๊ตฐ์ง‘ 51 ๋‚˜. ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 52 ๋‹ค. ๊ตฐ์ง‘๋ถ„์„ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ 57 2. ๊ฒฐ๋ก  58 3. ์ œ์–ธ 61์„

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    Exploring learner clusters to support personalized learning in elementary school blended learning

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์‚ฌ๋ฒ”๋Œ€ํ•™ ๊ต์œกํ•™๊ณผ(๊ต์œก๊ณตํ•™์ „๊ณต), 2022.2. ์กฐ์˜ํ™˜.์ฝ”๋กœ๋‚˜19 ํŒฌ๋ฐ๋ฏน์œผ๋กœ ์ธํ•ด ๋น„๋Œ€๋ฉด ์˜จ๋ผ์ธ ํ•™์Šต์ด ์ „์„ธ๊ณ„์ ์œผ๋กœ ์‹œํ–‰๋˜์—ˆ๋‹ค. ์ตœ๊ทผ์—๋Š” โ€˜์œ„๋“œ ์ฝ”๋กœ๋‚˜โ€™ ์ •์ฑ…๊ณผ ํ•จ๊ป˜ ํ•™๊ต์— ๋“ฑ๊ตํ•˜์—ฌ ์ˆ˜์—…์„ ๋“ฃ๋Š” ์˜คํ”„๋ผ์ธ ํ•™์Šต๊ณผ ๊ฐ€์ •์—์„œ์˜ ์˜จ๋ผ์ธ ํ•™์Šต์„ ๋ณ‘ํ–‰ํ•˜๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์ด ์‹ค์‹œ๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋ ‡๊ฒŒ ๋ณ€ํ™”๋œ ํ•™์Šต ํ™˜๊ฒฝ์€ ํ•™์ƒ๋“ค์˜ ํ•™์Šต๊ฒฉ์ฐจ๋ฅผ ์‹ฌํ™”์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•™์Šต๊ฒฉ์ฐจ๋ฅผ ํ•ด์†Œํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ํ•™์Šต์ž๋“ค์˜ ๊ต์œก์  ์š”๊ตฌ์— ๊ธฐ๋ฐ˜์„ ๋‘” ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค. ๊ต์‚ฌ๊ฐ€ ํ•™์Šต์ž๋“ค์„ ์œ„ํ•ด ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ํ•™์Šต์ž์˜ ์—ฌ๋Ÿฌ ์ธก๋ฉด์„ ์ •ํ™•ํ•˜๊ฒŒ ์ธ์‹ํ•˜๊ณ  ์ง„๋‹จํ•  ํ•„์š”๊ฐ€ ์žˆ์ง€๋งŒ, ์ตœ๊ทผ ์‹œํ–‰๋˜๊ณ  ์žˆ๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ๋Š” ํ•™์Šต์ž๋“ค์˜ ๋‹ค์–‘ํ•œ ํŠน์„ฑ์„ ๊ต์‚ฌ๊ฐ€ ์ด์ฒด์ ์œผ๋กœ ํŒŒ์•…ํ•˜๊ธฐ๋Š” ์–ด๋ ต๋‹ค. ๋”ฐ๋ผ์„œ ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๊ต์‚ฌ๊ฐ€ ํ•™์Šต์ž์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ์ดํ•ด์™€ ์ธ์‹์„ ๋ฐ”ํƒ•์œผ๋กœ ๋งž์ถคํ˜• ํ•™์Šต์„ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋„๋ก ์ถ”๊ฐ€์ ์ธ ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค. ์˜จ๋ผ์ธ๊ณผ ์˜คํ”„๋ผ์ธ ํ•™์Šต์ด ๋™์‹œ์— ์ง„ํ–‰๋˜๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๊ต์‚ฌ์˜ ์ •ํ™•ํ•œ ํ•™์Šต์ž ํŒŒ์•…์„ ๋•๊ธฐ ์œ„ํ•ด์„œ๋Š” ์˜จยท์˜คํ”„๋ผ์ธ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ํ•™์Šต์ž ํŒŒ์•…์ด ์ œ๊ณต๋  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•™์Šต์ž ํŒŒ์•…์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ํ•  ๋•Œ, 1๋Œ€ ๋‹ค์ˆ˜์ธ ๊ณต๊ต์œก์—์„œ๋Š” ๋น„์Šทํ•œ ์š”๊ตฌ๋ฅผ ์ง€๋‹Œ ํ•™์Šต์ž๋“ค์„ ๊ตฐ์ง‘ํ™”ํ•ด์„œ ๊ตฐ์ง‘๋ณ„๋กœ ์ ์ ˆํ•œ ์ฒ˜๋ฐฉ์„ ์ œ๊ณตํ•˜๋Š” ๊ฒƒ์ด ํ˜„์‹ค์ ์ธ ๋ฐฉ์•ˆ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ํ•™์Šต์ž ํŠน์„ฑ ๋ฐ ํ•™์Šต ํ–‰๋™ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ดˆ๋“ฑํ•™๊ต ํ•™์Šต์ž ์œ ํ˜•์„ ํƒ์ƒ‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ตฌ์ฒด์ ์ธ ์—ฐ๊ตฌ๋ฌธ์ œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ์œ„ํ•ด ํ•™์Šต์ž๋ฅผ ์–ด๋–ป๊ฒŒ ๊ตฐ์ง‘ํ™”ํ•  ์ˆ˜ ์žˆ๋Š”๊ฐ€? ๋‘˜์งธ, ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ๊ตฐ์ง‘ ๊ฐ„ ๊ต๊ณผ์ง€์‹, ์ •์„œ, ์ž๊ธฐ์กฐ์ ˆํ•™์Šต, ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ์— ์–ด๋– ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ๋Š”๊ฐ€? ์…‹์งธ, ์ดˆ๋“ฑํ•™๊ต ๊ต์‚ฌ๋Š” ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ํ•™์Šต์ž ๊ตฐ์ง‘์˜ ํƒ€๋‹น์„ฑ๊ณผ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์— ๋Œ€ํ•ด ์–ด๋–ป๊ฒŒ ์ธ์‹ํ•˜๋Š”๊ฐ€? ์ด์ƒ์˜ ์—ฐ๊ตฌ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋จผ์ € ์—ฐ๊ตฌ ์ฐธ์—ฌ์— ๋™์˜ํ•œ ์ดˆ๋“ฑํ•™๊ต 4ํ•™๋…„ ํ•™์ƒ 70๋ช…์— ๋Œ€ํ•œ ์ˆ˜ํ•™ ๊ต๊ณผ์—์„œ์˜ ํ‰๊ฐ€ ๊ฒฐ๊ณผ, ์ •์„œ ๋ฐ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์— ๋Œ€ํ•œ ์„ค๋ฌธ ๊ฒฐ๊ณผ, ํ•™์Šต๊ด€๋ฆฌ์‹œ์Šคํ…œ์—์„œ์˜ ํ™œ๋™ ๊ธฐ๋ก์„ ์ˆ˜์ง‘ํ•˜์˜€์œผ๋ฉฐ, ๊ตฐ์ง‘๊ฒฐ๊ณผ์˜ ๊ต์œกํ•™์  ํ•ด์„์„ ์œ„ํ•ด ๋ณ€์ˆ˜๋“ค์— ๋Œ€ํ•œ ์ฃผ์„ฑ๋ถ„๋ถ„์„์„ ์‹ค์‹œํ•œ ๋’ค ๋„์ถœ๋œ ์ฃผ์„ฑ๋ถ„๋“ค์˜ ์ ์ˆ˜๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ตฐ์ง‘๋ถ„์„์„ ์‹ค์‹œํ–ˆ๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์ด 3๊ฐ€์ง€ ๊ตฐ์ง‘์ด ๋„์ถœ๋˜์—ˆ์œผ๋ฉฐ, ๊ฐ ๊ตฐ์ง‘์€ ๋ชจ๋‘ ๊ต์œก์  ์š”๊ตฌ๋ฅผ ์ง€๋‹ˆ๊ณ  ์žˆ์—ˆ๋‹ค. ๊ตฐ์ง‘1์€ ์„ฑ์ , ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ, ์ •์„œ, ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์ด ๋ชจ๋‘ ๋‚ฎ์€ โ€˜ํ†ตํ•ฉ ์ง€์› ํ•„์š”ํ˜•โ€™์ด์—ˆ์œผ๋ฉฐ ๊ตฐ์ง‘2๋Š” ์„ฑ์ ๊ณผ ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ๊ฐ€ ๋†’์ง€๋งŒ ์ •์„œ์™€ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์ด ๋‚ฎ์€ โ€˜์ •์„œ ๋ฐ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต ์ง€์› ํ•„์š”ํ˜•โ€™์— ํ•ด๋‹นํ–ˆ๋‹ค. ๊ตฐ์ง‘3์€ ์ •์„œ์™€ ์ž๊ธฐ์กฐ์ ˆํ•™์Šต์ด ๋†’์ง€๋งŒ ์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ๊ฐ€ ๋‚ฎ์€ โ€˜์˜จ๋ผ์ธ ํ•™์Šต์ฐธ์—ฌ ์ง€์› ํ•„์š”ํ˜•โ€™์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ตฐ์ง‘๋ณ„๋กœ ์ฃผ์„ฑ๋ถ„๊ณผ ์„ธ๋ถ€ ๋ณ€์ธ์—์„œ ๋ชจ๋‘ ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๊ตฐ์ง‘์˜ ํƒ€๋‹น์„ฑ ๋ฐ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ ์กฐ์‚ฌ ๊ฒฐ๊ณผ, ๊ต์‚ฌ๋“ค์€ ๊ตฐ์ง‘์˜ ๊ฒฐ๊ณผ๊ฐ€ ํ•™์Šต์ž๋“ค์— ๋Œ€ํ•œ ์ž์‹ ์˜๊ธฐ์กด ์ธ์‹๊ณผ ์ฐจ์ด๊ฐ€ ์žˆ๋‹ค๊ณ  ๋Š๊ผˆ์œผ๋‚˜ ๋™์‹œ์— ์œ ์šฉํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ตฐ์ง‘๋ณ„๋กœ ์š”๊ตฌ์— ๊ธฐ๋ฐ˜ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€์œผ๋ฉฐ, ๊ตฐ์ง‘ ๊ฒฐ๊ณผ์— ๋”ฐ๋ผ ์ˆ˜์—… ์„ค๊ณ„ ๋ฐ ์ƒํ™œ์ง€๋„๋ฅผ ๋งž์ถคํ˜•์œผ๋กœ ์ง€์›ํ•  ๊ฒƒ์œผ๋กœ ์ธ์‹ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ์œ„ํ•ด ๋งž์ถคํ˜• ์ฝ˜ํ…์ธ  ์ œ๊ณต, ์—…๋ฌด ๊ฐ์†Œ ๋“ฑ์˜ ์ถ”๊ฐ€์ ์ธ ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ์ธ์‹ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ ํ•™์Šต์ž ์œ ํ˜•ํ™”๋ฅผ ํ†ตํ•ด ์ถ•์ ๋œ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•œ ์ด์ฒด์ ์ธ ํ•™์Šต์ž ์ดํ•ด์™€ ๋ชจ๋“  ํ•™์Šต์ž๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ๊ตฐ์ง‘๋ณ„ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์„ ์œ„ํ•ด์„œ๋Š” ๊ต์œก ์‹œ์Šคํ…œ ๊ตฌ์ถ•์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํƒ์ƒ‰ํ•œ ๋‚ด์šฉ์ด ํ–ฅํ›„ ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ์—ฐ๊ตฌ์— ์œ ์šฉํ•˜๊ฒŒ ํ™œ์šฉ๋œ๋‹ค๋ฉด ํ•™์Šต๊ฒฉ์ฐจ ํ•ด์†Œ ๋ฐ ํ•™์Šต์ž ์ดํ•ด์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.Due to the COVID-19 pandemic, non-face-to-face online learning has been implemented worldwide. Recently, along with the 'With Corona' policy, blended learning, which combines offline learning at school and online learning at home, is being implemented. However, this changed learning environment has been shown to deepen the learning gap among students. To bridge this learning gap, personalized learning support based on the educational needs of learners is required. For teachers to provide personalized learning support for learners, it is necessary to accurately recognize and diagnose various aspects of learners. However, in blended learning, it is difficult for teachers to grasp the various characteristics of learners holistically. Therefore, additional support is needed in blended learning so that teachers can provide personalized learning support based on accurate understanding and recognition of learners. For this, it is necessary to identify learners based on online and offline data. In addition, when providing personalized learning support based on learner identification, especially in public education, which is one-to-many, it is a realistic method to cluster learners with similar needs and provide appropriate educational prescriptions for each group. Therefore, in this study, elementary school learner types were explored based on learner characteristics and learning behavior data in blended learning. The specific research questions of this study are as follows. First, how can learners be clustered to support personalized learning in elementary school blended learning? Second, is there any difference in subject knowledge, affective domain, self-regulated learning, and online learning participation between groups in elementary school blended learning? Third, how do elementary school teachers perceive the validity of the learner cluster and personalized learning support methods in blended learning? To solve the above research problem, first, the evaluation results in math subjects, the results of the questionnaire on affective domain and self-regulated learning, and the online activity records in the learning management system were collected for 4th grade students of elementary school who agreed to participate in the research. (n=70) For pedagogical interpretation of the results, principal component analysis was conducted on the variables, and then cluster analysis was performed using the derived scores of principal components. As a result of the study, a total of three clusters were derived, and every cluster had educational needs. Cluster 1 was the 'integrated support type' with low grades, online learning participation, emotion, and self-regulated learning, and Cluster 2 was the 'emotional and self-regulated learning support type' with high grades and online learning participation but low emotional and self-regulated learning. Cluster 3 was found to be a โ€˜online learning participation support typeโ€™ with high score in affective domain and self-regulated learning but low score in online learning participation. In addition, it was found that there were significant differences in both the main component and the detailed variables by cluster. As a result of the survey on teachers' perceptions about the validity of clusters and personalized learning support methods, teachers perceived that the results of clustering were different from their existing perceptions of learners, but recognized that they were useful at the same time. In addition, it was founded that personalized learning support based on the needs of each cluster was necessary, and personalized support for instructional design and child guidance would be provided according to the results of the group. In addition, it was recognized that additional support such as recommendation system that provides customized learning contents according to the need of clusters and teacherโ€™s work reduction were necessary to support personalized learning. This study confirmed that it is necessary to understand the overall learner using the accumulated data in elementary school blended learning through learner clustering and to support personalized learning for all learners. In addition, it was confirmed that it was necessary to establish an education system to support personalized learning and provided educational prescriptions for each clusters. If the contents explored through this study are usefully used for further research on personalized learning support in blended learning in the future, it is expected to contribute to bridging the learning gap and understanding learners.โ… . ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 2. ์—ฐ๊ตฌ๋ฌธ์ œ 5 3. ์šฉ์–ด์˜ ์ •๋ฆฌ 6 ๊ฐ€. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹ 6 ๋‚˜. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› 6 ๋‹ค. ํ•™์Šต์ž ๊ตฐ์ง‘ 6 โ…ก. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 8 1. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹ 8 ๊ฐ€. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์˜ ๊ฐœ๋… ๋ฐ ์œ ํ˜• 8 ๋‚˜. ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์˜ ํšจ๊ณผ์™€ ์ œํ•œ์  10 2. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› 12 ๊ฐ€. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์˜ ๊ฐœ๋… ๋ฐ ํŠน์ง• 12 ๋‚˜. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์›์—์„œ ๊ณ ๋ คํ•ด์•ผํ•  ํ•™์Šต์ž ํŠน์„ฑ 13 3. ํ•™์Šต๋ถ„์„ 16 ๊ฐ€. ํ•™์Šต๋ถ„์„์˜ ๊ฐœ๋… ๋ฐ ํŠน์ง• 16 ๋‚˜. ํ•™์Šต๋ถ„์„์˜ ์ ˆ์ฐจ 18 ๋‹ค. ํ•™์Šต์ž ๊ตฐ์ง‘์˜ ์œ ํ˜• 19 โ…ข. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 22 1. ์—ฐ๊ตฌ ์ฐธ์—ฌ์ž 22 2. ์—ฐ๊ตฌ์ ˆ์ฐจ 24 3. ์ž๋ฃŒ ์ˆ˜์ง‘ 26 ๊ฐ€. ํ•™์Šต์ž ์ž๋ฃŒ ์ˆ˜์ง‘ 26 ๋‚˜. ๊ต์‚ฌ ๋ฉด๋‹ด ์ž๋ฃŒ ์ˆ˜์ง‘ 29 4. ์ž๋ฃŒ ๋ถ„์„ 29 ๊ฐ€. ํ•™์Šต์ž ์ž๋ฃŒ ๋ถ„์„ 29 ๋‚˜. ๊ต์‚ฌ ๋ฉด๋‹ด ์ž๋ฃŒ ๋ถ„์„ 33 โ…ฃ. ์—ฐ๊ตฌ๊ฒฐ๊ณผ 34 1. ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ํ•™์Šต์ž ๊ตฐ์ง‘ํ™” 34 2. ํ•™์Šต์ž ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 36 ๊ฐ€. ์ฃผ์„ฑ๋ถ„์—์„œ์˜ ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 36 ๋‚˜. ์„ธ๋ถ€ ๋ณ€์ธ์—์„œ์˜ ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 37 3. ๊ต์‚ฌ์˜ ๊ตฐ์ง‘ํ™”์— ๋Œ€ํ•œ ์ธ์‹ 40 ๊ฐ€. ๊ตฐ์ง‘์˜ ํƒ€๋‹น์„ฑ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ 40 ๋‚˜. ๋งž์ถคํ˜• ํ•™์Šต ์ง€์› ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ 43 โ…ค. ๋…ผ์˜ ๋ฐ ๊ฒฐ๋ก  51 1. ๋…ผ์˜ 51 ๊ฐ€. ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ํ•™์Šต์ž ๊ตฐ์ง‘ 51 ๋‚˜. ์ดˆ๋“ฑํ•™๊ต ๋ธ”๋ Œ๋””๋“œ ๋Ÿฌ๋‹์—์„œ์˜ ๊ตฐ์ง‘ ๊ฐ„ ์ฐจ์ด 52 ๋‹ค. ๊ตฐ์ง‘๋ถ„์„ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๊ต์‚ฌ์˜ ์ธ์‹ 57 2. ๊ฒฐ๋ก  58 3. ์ œ์–ธ 61์„

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    Master๊ตญ์ œ ๋ฐ ๊ตญ๋‚ด ํ™˜๊ฒฝ ๊ทœ์ œ๋กœ ์ธํ•ด ์„ํƒ„, ์„์œ ์™€ ๊ฐ™์€ ํ™”์„ ์—ฐ๋ฃŒ์˜ ์‚ฌ์šฉ์ด ์ œํ•œ๋˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด์— ๋”ฐ๋ผ ์ „์„ธ๊ณ„์ ์œผ๋กœ ์ฒœ์—ฐ ๊ฐ€์Šค์˜ ์ˆ˜์ž… ๋ฐ ์ˆ˜์ถœ๋Ÿ‰์ด ๊ธ‰๊ฒฉํ•˜๊ฒŒ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์ฒœ์—ฐ ๊ฐ€์Šค๋Š” ์ˆ˜์†ก ๋ฐ ์ €์žฅ์ด ํŽธ๋ฆฌํ•˜๊ฒŒ ํ•˜๊ธฐ ์œ„ํ•ด์„œ ์•กํ™”๋œ ์ฒœ์—ฐ ๊ฐ€์Šค์ธ LNG๋กœ ๋ณ€ํ™”๋˜๋ฉฐ, ์žฌ์‚ฌ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ธฐํ™”๋ฅผ ํ†ตํ•ด ๋‹ค์‹œ ์ฒœ์—ฐ ๊ฐ€์Šค๋กœ ๋ณ€ํ™˜ํ•˜์—ฌ ์‚ฌ์šฉํ•˜๊ฒŒ ๋œ๋‹ค. ํ•˜์ง€๋งŒ, ์ด ๊ณผ์ •์—์„œ ์ž์—ฐ๊ณผ์˜ ์—ด๊ตํ™˜์„ ํ†ตํ•ด ์—๋„ˆ์ง€์˜ ์†์‹ค๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ํ™˜๊ฒฝ ์˜ค์—ผ์ด ๋ฐœ์ƒ๋˜๊ฒŒ ๋œ๋‹ค. ์ด ์—๋„ˆ์ง€์˜ ์†์‹ค์„ ๋ง‰๊ณ , ํ™˜๊ฒฝ์„ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•ด์„œ ํ์—ด์„ ์ด์šฉํ•œ ์œ ๊ธฐ ๋ƒ‰๋งค ๋žญํ‚จ ์‚ฌ์ดํด์ธ ORC๊ฐ€ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ORC๋Š” ์—ด์นจ์„ LNG๋กœ ์‚ฌ์šฉํ•˜๊ณ , ์—ด์› (ํ•ด์ˆ˜, ํƒœ์–‘์—ด, ํ์—ด, ๋ฐ”์ด์˜ค๋งค์Šค ๋“ฑ)์„ ๋‹ค์–‘ํ•˜๊ฒŒ ์‚ฌ์šฉํ•œ๋‹ค. ์—ด์›์˜ ์˜จ๋„๊ฐ€ ๋งค์šฐ ๋‚ฎ๊ธฐ ๋•Œ๋ฌธ์— ํ™”๋ ฅ, ์›์ž๋ ฅ ๋“ฑ ๋ฐœ์ „์— ๋Œ€๋น„ํ•˜์—ฌ ๋‚ฎ์€ ์ผ, ์—ด๋Ÿ‰, ํšจ์œจ์„ ๊ฐ€์ง„๋‹ค. ํ•˜์ง€๋งŒ, ๋ฒ„๋ ค์ง€๋Š” ์—ด๋Ÿ‰์„ ์žฌ์‚ฌ์šฉํ•˜๊ณ , ํ™˜๊ฒฝ์„ ๋ณดํ˜ธํ•œ๋‹ค๋Š” ์ด์ ์ด ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ๊ฐ๊ด‘๋ฐ›๋Š”๋‹ค. ํ•˜์ง€๋งŒ, ํ•ด๋‹น ํ™˜๊ฒฝ ์กฐ๊ฑด์—์„œ ORC ์ตœ์  ์กฐ๊ฑด ์„ค๊ณ„๋Š” ๊ฐ„๋‹จํ•˜๊ฒŒ ๊ฒฐ์ •ํ•  ์ˆ˜ ์—†๋‹ค. ์‚ฌ์ดํด์„ ๊ฒฐ์ •ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋‹ค์–‘ํ•œ ๋ณ€์ˆ˜๋“ค์ด ์กด์žฌํ•˜๋ฉฐ, ์ด๋ฅผ ํŒŒ์•…ํ•˜์—ฌ ์„ค๊ณ„ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ๋‹ค์–‘ํ•œ ๋ณ€์ˆ˜์— ๋”ฐ๋ฅธ ์—ฐ๊ตฌ๋Š” ๋งŽ์ด ์‹ค์‹œ ๋˜์—ˆ์ง€๋งŒ, ๋ชจ๋“  ๋ณ€์ˆ˜๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์ตœ์  ์„ค๊ณ„ ์—ฐ๊ตฌ๋Š” ๋ถ€์กฑํ•˜๋‹ค๊ณ  ํŒ๋‹จ๋œ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‹ค์–‘ํ•œ ๋ณ€์ˆ˜๋“ค์„ ๋ชจ๋‘ ๊ณ ๋ คํ•˜์—ฌ ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€๋ฅผ ์ง„ํ–‰ํ•˜์—ฌ ์ตœ์  ์„ค๊ณ„ ์ง€์ ์— ๋Œ€ํ•œ ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ํ•ด๋‹น ์—ฐ๊ตฌ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์ˆœ์„œ๋กœ ์ง„ํ–‰๋œ๋‹ค. ์ฒซ๋ฒˆ์งธ, ์‚ฌ์ดํด, ์—ด๊ตํ™˜๊ธฐ, ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€ ์ฝ”๋“œ ์„ค๊ณ„์— ์•ž์„œ, ํ•ด๋‹น ์กฐ๊ฑด์—์„œ์˜ ์ ํ•ฉํ•œ ์‚ฌ์ดํด ๋ ˆ์ด์•„์›ƒ, ์ž‘๋™ ์œ ์ฒด ์ข…๋ฅ˜, ์—ด๊ตํ™˜๊ธฐ ํƒ€์ž… ๋ฐ ์žฌ๋ฃŒ๋ฅผ ์„ ์ •ํ•˜์˜€๋‹ค. ์‚ฌ์ดํด ๋ ˆ์ด์•„์›ƒ์€ ASPEN์„ ํ†ตํ•œ ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€๋ฅผ ์‹ค์‹œํ•˜์—ฌ, simple ORC๊ฐ€ ์ ํ•ฉํ•˜๋‹ค๊ณ  ํŒ๋‹จ๋˜์—ˆ์œผ๋ฉฐ, ์ž‘๋™ ์œ ์ฒด๋กœ๋Š” ๋ชฌํŠธ๋ฆฌ์˜ฌ ๋ฐ ๊ตํ† ์˜์ •์„œ์— ์˜ํ•ด์„œ ์ œํ•œ๋˜๋Š” ์œ ์ฒด์™€ ํ™˜๊ฒฝ ์กฐ๊ฑด์„ ๊ณ ๋ คํ•˜์—ฌ ์ด 13์ข…์˜ ์ž‘๋™ ์œ ์ฒด๋ฅผ ์„ ์ •ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ํ™˜๊ฒฝ ์กฐ๊ฑด์„ ๊ณ ๋ คํ•˜์—ฌ ์—ด๊ตํ™˜๊ธฐ ํƒ€์ž…๊ณผ ์žฌ๋ฃŒ๋ฅผ Evaporator์— shell & tubeํ˜• ์—ด๊ตํ™˜๊ธฐ ํƒ€์ž…์„ ์„ ์ •, ํ•ด์ˆ˜์˜ ๋ถ€์‹์„ ๊ณ ๋ คํ•œ Cu-Ni, Titanium์„ ์žฌ๋ฃŒ๋กœ์จ ์„ ์ •ํ–ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ž‘๋™ ํ™˜๊ฒฝ์„ ๊ณ ๋ คํ•˜์—ฌcondenser์— PCHE (Printed Circuit Heat Exchanger)์˜ ํƒ€์ž…์„ ์„ ์ •ํ–ˆ๊ณ , PCHE์˜ ์žฌ๋ฃŒ๋กœ๋Š” ์ œ์ž‘ ๊ฐ€๋Šฅ์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ SUS304, SUS316์œผ๋กœ ์„ ์ •ํ–ˆ๋‹ค. ๋‘๋ฒˆ์งธ, ํ•ด๋‹น ์‚ฌ์ดํด์„ ํ•ด์„ํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์ดํด, ์—ด๊ตํ™˜๊ธฐ, ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€ ์ฝ”๋“œ๋ฅผ ์„ค๊ณ„ํ–ˆ์œผ๋ฉฐ, ์ด๋Š” MATLAB ํ”„๋กœ๊ทธ๋žจ๊ณผ NIST REFPROP์˜ ์—ฐ๋™์„ ๋ฐ”ํƒ•์œผ๋กœ ์„ค๊ณ„๋˜์—ˆ๋‹ค. ์„ธ๋ฒˆ์งธ, ํ•ด๋‹น ์„ค๊ณ„ ์ฝ”๋“œ์— ๋Œ€ํ•œ ์ด์šฉ ์ ํ•ฉ์„ฑ์„ ํŒ๋‹จํ•˜๊ธฐ ์œ„ํ•ด ์‹ค์ œ ์‹คํ—˜ data ๋ฐ ASPEN์„ ํ†ตํ•ด์„œ ๋น„๊ต ๋ฐ ๊ฒ€์ฆ์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์‚ฌ์ดํด ์ฝ”๋“œ์˜ ๊ฒฝ์šฐ, ์ตœ๋Œ€ 3.29%์˜ ์˜ค์ฐจ๊ฐ€ ๋ฐœ์ƒํ–ˆ์œผ๋ฉฐ, ์ด๋Š” ๋ฌผ์„ฑ์น˜ ๋ฐฉ๋ฒ•๋ก ์˜ ์ฐจ์ด๋กœ ์ธํ•ด ๋ฐœ์ƒํ•˜๋Š” ์˜ค์ฐจ๋กœ ํŒ๋‹จํ–ˆ๋‹ค. ์—ด๊ตํ™˜๊ธฐ์˜ ๊ฒฝ์šฐ, ์ตœ๋Œ€ 15%์˜ ์˜ค์ฐจ๊ฐ€ ๋ฐœ์ƒํ–ˆ์œผ๋ฉฐ, ์ด๋Š” PCHE์˜ header effect์™€ ์ƒ๊ด€์‹์— ๋Œ€ํ•œ ์˜ค์ฐจ๋ฅผ ๊ฐ์•ˆํ•˜๋ฉด ํ•ฉ๋ฆฌ์ ์ธ ์ˆ˜์ค€์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์„ค๊ณ„ํ•œ ์ฝ”๋“œ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๊ฐ ๋ณ€์ˆ˜์— ๋”ฐ๋ฅธ parametric study๋ฅผ ํ†ตํ•ด ๋ถ„์„์„ ์‹ค์‹œํ–ˆ์œผ๋ฉฐ, ๋ชจ๋“  ๋ณ€์ˆ˜๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ๊ฒฝ์ œ์ ์œผ๋กœ ์ตœ์  ์ž‘๋™ ์กฐ๊ฑด์ด ๋˜๋Š” ORC๋ฅผ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์ฝ”๋“œ๋ฅผ ํ†ตํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ, ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€์— ๊ทผ๊ฑฐํ•œ ์ตœ์  ์ž‘๋™ ์กฐ๊ฑด์€ ์ž‘๋™ ์œ ์ฒด R-143a, ํŽŒํ”„ ์ถœ๊ตฌ ์••๋ ฅ 600kPa, ์งˆ๋Ÿ‰ ์œ ๋Ÿ‰ 50kg/s, pinch point 11๋„, shell & tube ์žฌ๋ฃŒ Cu-Ni(90/10), PCHE ์žฌ๋ฃŒ SUS316์œผ๋กœ ์ œ์•ˆํ•œ๋‹ค.Currently, Organic Rankine Cycle (ORCs) using cryogenic LNG has advantages in terms of environmental protection and energy saving. In the design of the ORC plant that use seawater as a heat source and use LNG as heat sink, determining the operating conditions is important because work, efficiency, and economics change greatly depending on variables including pressure, mass flow rate, components. For organic Rankine cycles of which typical efficiency is low, efforts for increasing the efficiency and work have been pursued in several ways by adjusting associated parameters such as the pressure, mass flow rate, working fluid. Also, the ORC consists of pump, turbine and heat exchanger, which vary in size and performance depending on various conditions. Therefore, it is necessary to derive an optimal point design under various conditions through an economic assessment. In this paper, variables were selected for pump outlet pressure, mass flow rate of working fluid, pinch point, type of working fluids and material of heat exchangers, and economic evaluation was carried out according to the parameters. The heat exchanger type was selected shell & tube for evaporator and PCHE (Printed Circuit Heat Exchanger) for condenser considering the operating condition of ORC. Since this paper uses low-temperature seawater as a heat source, the net work and efficiency are very low and the change in economics will be great depending on the variables. Therefore, in order to maximize this, consideration of all variables is necessary. In particular, the analysis of the material of the heat exchanger is insufficient, and this study is deemed necessary because thermal area of heat exchanger and economic feasibility are expected to vary greatly depending on this variable. Also, since it is judged that a lack of analysis according to the characteristics of the working fluid, which is classified as wet, isentropic, dry fluid in low-temperature heat source, it is compared and analyzed to determine the effect of cycle according to characteristics of working fluid under this conditions. The objective of this paper is to design optimum cycle, which is used LNG cold energy as heat sink and the seawater as heat source. To find the optimal cycle point, five parameters of working fluid type, mass flow rate, pump outlet pressure, pinch point and material of heat exchanger were selected. For evaluating the various variables having impact in ORC cycles, systematical cryogenic ORC design code consisting of cycle, heat exchanger, and economic assessment codes was developed. The type and material of heat exchanger was selected considering the operating conditions. After analyzing the cycle changes for each variable, the optimal design point based on maximum economic assessment was determined by considering all variables. To perform this analysis, OEC (ORC Economic evaluation Code) was developed and verification was conducted by comparing actual experiment data and ASPEN programs. Then, optimal design points for economic assessment were derived taking into account variables through OEC. According to economic assessment results, the most economical cycle has a net work of 1.51MW and an efficiency of 10.81%, shell & tube material is Cu-Ni (90/10) and PCHE material is SUS316
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