• 제목/요약/키워드: Role Models

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전략적 방법을 활용한 역할극 연구: 언어습득시기의 의사소통능력 향상을 중심으로 (On the study of role play using the strategic methodology: With respect to the communicative competence improvement in language acquisition period)

  • 최숙희;김성헌
    • 영어어문교육
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    • 제11권1호
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    • pp.203-224
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    • 2005
  • The purpose of this study is to justify the effects of role play with respect to speaking and listening functions and to provide the strategic methodology for improving English communicative competence of fifth grade primary school students. We can expand role play as a strategic teaching method to develop English learning models, so that English can be more easily acquired to the students who are in the critical language acquisition period. Strategic role play reflects the events and experiences of many kinds of people in everyday life. It is suggested that one of the best methods to improve English communicative competence in the primary classroom is through role play. Students can develop meaning for language patterns by portraying situations in which these instances in language would be used. This study proposes to facilitate English communicative ability using various student-centered role play strategies. It is concluded that the student-centered activities using strategic role play help the students to improve their English communicative competence. This is done by deriving their own creative dialogues and presenting the role play with their interests in learning English and with subsequently positive learning effects.

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간호사의 역할개념 양상과 간호직에 대한 헌신몰입에 관한 연구 (Korean Nurses과 Nursing Role Conceptions and Professional Commitment)

  • 이상미
    • 대한간호학회지
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    • 제21권3호
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    • pp.307-322
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    • 1991
  • The purpose of this exploratory study was to analyze nursing role conceptions and test the relationships between nursing role conceptions and professional commitment among selected Korean nurses. Data were obtained from a convenience sample of 262 practising nurses of varying positions, education, and experience. The total sample represents a response rate of 93 percent. Subscales of Nursing Role Conceptions (Pieta, 1976) were used to measure professional, service, and bureaucratic role conceptions 1 the tool to measure professional commitment was developed by the investigator. The results of this study were as follows. 1. Professional role conception and service role conception were positively related(normative r= .61 : categorical r= .64). Bureaucratic role conception scores(32.6$\pm$4.97) were higher than professional and service role conception scores. 2. Experience was positively related to bureaucratic professional categorical role conception(r= .17, p< .01), and negatively related to bureaucratic professional role discrepancy(r=- .12, p< .01). There was no relationship between experience and service role conception. This study also showed that nurses who had longer experience tended to have higher role conceptions on all three subscales. 3. Nurses with a master's degree had significantly higher professional and bureaucratic role conceptions scores. Bacealaureates graduates had the lowest bureaucratic categorical role conception scores ; associate nurses had the lowest professional categorical role conception scores. 4. Nursing supervisors and head nurses had significantly higher bureaucratic categorical role coneption scores, whereas they had lower bureaucratic normative and professional role conception scores. 5. Age and experience were positively related to professional commitment (r= .24, r= .28). Hierarchical multiple regression analyses showed that the combination of nursing role conceptions explained greater variance in professional commitment pair of the variables alone. Further research employing dynamic designs is needed to execute rigorous tests of causal models of nursing role conceptions and professional commitment. The findings of this study suggest that antecedents and moderating variables of nursing role conception and professional commitment need to be explored for further theoretical. specification and empirical evaluation.

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독서역할모델 및 독서유효성이 중학생의 학업성취에 미치는 영향 연구 (A Study on the Effect of Reading Role Model, Reading Effectiveness on Academic Achievement of Middle School Student)

  • 정대근
    • 한국문헌정보학회지
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    • 제51권4호
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    • pp.139-160
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    • 2017
  • 이 연구의 목적은 독서역할모델(부모, 교사, 친구)과 독서유효성(독서지속의지, 독서몰입, 독서만족)이 중학생의 학업성취(국어성적, 내신성적)에 미치는 영향을 조사하는 것이다. 분석결과, 국어성적에 영향을 미친 요인은 독서역할모델 중 아버지(1.9%)와 어머니(3.4%)였으며, 독서유효성 요인 중에는 독서지속의지(8%)만 유일하게 영향을 미쳤다. 내신성적의 경우 독서역할모델 요인 중 어머니(3.4%)만 유일하게 영향을 미쳤으며, 독서유효성은 독서지속의지(10.4%), 독서몰입(4.0%), 독서만족(1.9%) 모든 요인에서 영향을 미쳤다. 그러나 독서지속의지를 제외하고는 그 영향력이 미미하였다.

APDM : Adding Attributes to Permission-Based Delegation Model

  • Kim, Si-Myeong;Han, Sang-Hoon
    • 한국컴퓨터정보학회논문지
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    • 제27권2호
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    • pp.107-114
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    • 2022
  • 위임은 사용자에게 접근 권한을 사상(mapping)하여 유연하고 동적인 접근제어 결정을 제공하는 강력한 메카니즘이다. 또한, 분산환경에 유용하다. 대표적인 위임 모델 중 RBDM0 와 RDM200은 사용자 대 사용자 위임으로서 역할위임이다. 그러나, RBAC에서 역할계층의 상속 개념은 실 기업 조직의 관리 규칙과 조화롭지 못하다. 본 논문에서 우리는 위임 권한의 영속성을 보장하고 의무 분리 원칙과 최소 권한의 보안 원칙에 위배되지 않는 속성을 첨가한 권한위임 모델 (APDM)을 제안한다. RBAC모델을 기반으로 하는 APDM은 속성을 사용하여 역할 대 역할과 사용자 대 사용자의 위임을 제공한다. 위임자는 원하는 권한만을 특정인에게 위임할 수 있고, 속성을 활용하여 위임자가 원하는 시점에서 권한을 회수할 수 있다.

간접 경험 및 롤 모델이 창업의지에 미치는 영향 (Influence of Indirect Experiences and Role Models on Entrepreneurial Intentions)

  • 장수진;정병규
    • 벤처혁신연구
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    • 제5권2호
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    • pp.35-48
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    • 2022
  • 본 연구는 창업의지에 미치는 영향을 분석하고 어떤 요인이 가장 큰 영향을 미치는지에 대해 실증적으로 분석하기 위해 이루어졌다. 이를 위해 창업의지에 미치는 영향요인으로 자아성취동기, 간접경험, 롤모델, 사업가에 대한 인식, 실패부담감을 독립변수로 설정하였다. 이를 실증적으로 분석하기 위하여 일반인을 대상으로 유효한 데이터 399개를 분석 대상으로 하였다. 통계분석에는 SPSS 25.0를 활용하였다. 본 연구의 실증 분석 결과, 자아성취동기, 간접경험, 롤모델, 사업가에 대한 인식, 실패부담감은 창업의지에 유의한 정(+)의 영향을 미치는 것으로 나타났다. 본 연구 결과는 창업의지에 영향을 미치는 요인 중에서도 자아성취동기가 가장 큰 영향을 미치는 것을 확인하였으며, 이론형 창업강좌, 창업특강, 부모나 지인들의 창업 유무 등 간접경험과 롤모델이 창업의지에 영향을 미치는 것을 실증적으로 분석하였다는 측면에서 의의가 있다.

Forecasting Chinese Yuan/USD Via Combination Techniques During COVID-19

  • ASADULLAH, Muhammad;UDDIN, Imam;QAYYUM, Arsalan;AYUBI, Sharique;SABRI, Rabia
    • The Journal of Asian Finance, Economics and Business
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    • 제8권5호
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    • pp.221-229
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    • 2021
  • This study aims to forecast the exchange rate of the Chinese Yuan against the US Dollar by a combination of different models as proposed by Poon and Granger (2003) during the Covid-19 pandemic. For this purpose, we include three uni-variate time series models, i.e., ARIMA, Naïve, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Chinese Yuan against the US dollar by two combination criteria i.e. var-cor and equal weightage. After finding out the individual accuracy, the models are then assessed through equal weightage and var-cor methods. Our results suggest that Naïve outperforms all individual & combination of time series models. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models except the Naïve model, with the lowest MAPE value of 0764. The results suggesting that the Chinese Yuan exchange rate against the US Dollar is dependent upon the recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting which commensurate with the literature.

Forecasting Exchange Rates: An Empirical Application to Pakistani Rupee

  • ASADULLAH, Muhammad;BASHIR, Adnan;ALEEMI, Abdur Rahman
    • The Journal of Asian Finance, Economics and Business
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    • 제8권4호
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    • pp.339-347
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    • 2021
  • This study aims to forecast the exchange rate by a combination of different models as proposed by Poon and Granger (2003). For this purpose, we include three univariate time series models, i.e., ARIMA, Naïve, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Pakistani Rupee against the US dollar by a combination of different forecasting techniques. The observations from M1 2020 to M12 2020 are held back for in-sample forecasting. The models are then assessed through equal weightage and var-cor methods. Our results suggest that NARDL outperforms all individual time series models in terms of forecasting the exchange rate. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models with the lowest MAPE value of 0.612 suggesting that the Pakistani Rupee exchange rate against the US Dollar is dependent upon the macro-economic fundamentals and recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting, as stated by Poon and Granger (2003).

Gaussian models for bond strength evaluation of ribbed steel bars in concrete

  • Prabhat R., Prem;Branko, Savija
    • Structural Engineering and Mechanics
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    • 제84권5호
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    • pp.651-664
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    • 2022
  • A precise prediction of the ultimate bond strength between rebar and surrounding concrete plays a major role in structural design, as it effects the load-carrying capacity and serviceability of a member significantly. In the present study, Gaussian models are employed for modelling bond strength of ribbed steel bars embedded in concrete. Gaussian models offer a non-parametric method based on Bayesian framework which is powerful, versatile, robust and accurate. Five different Gaussian models are explored in this paper-Gaussian Process (GP), Variational Heteroscedastic Gaussian Process (VHGP), Warped Gaussian Process (WGP), Sparse Spectrum Gaussian Process (SSGP), and Twin Gaussian Process (TGP). The effectiveness of the models is also evaluated in comparison to the numerous design formulae provided by the codes. The predictions from the Gaussian models are found to be closer to the experiments than those predicted using the design equations provided in various codes. The sensitivity of the models to various parameters, input feature space and sampling is also presented. It is found that GP, VHGP and SSGP are effective in prediction of the bond strength. For large data set, GP, VHGP, WGP and TGP can be computationally expensive. In such cases, SSGP can be utilized.