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    ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ์˜ ์†Œ์…œ AI ๊ฐœ์ธ๋น„์„œ ํ‰๊ฐ€ ๋ชจ๋ธ ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์‚ฐ์—…๊ณตํ•™๊ณผ, 2022.2. ์œค๋ช…ํ™˜.This dissertation aims to propose a user evaluation model to evaluate social AI personal assistants in the early stage of product development. Due to the rapid development of personal devices, data generated from personal devices are increasing explosively, and various personal AI services and products using these data are being launched. However, compared to the interest in AI personal assistant products, its market is still immature. In this case, it is important to understand consumer expectations and perceptions deeply and develop a product that can satisfy them to spread the product and allow general consumers to easily accept the product promptly. Accordingly, this dissertation proposes and validates a user evaluation model that can be used in the early stage of product development. Prior to proposing this methodology, main characteristics of social AI personal assistants, the importance of user evaluation in the early stage of product development and the limitations of the existing user evaluation model were investigated in Chapter 2. Various technology acceptance models and evaluation models for social AI personal assistant products have been proposed, evaluation models that can be applied in the initial stage of product development were insufficient, however. Moreover, it was found that commonly used evaluation measures for assessment of hedonic value were much fewer compared to measures for utilitarian value. These were used as starting points of this dissertation. In Chapter 3, the evaluation measures used in previous studies related to social AI personal assistant were collected and carefully reviewed. Through systematic review of 40 studies, the evaluation measures used in the past and limitation of related research were investigated. As a result, it was found that it was not easy to develop a prototype for evaluation, so it was possible to make the most of the products that have already been commercialized. In addition, all evaluation items used in previous studies were collected and used as the basis for the evaluation model to be proposed later. As a result of the analysis, considering the purpose of the social AI personal assistant, the role as supporting the user emotionally through social interaction with the user is important, but it was found that the evaluation measures related to hedonic value that are commonly used were still insufficient. In Chapter 4, evaluation measures that can be used in the initial stage of product development for social AI personal assistant were selected. Selected evaluation measures were used to evaluate three types of social robots and relationship among evaluation factors were induced through this evaluation. A process was proposed to understand to various opinions related to social robots and to derive evaluation items, and a case study was conducted in which a total of 230 people evaluated three social robots concept images using the evaluation items finally selected through this process. As a result, it is shown that consumersโ€™ attitude toward products was built through the utilitarian dimension and the hedonic dimension. In addition, there is positive relationship between ease of use and utility in the utilitarian dimension, and among aesthetic pleasure, attractiveness of personality, affective value in the hedonic dimension. Moreover, it is confirmed that the evaluation model derived from this study showed superior explanatory power compared to the previously proposed technology acceptance model. In Chapter 5, the model was validated again by applying the evaluation measure and the relationship among evaluation factors derived in Chapter 4 to other products. 100 UX experts with expertise in the field of social AI personal assistants and 100 users who use the voice assistant service often, watched two concept videos of the voice assistant service to help users in the onboarding situation of mobile phones and evaluated these concepts. As a result of the evaluation, there is no significant difference in the evaluation results between the UX expert and the real user group, so the structural equation model analysis was conducted using all the data obtained from the UX expert and the real user group. As a result, results similar to those in Chapter 4 are obtained, and it is expected that the model could be generalized to social AI personal assistant products and applied for future research. This dissertation proposes evaluation measure and relationship among evaluation factors that can be applied when conducting user evaluation in the initial stage of social AI personal assistant development. In addition, case studies using social AI personal assistant products and services were conducted to validate it. With the findings of this study, it is expected that researchers who need to conduct user evaluation to clarify product concepts in the early stages of product development will be able to apply evaluation measures effectively. It is expected that the significance of this dissertation will become clearer if further research is conducted comparing the finished product of social AI personal assistants with the video type stimulus in the early stage of development.๋ณธ ๋…ผ๋ฌธ์€ ์ตœ๊ทผ ๋น ๋ฅด๊ฒŒ ๋ฐœ์ „ํ•˜๊ณ  ์žˆ๋Š” social AI personal assistant์˜ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์— ํ™œ์šฉ ๊ฐ€๋Šฅํ•œ ์‚ฌ์šฉ์ž ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ํ‰๊ฐ€ ํ•ญ๋ชฉ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ๊ฒ€์ฆํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๊ฐœ์ธ ๋””๋ฐ”์ด์Šค์˜ ๋ฐœ๋‹ฌ๋กœ ์ธํ•ด, ๊ฐ ๋””๋ฐ”์ด์Šค์—์„œ ์ƒ์„ฑ๋˜๋Š” ๋ฐ์ดํ„ฐ๊ฐ€ ํญ๋ฐœ์ ์œผ๋กœ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๊ณ , ์ด๋ฅผ ํ™œ์šฉํ•œ ๊ฐœ์ธ์šฉ AI ์„œ๋น„์Šค ๋ฐ ์ œํ’ˆ์ด ๋‹ค์–‘ํ•˜๊ฒŒ ์ œ์•ˆ๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ ๊ด€์‹ฌ์— ๋น„ํ•ด, social AI personal assistant ์ œํ’ˆ์˜ ์‹ค์ œ ์‹œ์žฅ์€ ์•„์ง ์„ฑ์ˆ™ํ•˜์ง€ ์•Š์€ ๋‹จ๊ณ„์ด๋‹ค. ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์—์„œ ์ œํ’ˆ์„ ๋น ๋ฅด๊ฒŒ ํ™•์‚ฐ์‹œํ‚ค๊ณ  ์ผ๋ฐ˜ ์†Œ๋น„์ž๋“ค์ด ์‰ฝ๊ฒŒ ์ œํ’ˆ์„ ์ˆ˜์šฉํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š”, ์†Œ๋น„์ž์˜ ๊ธฐ๋Œ€์™€ ์ธ์‹์„ ์ถฉ๋ถ„ํžˆ ์ดํ•ดํ•˜๊ณ  ๊ทธ๋ฅผ ์ถฉ์กฑ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ์ œํ’ˆ์„ ๊ฐœ๋ฐœํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ์ด์— ๋”ฐ๋ผ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ œํ’ˆ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์‚ฌ์šฉ์ž ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ์ œ์•ˆํ•˜๊ณ  ํ‰๊ฐ€ ํ•ญ๋ชฉ ๊ฐ„ ๊ด€๊ณ„๋ฅผ ๋„์ถœํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๋จผ์ € 2์žฅ์—์„œ๋Š” social AI personal assistant์˜ ํŠน์ง•, ์ œํ’ˆ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ ์ด๋ฃจ์–ด์ง€๋Š” ์‚ฌ์šฉ์ž ํ‰๊ฐ€์˜ ์ค‘์š”์„ฑ ๋ฐ ๊ธฐ์กด ์‚ฌ์šฉ์ž ํ‰๊ฐ€ ๋ชจ๋ธ์˜ ํ•œ๊ณ„์ ์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๊ธฐ์กด์— ๊ธฐ์ˆ  ์ˆ˜์šฉ ๋ชจ๋ธ ๋ฐ AI personal assistant ์ œํ’ˆ์˜ ํ‰๊ฐ€ ๋ชจ๋ธ๋“ค์ด ๋‹ค์–‘ํ•˜๊ฒŒ ์ œ์•ˆ๋˜์–ด ์™”์œผ๋‚˜, ์ œํ’ˆ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ํ‰๊ฐ€ ๋ชจ๋ธ์€ ๋ถ€์กฑํ•˜์˜€๊ณ , ์ œํ’ˆ ์ „๋ฐ˜์„ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ๋Š” ํ‰๊ฐ€ ๋ชจ๋ธ์˜ ๋ถ€์žฌ๋กœ ๋Œ€๋ถ€๋ถ„์˜ ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ๋‘ ๊ฐ€์ง€ ์ด์ƒ์˜ ํ‰๊ฐ€ ๋ชจ๋ธ์„ ๊ฒฐํ•ฉ, ์ˆ˜์ •ํ•˜์—ฌ ์‚ฌ์šฉํ•œ ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. 3์žฅ์—์„œ๋Š” AI personal assistant ๊ด€๋ จ ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ ํ™œ์šฉ๋œ ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ์ด 40๊ฐœ์˜ ์—ฐ๊ตฌ๋ฅผ ๋ฆฌ๋ทฐํ•˜์—ฌ, ๊ธฐ์กด์— ํ™œ์šฉ๋˜๊ณ  ์žˆ๋Š” ํ‰๊ฐ€ ํ•ญ๋ชฉ์˜ ์ข…๋ฅ˜ ๋ฐ ํ•œ๊ณ„์ ์„ ์•Œ์•„๋ณด์•˜๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ํ‰๊ฐ€๋ฅผ ์œ„ํ•œ ํ”„๋กœํ† ํƒ€์ž… ๊ฐœ๋ฐœ์ด ์‰ฝ์ง€ ์•Š๊ธฐ์— ์ด๋ฏธ ์ƒ์šฉํ™”๋œ ์ œํ’ˆ๋“ค์„ ์ตœ๋Œ€ํ•œ ํ™œ์šฉํ•˜๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ์ œํ’ˆ ์ „๋ฐ˜์„ ํ‰๊ฐ€ํ•œ ์‚ฌ๋ก€๋Š” ๋ถ€์กฑํ•จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์ด ์‚ฌ์šฉํ•œ ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ๋ชจ๋‘ ์ˆ˜์ง‘ ๋ฐ ์ •๋ฆฌํ•˜์—ฌ ์ดํ›„ ์ œ์•ˆํ•  ํ‰๊ฐ€ ๋ชจ๋ธ์˜ ๊ธฐ๋ฐ˜ ์ž๋ฃŒ๋กœ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, social AI personal assistant์˜ ๋ชฉ์ ์„ ๊ณ ๋ คํ•ด๋ณด์•˜์„ ๋•Œ, ์‚ฌ์šฉ์ž์™€์˜ ์‚ฌํšŒ์  ์ธํ„ฐ๋ž™์…˜์„ ํ†ตํ•ด ์‚ฌ์šฉ์ž์˜ ๊ฐ์ •์ ์ธ ๋ฉด์„ ์ฑ„์›Œ์ฃผ๋Š” ์—ญํ• ์ด ์ค‘์š”ํ•˜์ง€๋งŒ, ๊ณตํ†ต์ ์œผ๋กœ ํ™œ์šฉํ•˜๊ณ  ์žˆ๋Š” ๊ฐ์ •์  ๊ฐ€์น˜ ๊ด€๋ จ ํ‰๊ฐ€ ํ•ญ๋ชฉ์ด ๋ถ€์กฑํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. 4์žฅ์—์„œ๋Š” social AI personal assistant ์ œํ’ˆ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ ํ™œ์šฉ ๊ฐ€๋Šฅํ•œ ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ์ˆ˜์ง‘ ๋ฐ ์ œ์•ˆํ•˜๊ณ , ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ํ™œ์šฉํ•˜์—ฌ social robots์„ ํ‰๊ฐ€ํ•œ ๋’ค ์ด๋ฅผ ํ†ตํ•ด ํ‰๊ฐ€ ํ•ญ๋ชฉ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. Social robots ๊ด€๋ จ ์˜๊ฒฌ์„ ๋‹ค์–‘ํ•˜๊ฒŒ ์ฒญ์ทจํ•˜๊ณ  ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ๋„์ถœํ•˜๋Š” ํ”„๋กœ์„ธ์Šค๋ฅผ ์ œ์•ˆํ•˜์˜€์œผ๋ฉฐ, ๋ณธ ํ”„๋กœ์„ธ์Šค๋ฅผ ํ†ตํ•ด ์ตœ์ข… ์„ ์ •๋œ ํ‰๊ฐ€ ํ•ญ๋ชฉ์„ ์ด์šฉํ•˜์—ฌ, ์ด 230๋ช…์ด ์„ธ ๊ฐ€์ง€ social robots ์ปจ์…‰ ์˜์ƒ์„ ํ‰๊ฐ€ํ•˜๋Š” ์‚ฌ๋ก€ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ํ‰๊ฐ€ ๊ฒฐ๊ณผ, ์ œํ’ˆ์— ๋Œ€ํ•œ ์†Œ๋น„์ž ํƒœ๋„๋Š” Utilitarian dimension๊ณผ Hedonic dimension์„ ํ†ตํ•ด ํ˜•์„ฑ๋˜์—ˆ๊ณ , Utilitarian dimension ๋‚ด ์‚ฌ์šฉ์„ฑ ๋ฐ ์ œํ’ˆ ํšจ์šฉ์„ฑ, Hedonic dimension์— ํฌํ•จ๋˜๋Š” ์‹ฌ๋ฏธ์  ๋งŒ์กฑ๋„, ์„ฑ๊ฒฉ์˜ ๋งค๋ ฅ๋„, ๊ฐ์„ฑ์  ๊ฐ€์น˜ ๊ฐ๊ฐ์€ ์„œ๋กœ ๊ธ์ •์ ์ธ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ง€๋‹˜์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ๊ธฐ์กด์— ์ œ์•ˆ๋œ ๊ธฐ์ˆ  ์ˆ˜์šฉ ๋ชจ๋ธ ๋Œ€๋น„ ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋„์ถœํ•œ ํ‰๊ฐ€ ๋ชจ๋ธ์ด ์šฐ์ˆ˜ํ•œ ์„ค๋ช…๋ ฅ์„ ๋ณด์ž„์„ ํ™•์ธํ•˜์˜€๋‹ค. 5์žฅ์—์„œ๋Š” 4์žฅ์—์„œ ๋„์ถœ๋œ ํ‰๊ฐ€ ๋ชจ๋ธ์„ ํƒ€ ์ œํ’ˆ์— ์ ์šฉํ•˜์—ฌ ๋ชจ๋ธ์„ ๋‹ค์‹œ ํ•œ๋ฒˆ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ํ•ด๋‹น ๋ถ„์•ผ์— ์ „๋ฌธ์„ฑ์„ ์ง€๋‹Œ UX ์ „๋ฌธ๊ฐ€ 100๋ช… ๋ฐ ์Œ์„ฑ ๋น„์„œ ์„œ๋น„์Šค๋ฅผ ์‹ค์ œ ์‚ฌ์šฉํ•˜๋Š” ์‹ค์‚ฌ์šฉ์ž 100๋ช…์ด, ํœด๋Œ€ํฐ ์˜จ๋ณด๋”ฉ ์ƒํ™ฉ์—์„œ ์‚ฌ์šฉ์ž๋ฅผ ๋„์™€์ฃผ๋Š” ์Œ์„ฑ ๋น„์„œ ์„œ๋น„์Šค์˜ ์ปจ์…‰ ์˜์ƒ ๋‘ ๊ฐ€์ง€๋ฅผ ๋ณด๊ณ  ์ปจ์…‰์— ๋Œ€ํ•œ ํ‰๊ฐ€๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ํ‰๊ฐ€ ๊ฒฐ๊ณผ UX ์ „๋ฌธ๊ฐ€์™€ ์‹ค์‚ฌ์šฉ์ž ๊ทธ๋ฃน ๊ฐ„์—๋Š” ํ‰๊ฐ€ ๊ฒฐ๊ณผ์— ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜๊ธฐ ๋•Œ๋ฌธ์—, UX ์ „๋ฌธ๊ฐ€์™€ ์‹ค์‚ฌ์šฉ์ž ๊ทธ๋ฃน์—์„œ ์–ป์€ ๋ฐ์ดํ„ฐ ์ „์ฒด๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ตฌ์กฐ ๋ฐฉ์ •์‹ ๋ชจ๋ธ ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ 5์žฅ๊ณผ ์œ ์‚ฌํ•œ ์ˆ˜์ค€์˜ ๊ฒฐ๊ณผ๋ฅผ ์–ป์—ˆ๊ณ , ์ถ”ํ›„ ํ•ด๋‹น ๋ชจ๋ธ์„ social AI personal assistant ์ œํ’ˆ์— ์ผ๋ฐ˜ํ™”ํ•˜์—ฌ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ํŒ๋‹จํ•˜์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ social AI personal assistant ๊ด€๋ จ ์ œํ’ˆ ๋ฐ ์„œ๋น„์Šค์˜ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ ์‚ฌ์šฉ์ž ํ‰๊ฐ€๋ฅผ ์ง„ํ–‰ํ•  ๋•Œ ํ™œ์šฉ ๊ฐ€๋Šฅํ•œ ํ‰๊ฐ€ ํ•ญ๋ชฉ ๋ฐ ํ‰๊ฐ€ ํ•ญ๋ชฉ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ด๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ social AI personal assistant ์ œํ’ˆ ๋ฐ ์„œ๋น„์Šค๋ฅผ ํ™œ์šฉํ•œ ์‚ฌ๋ก€์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ์ถ”ํ›„ ์ œํ’ˆ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ ์ œํ’ˆ์˜ ์ปจ์…‰์„ ๋ช…ํ™•ํžˆ ํ•˜๊ธฐ ์œ„ํ•œ ์‚ฌ์šฉ์ž ํ‰๊ฐ€๋ฅผ ์‹ค์‹œํ•ด์•ผ ํ•˜๋Š” ์—ฐ๊ตฌ์ง„์ด ํšจ์œจ์ ์œผ๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ์ถ”ํ›„ ์ด ๋ถ€๋ถ„์˜ ๊ฒ€์ฆ์„ ์œ„ํ•ด, social AI personal assistants์˜ ์™„์ œํ’ˆ๊ณผ ๊ฐœ๋ฐœ ์ดˆ๊ธฐ ๋‹จ๊ณ„์˜ video type stimulus๋ฅผ ๋น„๊ตํ•˜๋Š” ์ถ”๊ฐ€ ์—ฐ๊ตฌ๊ฐ€ ์ด๋ฃจ์–ด์ง„๋‹ค๋ฉด ๋ณธ ์—ฐ๊ตฌ์˜ ์˜๋ฏธ๋ฅผ ๋ณด๋‹ค ๋ช…ํ™•ํ•˜๊ฒŒ ์ œ์‹œํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค.Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1 Research objectives 5 1.2 Dissertation outline 7 Chapter 2 Literature review 9 2.1 Social AI personal assistant 9 2.2 User centered design process 13 2.3 Technology acceptance models 16 2.4 Evaluation measures for social AI personal assistant 22 2.5 Existing evaluation methodologies for social AI personal assistant 27 Chapter 3 Collection of existing evaluation measures for social AI personal assistants 40 3.1 Background 40 3.2 Methodology 43 3.3 Result 51 3.4 Discussion 60 Chapter 4 Development of an evaluation model for social AI personal assistants 63 4.1 Background 63 4.2 Methodology 66 4.2.1 Developing evaluation measures for social AI personal assistants 68 4.2.2 Conducting user evaluation for social robots 74 4.3 Result 77 4.3.1 Descriptive statistics 77 4.3.2 Hypothesis development and testing 80 4.3.3 Comparison with existing technology acceptance models 88 4.4 Discussion 93 Chapter 5 Verification of an evaluation model with voice assistant services 95 5.1 Background 95 5.2 Methodology 98 5.2.1 Design of evaluation questionnaires for voice assistant services 99 5.2.2 Validation of relationship among evaluation factors 103 5.3 Result 108 5.3.1 Descriptive statistics 108 5.3.2 Hypothesis development and testing 111 5.3.3 Comparison with existing technology acceptance models 118 5.4 Discussion 121 Chapter 6 Conclusion 124 6.1 Summary of this study 124 6.2 Contribution of this study 126 6.3 Limitation and future work 128 Bibliography 129 Appendix A. Evaluation measures for social AI personal assistant collected in Chapter 4 146 Appendix B. Questionnaires for evaluation of social robots 154 Appendix C. Questionnaires for evaluation of voice assistant service 166๋ฐ•

    ๋Œ€์ „์ง€์—ญ ํ•™๊ต๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ(ํ–‰์ •ํ•™์ „๊ณต), 2022. 8. ์ด์ˆ˜์˜.๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ๋งค๋…„ ์•ฝ 5๋งŒ๋ช… ์ด์ƒ์˜ ํ•™์ƒ๋“ค์ด ํ•™์—…์„ ์ค‘๋‹จํ•˜๋Š” ์ƒํ™ฉ์—์„œ 17๊ฐœ ์‹œยท๋„๊ต์œก์ฒญ์—์„œ ํ•™์—…์ค‘๋‹จ ์˜ˆ๋ฐฉ์„ ์œ„ํ•ด ์‹ค์‹œํ•˜๊ณ  ์žˆ๋Š” ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ์˜ ์„ฑ๊ณต ์‚ฌ๋ก€๋ฅผ ๋ถ„์„ํ•˜์—ฌ ๊ทธ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ ์šฐ์ˆ˜ํ•œ ์‚ฌ๋ก€๊ฐ€ ํ™•์‚ฐ๋˜๊ณ , ํ•„์š”ํ•œ ๊ฒฝ์šฐ ์ œ๋„ ๊ฐœ์„ ์ด ์ด๋ค„์ ธ ํ•™์—…์ค‘๋‹จ ์œ„๊ธฐํ•™์ƒ๋“ค์ด ์˜จ์ „ํ•˜๊ฒŒ ํ•™์—…์„ ์˜์œ„ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด์„œ ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ๋ฅผ ์šฐ์ˆ˜ํ•˜๊ฒŒ ์šด์˜ํ•˜๊ณ  ์žˆ๋Š” ๋Œ€์ „ ์ง€์—ญ ํ•™๊ต๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์ธํ„ฐ๋ทฐ๋ฅผ ์ง„ํ–‰ํ•˜์˜€์œผ๋ฉฐ, ์šฐ์ˆ˜ ํ•™๊ต๋Š” ๋Œ€์ „๊ด‘์—ญ์‹œ๊ต์œก์ฒญ์˜ ์ถ”์ฒœ ํ•™๊ต, ํ•™์—…์ค‘๋‹จ ์˜ˆ๋ฐฉ ์šฐ์ˆ˜์‚ฌ๋ก€ ๊ณต๋ชจ์ „ ์ž…์ƒ ํ•™๊ต ๋“ฑ์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•œ ์ธํ„ฐ๋ทฐ ๋Œ€์ƒ์ž๋Š” ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ๋ฅผ ๋‹ด๋‹นํ•˜๊ณ  ์žˆ๋Š” ์ „๋ฌธ์ƒ๋‹ด๊ต์‚ฌ, ๊ต์žฅ(๊ฐ), ๋‹ด์ž„๊ต์‚ฌ, ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ์— ์ฐธ์—ฌํ•˜๊ณ  ํ•™์—…์— ๋ณต๊ท€ํ•œ ํ•™์ƒ ๋“ฑ์ด์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ์˜ ์„ฑ๊ณต ์‚ฌ๋ก€๋ฅผ ๋ถ„์„ํ•˜๊ณ ์ž ํ•˜๋Š” ๋ชฉ์ ์—์„œ ์–‘์  ์—ฐ๊ตฌ๋ณด๋‹ค๋Š” ์งˆ์  ์—ฐ๊ตฌ๋ฅผ ์„ ํƒํ•˜์˜€์œผ๋ฉฐ, ๋‹ค์–‘ํ•œ ์งˆ์ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•๋ก  ์ค‘ ๊ทผ๊ฑฐ์ด๋ก ์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ์ด๋ฒˆ ์—ฐ๊ตฌ์—์„œ ๊ทผ๊ฑฐ์ด๋ก ์„ ๋ฐ”ํƒ•์œผ๋กœ ๋ถ„์„์„ ํ•œ ์ด์œ ๋Š” ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ๋Š” ๊ต์œก์ฒญ์—์„œ ๋‚ด๋ ค์˜จ ๋™์ผํ•œ ์šด์˜์ง€์นจ์„ ๊ฐ€์ง€๊ณ  ํ•™๊ต๋ณ„ ํŠน์„ฑ์— ๋”ฐ๋ผ ์ œ๋„ ์šด์˜์˜ ํŽธ์ฐจ๊ฐ€ ๋‚˜ํƒ€๋‚˜๊ธฐ ๋•Œ๋ฌธ์— ์–‘์  ์ž๋ฃŒ๋ฅผ ๋ถ„์„ํ•˜๋Š” ๊ฒƒ๋ณด๋‹ค ์ œ๋„ ์šด์˜๊ณผ์ •์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๋งฅ๋ฝ์ ์ธ ์ฐจ์ด๋ฅผ ์‹ฌ์ธต์ ์œผ๋กœ ๊ทœ๋ช…ํ•  ์ˆ˜ ์žˆ๋Š” ๊ทผ๊ฑฐ์ด๋ก ์ด ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์„ ๋‹ฌ์„ฑํ•˜๋Š”๋ฐ ๋ณด๋‹ค ์ ํ•ฉํ•˜๋‹ค๊ณ  ํŒ๋‹จํ•˜์˜€๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋˜ํ•œ, ๊ทผ๊ฑฐ์ด๋ก  ์ค‘ ํŒจ๋Ÿฌ๋‹ค์ž„ ๋ชจํ˜•์„ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ, ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ์˜ ์„ฑ๊ณต์ด๋ผ๋Š” ์ค‘์‹ฌ ํ˜„์ƒ์„ ๋‘๊ณ , ์ธ๊ณผ์  ์กฐ๊ฑด๊ณผ ๋งฅ๋ฝ์  ์†์„ฑ์„ ๋ถ„์„ํ•˜๋Š” ์ ์— ์ค‘์ ์„ ๋‘์—ˆ๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ๋ฅผ ์šฐ์ˆ˜ํ•˜๊ฒŒ ์šด์˜ํ•˜๋Š” ํ•™๊ต๋“ค์˜ ๊ฒฝ์šฐ ๋ช‡ ๊ฐ€์ง€ ๊ณตํ†ต์ ์ธ ํŠน์ง•์„ ๋ฐœ๊ฒฌํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ธ๊ณผ์  ์กฐ๊ฑด ์˜์—ญ ์ค‘ ์ˆ™๋ ค๊ธฐ๊ฐ„์—์„œ๋Š” โ€œํ•™์ƒ ๋งž์ถคโ€์ด๋‚˜ โ€œํ•™์ƒ ์˜ํ–ฅโ€๊ณผ ๊ฐ™์€ ๊ณตํ†ต์˜ ๋ฒ”์ฃผ๋ฅผ ์ฐพ์„ ์ˆ˜ ์žˆ์—ˆ๊ณ , ์˜ˆ์‚ฐ์—์„œ๋Š” โ€œ์œ ์—ฐํ•œ ์ง‘ํ–‰โ€์ด๋ผ๋Š” ๊ณตํ†ต ๋ฒ”์ฃผ๋ฅผ ํ† ์ถœํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ถœ๊ฒฐ ๋ฐ ์„ฑ์ ์ฒ˜๋ฆฌ์—์„œ๋„ ๋งค๋‰ด์–ผ์ด ์žˆ๊ธฐ ๋•Œ๋ฌธ์— โ€œ๊ธฐ์ค€โ€์œผ๋กœ ๋จผ์ € ๋ฒ”์ฃผํ™”๊ฐ€ ๋์œผ๋‚˜ ์ด ๋ถ€๋ถ„์—์„œ๋„ โ€œํ•™์ƒ ๋งž์ถคโ€์˜ ๋ฒ”์ฃผ๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฐธ์—ฌํ•™์ƒ์˜ ๊ฒฝ์šฐ โ€œ๊ด€์ฐฐโ€๊ณผ โ€œ์ „๋ฌธ์  ๊ฒ€์‚ฌโ€๋ผ๋Š” ๋ฒ”์ฃผ๋ฅผ ๊ตฌ์„ฑํ•˜์˜€๊ณ , ์šด์˜๊ธฐ๊ด€ ํ•ญ๋ชฉ์˜ ๊ฒฝ์šฐ ๋ฒ”์ฃผํ™” ํ–ˆ์„ ๋•Œ ๊ณตํ†ต์ ์œผ๋กœ ๋„์ถœ๋œ ๋‹จ์–ด๋Š” โ€œ์„ ํ˜ธ๋ฐ˜์˜โ€์ด์—ˆ๋‹ค. ๊ฒฐ๊ตญ ์ด์ƒ์„ ์ข…ํ•ฉํ•ด๋ณผ ๋•Œ ์ธ๊ณผ์  ์กฐ๊ฑด์—์„œ๋Š” ํ•œ์ •๋œ ์žฌ์›๊ณผ ๋งค๋‰ด์–ผ์ด๋ผ๋Š” ๋™์ผํ•œ ๊ธฐ์ค€์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ•™์ƒ์˜ ํ˜„์žฌ ์ƒํ™ฉ์„ ์ •ํ™•ํ•˜๊ฒŒ ์ง„๋‹จํ•˜๊ณ  ํŒŒ์•…ํ•˜์—ฌ ๋งž์ถคํ˜•์œผ๋กœ ํ”„๋กœ๊ทธ๋žจ์„ ์ œ๊ณตํ•˜๊ณ , ๊ด€์ฐฐ๊ณผ ์ง€์†์ ์ธ ๊ด€์‹ฌ์„ ๋ณด์ด๋Š” ๊ฒƒ์ด ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ๋ฅผ ์„ฑ๊ณต์ ์œผ๋กœ ์šด์˜ํ•˜๋Š” ๊ณตํ†ต ์š”์ธ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋งฅ๋ฝ์  ์†์„ฑ ์˜์—ญ์—์„œ๋Š” ๊ด€๋ฆฌ์ž์ธ ๊ต์žฅ๊ณผ ๊ต๊ฐ์€ ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ ์šด์˜์— ์ง€์†์ ์œผ๋กœ ๊ด€์‹ฌ์„ ๊ฐ–๊ณ  ๋‹ด์ž„๊ต์‚ฌ, ์ƒ๋‹ด๊ต์‚ฌ, ํ•™์ƒ์„ ์‹ ๋ขฐํ•˜๊ณ  ๋ฌผ์‹ฌ์–‘๋ฉด์œผ๋กœ ์ง€์›ํ•ด ์ฃผ๋Š” ๊ฒƒ์ด ์ค‘์š”ํ–ˆ๋‹ค. ๋˜ํ•œ ์ƒ๋‹ด๊ณผ ๊ด€๋ จ๋œ ์ „๋ฌธ ์ž๊ฒฉ์ฆ์„ ๋ณด์œ ํ•œ ์ƒ๋‹ด๊ต์‚ฌ์˜ ๋†’์€ ์ „๋ฌธ์„ฑ๊ณผ ํ•จ๊ป˜ ๋‹ด์ž„๊ต์‚ฌ ๋“ฑ ํ•™๊ต ๊ตฌ์„ฑ์›์ด ํ•จ๊ป˜ ํ•™์ƒ์— ๋Œ€ํ•œ ๋”ฐ๋œปํ•œ ์‹œ์„ ๊ณผ ์—ด์ •์œผ๋กœ ํ•™์ƒ์„ ์ƒํ™ฉ์— ๋งž์ถฐ ๋‹ค์–‘ํ•˜๊ฒŒ ์ง€์›ํ•  ๋•Œ ์„ฑ๊ณต์ ์ธ ์šด์˜์„ ์ด๋ฃฐ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์†Œ์ˆ˜์˜ ๋ฉด๋‹ด์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์ธํ„ฐ๋ทฐ๋ฅผ ํ† ๋Œ€๋กœ ์ด๋ค„์กŒ๊ธฐ ๋•Œ๋ฌธ์— ์ ์€ ํ‘œ๋ณธ์—์„œ ๊ฒฐ๋ก ์„ ๋„์ถœํ•˜๊ณ ์ž ํ–ˆ๋‹ค๋Š” ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์ ์ด ์žˆ๋‹ค. ๋˜ํ•œ, ๋‚ฎ์€ ํ•™์—…์ค‘๋‹จ์œจ์„ ๋ณด์ด๋Š” ํ•™๊ต์™€ ๊ฐ™์ด ์ •๋Ÿ‰์  ๊ธฐ์ค€์œผ๋กœ ์šฐ์ˆ˜ํ•œ ํ•™๊ต๋ฅผ ์„ ์ •ํ•œ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ํ•™์—…์ค‘๋‹จ ์˜ˆ๋ฐฉ ๊ณต๋ชจ์ „ ์ž…์ƒ์ด๋‚˜ ์‹œ๊ต์œก์ฒญ์˜ ์ถ”์ฒœ ๋“ฑ์ด ์ •์„ฑ์ ์ธ ์š”์ธ์— ๊ทผ๊ฑฐํ•˜์—ฌ ์šฐ์ˆ˜ ์‚ฌ๋ก€๋ฅผ ์„ ์ •ํ•œ ๋ถ€๋ถ„์€ ๋‹ค๋ฅธ ๊ฒฌํ•ด๊ฐ€ ์žˆ์„ ์ˆ˜ ์žˆ๋‹ค. ๋‹ค๋งŒ, ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ๋ฅผ ์šฐ์ˆ˜ํ•˜๊ฒŒ ์šด์˜ํ•˜๋Š” ํ•™๊ต๋“ค์˜ ๊ณตํ†ต์ ์ธ ํŠน์ง•์ด ํ•™์ƒ์— ๋Œ€ํ•œ ์ง€์†์ ์ธ ๊ด€์‹ฌ, ํ•™๊ต ๊ตฌ์„ฑ์›์˜ ๋‹ค๊ฐ์ ์ธ ๋…ธ๋ ฅ, ๊ต์‚ฌ์˜ ์—ด์ • ๋“ฑ์œผ๋กœ ๋‚˜ํƒ€๋‚œ ๋ฐ” ๊ต์œก ํ˜„์žฅ์—์„œ๋Š” ํ•™์—…์ค‘๋‹จ ์œ„๊ธฐํ•™์ƒ ์ง€์›์„ ์œ„ํ•˜์—ฌ ์ด๋Ÿฌํ•œ ์š”์ธ๋“ค์ด ๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ๋„๋ก ๋…ธ๋ ฅ์„ ๊ธฐ์šธ์ผ ํ•„์š”๊ฐ€ ์žˆ๋‹ค.The purpose of this study is to analyze the successful cases of the careful deliberation before school dropout conducted by 17 metropolitan offices of education. And then excellent cases spread other metropolitan offices and schools. For this purpose, Interviews were conducted for schools in Daejeon. The interviewees who participated in the study were counseling teachers, principals, homeroom teachers, and students. As a result of the analysis, several common characteristics were found in the case of schools that excellently operate the careful deliberation before school dropout. Among the causal conditions areas, common categories such as "student customization" and "student intention" could be found during the deliberation period, and common categories such as "flexible execution" could be extracted from the budget. And there is a manual in attendance and grade processing, it was first categorized as a "standard," but in this part, the category of "customized students" appeared. In the case of participating students, the categories of "observation" and "professional inspection" were constructed, and in the case of operating institution items, the commonly derived words were "preferred reflection." In the end, despite the same criteria of limited financial resources and manuals under causal conditions, providing customized programs by accurately diagnosing and grasping students' current situations, and showing observation and continuous interest were common factors. In the contextual attributes area, it was important for the principal to pay attention to the operation of careful deliberation before school dropout and trust teachers. In addition, counseling teachers with professional certificates related to counseling, was achieved successful operation when school members such as homeroom teachers supported students in various ways with warm eyes and passion for students. Since this study was conducted based on interviews with a small number of interviewees, there is a limitation of the study. In addition, there may be different views on the selection of excellent schools. However, through research, the common characteristics of schools that operate excellent school were continuous interest in students, multi-faceted efforts of school members, and teacher enthusiasm, so efforts need to be made to support students in school dropout.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  ๋ฐ ํ•„์š”์„ฑ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ๊ณผ ๋ฒ”์œ„ 3 ์ œ 2 ์žฅ ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  4 ์ œ 1 ์ ˆ ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ 4 1. ํ•™์—…์ค‘๋‹จ์˜ ๊ฐœ๋… 4 2. ํ•™์—…์ค‘๋‹จ์˜ ์‹คํƒœ 5 3. ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ ๊ฐœ๊ด€ 7 ์ œ 2 ์ ˆ ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  11 1. ์„ ํ–‰์—ฐ๊ตฌ ๋ถ„์„ 11 2. ์†Œ๊ฒฐ 21 ์ œ 3 ์žฅ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• : ๊ทผ๊ฑฐ์ด๋ก ์  ์ ‘๊ทผ 23 ์ œ 1 ์ ˆ ์งˆ์ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•์˜ ํ•„์š”์„ฑ 23 ์ œ 2 ์ ˆ ๊ทผ๊ฑฐ์ด๋ก (Ground theory)๊ณผ ๋ถ„์„๊ณผ์ • 24 1. ๊ทผ๊ฑฐ์ด๋ก ์˜ ๊ฐœ๋… 24 2. ๊ทผ๊ฑฐ์ด๋ก ์˜ ๋ถ„์„ํ‹€(ํŒจ๋Ÿฌ๋‹ค์ž„ ๋ชจํ˜•) 25 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ๋ฌธ์ œ์˜ ์„ค์ •๊ณผ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 27 1. ์—ฐ๊ตฌ๋ฌธ์ œ์˜ ์„ค์ • 27 2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 29 3. ์งˆ๋ฌธ์ง€ ๊ตฌ์„ฑ 31 ์ œ 4 ์žฅ ๋ถ„์„ ๊ฒฐ๊ณผ 33 ์ œ 1 ์ ˆ ์ธ๊ณผ์  ์กฐ๊ฑด ๋ถ„์„ 33 1. ์ˆ™๋ ค๊ธฐ๊ฐ„ 33 2. ์˜ˆ์‚ฐ 36 3. ์ถœ๊ฒฐ ๋ฐ ์„ฑ์  ์ฒ˜๋ฆฌ 38 4. ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ ์ฐธ์—ฌ๋Œ€์ƒ 40 5. ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ ํ”„๋กœ๊ทธ๋žจ ์šด์˜๊ธฐ๊ด€ 45 6. ํ•™์—…์ค‘๋‹จ ์ˆ™๋ ค์ œ ์ดํ›„ ํ•™์—…๋ณต๊ท€ 50 ์ œ 2 ์ ˆ ๋งฅ๋ฝ์  ์†์„ฑ ๋ถ„์„ 52 1. ๊ด€๋ฆฌ์ž์˜ ์ง€์ง€์™€ ๊ด€์‹ฌ 52 2. ๊ต์‚ฌ์˜ ์ž์งˆ 55 3. ์ง€์—ญ์  ํŠน์ƒ‰ ๋ฐ ๋ฌธํ™” 58 ์ œ 3 ์ ˆ ๊ฒฐ๊ณผ ๋ถ„์„ 60 ์ œ 5 ์žฅ ๊ฒฐ๋ก  64 ์ œ 1 ์ ˆ ๊ฒฐ๋ก  64 ์ œ 2 ์ ˆ ์ •์ฑ… ์ œ์–ธ 65 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 67 ์ฐธ๊ณ ๋ฌธํ—Œ 69์„

    A study of the effects of interactivity of interactive TV advertising on users satisfaction

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ์ตœ๊ทผ ๋Œ€์ค‘ํ™”๋˜๊ณ  ์žˆ๋Š” ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ TV์—์„œ ๊ทธ ์‹คํ˜„ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์•„์ง€๊ณ  ์žˆ๋Š” ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ ๊ด‘๊ณ ์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž ๋งŒ์กฑ๋„ ๋„์ถœ์„ ๋ชฉ์ ์œผ๋กœ ํ•˜๊ณ  ์žˆ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์— ๋”ฐ๋ฅด๋ฉด ์ธํ„ฐ๋ž™ํ‹ฐ๋น„ํ‹ฐ์˜ ์ •๋„๊ฐ€ ๋†’์•„์งˆ ์ˆ˜๋ก ์‚ฌ์šฉ์ž์˜ ํ†ต์ œ์„ฑ์ด ๋†’์•„์ง€๊ฒŒ ๋˜๋ฏ€๋กœ ์ด์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž ๋งŒ์กฑ๋„๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ TV๋ผ๋Š” ๋งค์ฒด์˜ ์ˆ˜๋™์ ์ด๋ฉฐ ์—”ํ„ฐํ…Œ์ธ๋จผํŠธ์  ์„ฑ๊ฒฉ์ด ๊ฐ•ํ•œ ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•˜์—ฌ ์‚ฌ์šฉ์ž ๋งŒ์กฑ๋„๊ฐ€ ์–ด๋–ป๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š”์ง€์— ๋Œ€ํ•ด ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” Kano model๊ณผ CPV๊ฐœ๋…์„ ์ ์šฉํ•˜์—ฌ ์˜ˆ์ธกํ•ด ๋ณธ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ์ธํ„ฐ๋ž™ํ‹ฐ๋น„ํ‹ฐ๊ฐ€ ๋งค์šฐ ๋†’์•„์ง€๋Š” ๊ฒฝ์šฐ ์˜คํžˆ๋ ค ๋งŒ์กฑ๋„๊ฐ€ ๋‚ฎ์•„์ง€๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€์œผ๋ฉฐ ์ค‘๊ฐ„ ๋‹จ๊ณ„์˜ ์ธํ„ฐ๋ž™ํ‹ฐ๋น„ํ‹ฐ๋ฅผ ์ œ๊ณตํ•˜๋Š” ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ TV ๊ด‘๊ณ ์—์„œ ๊ทธ ๋งŒ์กฑ๋„๊ฐ€ ๊ฐ€์žฅ ๋†’์œผ๋ฉฐ attractive quality๋กœ ์ธ์‹ํ•˜๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค.OAIID:oai:osos.snu.ac.kr:snu2008-01/104/0000025799/16SEQ:16PERF_CD:SNU2008-01EVAL_ITEM_CD:104USER_ID:0000025799ADJUST_YN:NEMP_ID:A075458DEPT_CD:611CITE_RATE:0FILENAME:์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ_TV_๊ด‘๊ณ ์˜_์ธํ„ฐ๋ž™ํ‹ฐ๋น„ํ‹ฐ_์ฆ๊ฐ€์—_๋”ฐ๋ฅธ_์‚ฌ์šฉ์ž_๋งŒ์กฑ๋„_๋ณ€ํ™”_์—ฐ๊ตฌ.pdfDEPT_NM:๋””์ž์ธํ•™๋ถ€EMAIL:[email protected]:

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    We are living in a media community. In other words, we live in flood of information. For that reason, it is very important to find correct informations and control them to human life. In this point of view, the question about how to read a media text is the prior issue of media literacy. In education, the improvement of media literacy is essential to learners

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ตญ์–ด๊ต์œก๊ณผ,2003.Maste

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ตญ์–ด๊ต์œก๊ณผ(๊ตญ์–ด๊ต์œก์ „๊ณต),2008.Docto

    Comparison of documentation completeness between the paper-based medical record and the electronic medical record : based on the first visit outpatient

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    ๋ณ‘์›ํ–‰์ •ํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€]๊ตญ๋‚ด์—์„œ๋Š” ๊ธฐ์กด ๋Œ€ํ˜• ๋ณ‘์›๊ณผ ์‹ ์„ค ๋ณ‘์›์„ ์ค‘์‹ฌ์œผ๋กœ ์ „์ž์˜๋ฌด๊ธฐ๋ก ๋„์ž…์ด ์ ์ฐจ ํ™•์‚ฐ๋˜๊ณ  ์žˆ๋Š” ์ถ”์„ธ์ด๋ฉฐ, ์ „์ž์˜๋ฌด๊ธฐ๋ก ๋„์ž… ์‹œ ์‚ฌ์šฉ์ž ๋งŒ์กฑ์„ ์œ„ํ•œ ๊ธฐ๋Šฅ ๊ตฌํ˜„๋„ ์ค‘์š”ํ•˜์ง€๋งŒ ์ „์ž์˜๋ฌด๊ธฐ๋ก์œผ๋กœ ์ž‘์„ฑ๋˜๋Š” ์˜๋ฌด๊ธฐ๋ก์˜ ์ถฉ์‹ค๋„๋ฅผ ํ™•๋ณดํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€์žฅ ํฐ ๊ด€๊ฑด์ด๋‹ค. ์ด์— ์™ธ๋ž˜ ์ง„๋ฃŒ์— ์ „์ž์˜๋ฌด๊ธฐ๋ก ์ ์šฉ ์‹œ ์™ธ๋ž˜์˜๋ฌด๊ธฐ๋ก์˜ ํ•ญ๋ชฉ๋ณ„ ๊ธฐ์žฌ์—ฌ๋ถ€๋ฅผ ํ†ตํ•œ ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก๊ณผ์˜ ๊ธฐ์žฌ ์ถฉ์‹ค๋„๋ฅผ ๋น„๊ตํ•˜๊ณ , ์˜๋ฌด๊ธฐ๋ก์˜ ๊ธฐ์žฌ ์ถฉ์‹ค๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์„ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์ „์ž์˜๋ฌด๊ธฐ๋ก์„ ๋„์ž…ํ•œ ํ•œ ๋Œ€ํ•™๋ณ‘์›์˜ ์ดˆ์ง„ ์™ธ๋ž˜์˜๋ฌด๊ธฐ๋ก ์ค‘ 1998๋…„ ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก๊ณผ 2005๋…„ ์ „์ž์˜๋ฌด๊ธฐ๋ก์„ ๋Œ€์ƒ์œผ๋กœ ๋‚ด๊ณผ๊ณ„, ์™ธ๊ณผ๊ณ„, ์†Œ์•„๊ณผ ์„ ํƒ์ง„๋ฃŒ์˜์˜ 1์ˆœ์œ„ ๋˜๋Š” 2์ˆœ์œ„ ์งˆํ™˜(์ฆ์ƒ)์„ ์„ ์ •ํ•˜์—ฌ ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก๊ณผ ์ „์ž์˜๋ฌด๊ธฐ๋ก ๊ฐ 380๊ฑด์”ฉ ์ด 760๊ฑด์˜ ์˜๋ฌด๊ธฐ๋ก์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ์ฃผํ˜ธ์†Œ, ํ˜„๋ณ‘๋ ฅ, ๋ฌธ์ง„์†Œ๊ฒฌ, ๊ณผ๊ฑฐ๋ ฅ, ์‹ ์ฒด๊ฒ€์ง„, ์‹ ์ฒด๊ณ„์ธก, ์ถ”์ •์ง„๋‹จ, ํ™˜์ž๊ธฐ๋ณธ์ •๋ณด, ์ž‘์„ฑ์ž ์„œ๋ช…์˜ ์ด 9ํ•ญ๋ชฉ ์ถฉ์‹ค๋„ ์ ์ˆ˜๋ฅผ ์ธก์ •ํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๊ณผ๋ฅผ ์–ป์—ˆ๋‹ค.์ฒซ์งธ, ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก๊ณผ ์ „์ž์˜๋ฌด๊ธฐ๋ก ์ถฉ์‹ค๋„๋Š” ํ™˜์ž๊ธฐ๋ณธ์ •๋ณด์™€ ์ž‘์„ฑ์ž ์„œ๋ช… ํ•ญ๋ชฉ์„ ํฌํ•จํ•œ 9ํ•ญ๋ชฉ๊ณผ ์ด๋ฅผ ์ œ์™ธํ•œ 7ํ•ญ๋ชฉ์œผ๋กœ ๋‚˜๋ˆ„์–ด ๋น„๊ตํ•˜์˜€๋‹ค. 9ํ•ญ๋ชฉ ์ถฉ์‹ค๋„๋Š” ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก์— ๋น„ํ•ด ์ „์ž์˜๋ฌด๊ธฐ๋ก์ด ๋†’์•˜์œผ๋‚˜, 7ํ•ญ๋ชฉ ์ถฉ์‹ค๋„๋Š” ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก์ด ๋†’์•˜๋‹ค.๋‘˜์งธ, ์ง„๋ฃŒ๊ณผ๋ณ„ ๊ธฐ์žฌ ์ถฉ์‹ค๋„์—์„œ๋Š” ๋‚ด๊ณผ๊ณ„, ์™ธ๊ณผ๊ณ„๋Š” ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก์ด ๋†’์•˜๊ณ , ์†Œ์•„๊ณผ๋Š” ์ „์ž์˜๋ฌด๊ธฐ๋ก์ด ๋†’์•˜๋‹ค. ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก๊ณผ ์ „์ž์˜๋ฌด๊ธฐ๋ก ๋ชจ๋‘ ์™ธ๊ณผ๊ณ„์— ๋น„ํ•ด ๋‚ด๊ณผ๊ณ„์˜ ์ถฉ์‹ค๋„๊ฐ€ ๋†’์•˜๋‹ค.์…‹์งธ, ํ•ญ๋ชฉ๋ณ„ ๊ธฐ์žฌ ์ถฉ์‹ค๋„๋Š” ์ฃผํ˜ธ์†Œ๊ฐ€ ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก๊ณผ ์ „์ž์˜๋ฌด๊ธฐ๋ก์—์„œ ์ถฉ์‹ค๋„๊ฐ€ ๊ฐ€์žฅ ๋†’์€ ํ•ญ๋ชฉ์ด์—ˆ์œผ๋ฉฐ, ์ถฉ์‹ค๋„์— ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์ธ ํ•ญ๋ชฉ์€ ๋ฌธ์ง„์†Œ๊ฒฌ, ๊ณผ๊ฑฐ๋ ฅ, ํ™˜์ž๊ธฐ๋ณธ์ •๋ณด, ์ž‘์„ฑ์ž ์„œ๋ช…์ด์—ˆ๋‹ค.๋„ท์งธ, ๋‚ด๊ณผ๊ณ„, ์™ธ๊ณผ๊ณ„ ๋ฐ ์†Œ์•„๊ณผ๊ฐ„ ๊ธฐ์žฌ ์ถฉ์‹ค๋„๋Š” ํ•ญ๋ชฉ๋ณ„๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ๊ฐ™์€ ์งˆํ™˜(์ฆ์ƒ)์„ ์ง„๋ฃŒํ•œ ๋™์ผ ์ง„๋ฃŒ๊ณผ ๋‚ด ์˜์‚ฌ๊ฐ„ ๊ธฐ์žฌ ์ถฉ์‹ค๋„๋Š” ์ˆœํ™˜๊ธฐ๋‚ด๊ณผ, ํ˜ธํก๊ธฐ๋‚ด๊ณผ, ์™ธ๊ณผ, ํ‰๋ถ€์™ธ๊ณผ, ์ •ํ˜•์™ธ๊ณผ, ์†Œ์•„๊ณผ๊ฐ€ ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก์—์„œ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€์œผ๋ฉฐ, ์ˆœํ™˜๊ธฐ๋‚ด๊ณผ, ๋‚ด๋ถ„๋น„๋‚ด๊ณผ, ์™ธ๊ณผ, ํ‰๋ถ€์™ธ๊ณผ, ์ •ํ˜•์™ธ๊ณผ๋Š” ์ „์ž์˜๋ฌด๊ธฐ๋ก์—์„œ ์œ ์˜ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค.๋‹ค์„ฏ์งธ, ์˜๋ฌด๊ธฐ๋ก์˜ ๊ธฐ์žฌ ์ถฉ์‹ค๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„ ํ•˜์˜€๋‹ค. ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก๊ณผ ์ „์ž์˜๋ฌด๊ธฐ๋ก ๊ฐ๊ฐ์˜ ์ถฉ์‹ค๋„์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๋ณ€์ˆ˜๋Š” ์ง„๋ฃŒ๊ณผ์™€ ์„ธ์…˜๋ณ„ ์™ธ๋ž˜ํ™˜์ž์ˆ˜์ด์—ˆ์œผ๋ฉฐ, ์„ธ์…˜๋ณ„ ์™ธ๋ž˜ํ™˜์ž์ˆ˜๊ฐ€ ๋งŽ์„์ˆ˜๋ก ์ถฉ์‹ค๋„๊ฐ€ ๋‚ฎ์•˜๊ณ , ์„ ํƒ์ง„๋ฃŒ์˜ ์—ฐ๋ น์€ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค.๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ ์ „์ž์˜๋ฌด๊ธฐ๋ก์ด ์ˆ˜๊ธฐ์˜๋ฌด๊ธฐ๋ก์— ๋น„ํ•˜์—ฌ ํ˜„์ €ํžˆ ๋†’์€ ์ถฉ์‹ค๋„๋ฅผ ๋ณด์ด์ง€๋Š” ๋ชปํ•˜์˜€์ง€๋งŒ ํ™˜์ž๊ธฐ๋ณธ์ •๋ณด, ์ž‘์„ฑ์ž ์„œ๋ช… ๋“ฑ ์ „์‚ฐ์‹œ์Šคํ…œ์˜ ์ง€์›์„ ๋ฐ›์„ ์ˆ˜ ์žˆ๋Š” ํ•ญ๋ชฉ์—์„œ๋Š” ํ˜„์ €ํ•œ ์ฐจ์ด๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ์ž‘์„ฑ์ž์˜ ๊ธฐ๋กํ•˜๋Š” ๋…ธ๋ ฅ์„ ์ค„์—ฌ์ฃผ๊ณ , ์ž…๋ ฅ์„ ์šฉ์ดํ•˜๊ฒŒ ์ „์ž์˜๋ฌด๊ธฐ๋ก ์ž…๋ ฅ ๋ฐฉ์‹์„ ๊ณ ์•ˆํ•จ์œผ๋กœ์จ ์ „์ž์˜๋ฌด๊ธฐ๋ก ์ถฉ์‹ค๋„๋ฅผ ๋†’์ผ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋œ๋‹ค. [์˜๋ฌธ]An electronic medical record has been introduced starting from existing large hospitals and newly established hospitals and its use is now gradually increased in our country. When introducing the electronic medical record, though the realization of user friendly system is considered to be important, the most important concern should be to ensure its completeness documented by the system. Thus, in case the electronic medical record applied in an outpatient medical practice, I compared its completeness with that of paper-based medical record by investigating whether each item is documented or not and also investigated factors affecting completeness of medical records as well. I investigated a total of 760 cases (paper 380, electronic 380) selecting from the highest and the second highest rate of diseases from the areas of internal medicine, the areas of surgery, and pediatrics on the paper-based medical record of 1998 and the electronic medical record of 2005. Results were conclude as follows by measuring the completeness scores of 9 factors such as chief complaints, present illness, review of systems, past history, physical examination, vital signs, impression, demographics information of patients, and signature of doctor.First, the completeness score for the 9 items was higher in the electronic medical record than that of the paper-based medical record, while the completeness score for the 7 items excluding patient''s demographics information and signature of doctor was higher in the paper-based medical record.Second, in completeness according to departments, the areas of internal medicine and the areas of surgery showed higher completeness in the paper-based medical record, and pediatrics showed higher completeness in the electronic medical record.Third, in completeness according to documented items, completeness in chief complaints was the highest in both paper-based medical record and electronic medical record, but there were significant differences in items such as review of system, past history, patient''s demographics information, and signature of doctor.Fourth, there were significant differences in completeness according to documented items among the areas of internal medicine, the areas of surgery, and pediatrics.Fifth, multiple regression analysis was done to analyze factors affecting documentation completeness in the medical records. The factors significantly affecting on each completeness in the paper-based medical record and electronic medical record were departments and the number of outpatients by session. Completeness was getting low with the increasing the number of outpatient by session and specialist doctorโ€™s age was not significant.When considering the results of the study, although completeness in the electronic medical record was not shown to be remarkably higher than the paper-based medical record. But, there were significant differences in the items that can get support from a computerized system such as patient''s demographics information and signature of doctor. It is considered that by contriving the easier way of input to the electronic medical record to reduce doctor''s efforts, the higher completeness in electronic medical record could be achieved.ope

    A study on the persuasive discourse evaluation aspects and awareness of Korean language teachers

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    ์ด ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ๊ตญ์–ด๊ณผ ๊ต์‚ฌ๋“ค์˜ ์„ค๋“ ๋‹ดํ™” ํ‰๊ฐ€ ์–‘์ƒ์„ ์‚ดํŽด์„œ ๊ทธ๋“ค์ด ์„ค๋“ ๋‹ดํ™”๋ฅผ ํ‰๊ฐ€ํ•  ๋•Œ ์–ด๋–ค ์ ์— ์ฃผ๋ชฉํ•˜๊ณ  ์žˆ๊ณ , ์™œ ๊ทธ๋Ÿฌํ•œ์ง€๋ฅผ ๋ฐํžˆ๋Š” ๊ฒƒ์ด๋‹ค. ํ˜„์žฌ ํ•™๊ต ๊ต์œก ๊ฐœํ˜ ๋ฐ ๊ต์œก๊ณผ์ • ๊ฐœ์ •์˜ ๋ฐฉํ–ฅ์€ ํ˜„์žฅ ๊ต์‚ฌ๋“ค์—๊ฒŒ ํ‰๊ฐ€ ์ „๋ฌธ์„ฑ์„ ์š”๊ตฌํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„์‹ค์ ์œผ๋กœ ํ˜„์žฅ ๊ต์‚ฌ๋“ค์€ ์ด์— ๋Œ€ํ•œ ๋Œ€๋น„๋ฅผ ํ•˜๊ณ  ์žˆ์ง€ ๋ชปํ•˜๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๊ต์‚ฌ๋“ค์˜ ํ‰๊ฐ€ ์–‘์ƒ์„ ํ†ตํ•ด ๊ทธ๋“ค์ด ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋งํ•˜๊ธฐ ํ‰๊ฐ€์— ๋Œ€ํ•œ ์ธ์‹๊ณผ ๋ฌธ์ œ์ ์„ ํŒŒ์•…ํ•˜๋Š” ๊ฒƒ์ด ์‹œ๊ธ‰ํ•˜๋‹ค๊ณ  ๋ณด์•˜๋‹ค. ์ด์— ๋ณธ๊ณ ๋Š” ๊ตญ์–ด๊ณผ ๊ต์‚ฌ๋“ค์˜ ์„ค๋“ ๋‹ดํ™” ํ‰๊ฐ€ ์–‘์ƒ์„ ํ†ตํ•ด ๊ทธ๋“ค์˜ ์ธ์‹์„ ํƒ์ƒ‰ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ๊ตญ์–ด๊ณผ ๊ต์‚ฌ๋“ค์€ ์„ค๋“ ๋‹ดํ™” ํ‰๊ฐ€์™€ ๊ด€๋ จํ•˜์—ฌ ๊ฐ์„ฑ ์„ค๋“ ์ „๋žต์ด ํ™œ์šฉ๋œ ๋‹ดํ™”์— ๋Œ€ํ•ด์„œ๋Š” ๊ต์‚ฌ๋“ค ๊ฐ„์— ์—‡๊ฐˆ๋ฆฐ ํ‰๊ฐ€ ์–‘์ƒ์„ ๋ณด์˜€์œผ๋ฉฐ, ๋™์ผํ•œ ๋‹ดํ™”๋ฅผ ํ‰๊ฐ€ํ•  ๋•Œ, ์–ด๋–ค ํ‰๊ฐ€ ๋ฐฉ๋ฒ•์„ ์ ์šฉํ•˜๋Š๋ƒ์— ๋”ฐ๋ผ ํ‰๊ฐ€ ๊ธฐ์ค€์„ ๋‹ฌ๋ฆฌ ์„ค์ •ํ•˜๋Š” ์–‘์ƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์‹ฌ์ธต ๋ฉด๋‹ด ๊ฒฐ๊ณผ, ์ด๋Ÿฌํ•œ ํ‰๊ฐ€ ์–‘์ƒ์˜ ์›์ธ์ด ๊ตญ์–ด๊ณผ ๊ต์‚ฌ๋“ค์˜ ์„ค๋“ ๋‹ดํ™” ๋ณธ์งˆ์— ๋Œ€ํ•œ ์ดํ•ด์™€ ๋‹ดํ™” ํ‰๊ฐ€ ์ƒํ™ฉ์— ๋Œ€ํ•œ ์˜์‹์—์„œ ๋น„๋กฏ๋˜์—ˆ์Œ์„ ํŒŒ์•…ํ•˜์˜€๋‹ค. The current direction of secondary education reform and curriculum revision demands teacher's assessment competence. However, on-site teachers are not prepared yet. To resolve it, it is very necessary to understand their awareness through teachers' actual evaluation aspects. This paper explored their awareness through persuasive discourse evaluation aspect of Korean language teachers. As a result, teachers differently evaluated the discourse by utilizing the emotional appeal in relation to the persuasive discourse evaluation. In addition, upon evaluating the same discourse, it was confirmed that the aspects to set up the different standards for evaluation were shown based on evaluation methods. As a result of in-depth interviews, we understood that the cause of this evaluation aspect came from the awareness of understanding the essence of persuasive discourse and discourse evaluation situation of Korean language teachers
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