• Title/Summary/Keyword: e-learning characteristics

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The Characteristic Analysis of Content Areas and Behavioral Areas Based on the Deviation of NAEA Achievement Level-Based Correct-Answer Rate (국가수준 학업성취도 평가의 성취수준별 정답률 편차에 따른 내용 영역과 행동 영역 특성 분석)

  • Huh, Nan;Yang, Seong Hyun
    • Communications of Mathematical Education
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    • v.32 no.3
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    • pp.435-453
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    • 2018
  • The results analysis of National Assessment of Educational Achievement(NAEA) can provide various implications for teaching and learning in the school field. In this study we analyzed the deviation of NAEA achievement level-based correct-answer rate and the distribution of the responses percentages for three years from 2015 to 2017 focused on multiple-choice items. First we calculated the deviation of correct-answer rate between advanced level and proficient level and between proficient level and basic level, and then we selected the items whose deviation of correct-answer rate is more than the third quartile. We explored what the content areas, behavior areas and achievement standards of each item are and what the achievement standards and characteristics of these questions are. Based on the results of the analysis, we intended to derive implications for appropriate teaching-learning methods at each achievement-level.

Teaching and Learning Effects of Structural-Mapping used Instruction in Permutation and Combination (구조적 동형을 활용한 순열과 조합의 교수.학습 효과)

  • Kim, Won-Kyoung;Hong, Gab-Ryong;Lee, Jong-Hak
    • Communications of Mathematical Education
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    • v.25 no.3
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    • pp.607-627
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    • 2011
  • The purpose of this study is to analyse teaching and learning effects of the structural-mapping used instruction and to find out the characteristics of problem solving process in permutation and combination. For this study, two classes of 11th grade students(67 students) were randomly selected from S high school in D city. One of them was assigned to the experimental group and the other to the control group, respectively. Four lectures of the structural-mapping used instruction were carried out in the experimental group and same amount of lectures of the text book oriented instruction were carried out in the control group. The research findings are as follows. First, the structural-mapping used instruction is shown to be more effective in achievement than the traditional textbook-oriented instruction. Second, the ball-box model is found out to be easier and simpler than the selection-distribution model. Third, students who used the ball-box model are properly able to use both model.

Patient safety practices in Korean hospitals (우리나라 병원의 환자안전 향상을 위한 활동 현황)

  • Hwang, Soo-Hee;Kim, Myung-Hwa;Park, Choon-Seon
    • Quality Improvement in Health Care
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    • v.22 no.2
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    • pp.43-73
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    • 2016
  • Purpose: The aims of this study were to assess the presence of core patient safety practices in Korean hospitals and assess the differences in reporting and learning systems of patient safety, infrastructure, and safe practices by hospital characteristics. Methods: The authors developed a questionnaire including 39 items of patient safety staffing, health information system, reporting system, and event-specific prevention practices. The survey was conducted online or e-mail with 407 tertiary, general and specialty hospitals. Results: About 90% of hospitals answered the self-reporting system of patient safety related events is established. More than 90% of hospitals applied incidence monitoring or root cause analysis on healthcare-associated infection, in-facility pressure ulcers and falls, but only 60% did on surgery/procedure related events. More than 50% of the hospitals did not adopted present on admission (POA) indicators. One hundred (80.0%) hospitals had a department of patient safety and/or quality and only 52.8% of hospitals had a patient safety officer (PSO). While 82.4% of hospitals used electronic medical records (EMRs), only 53% of these hospitals adopted clinical decision support function. Infrastructure for patient safety except EMRs was well established in training, high-level and large hospitals. Most hospitals implemented prevention practices of adverse drug events, in-facility pressure ulcers and falls (94.4-100.0%). But prevention practices of surgery/procedure related events had relatively low adoption rate (59.2-92.8%). Majority of prevention practices for patient safety events were also implemented with a relatively modest increase in resources allocated. Conclusion: The hospital-based reporting and learning system, EMRs, and core evidence-based prevention practices were implemented well in high-level and large hospitals. But POA indicator and PSO were not adopted in more than half of surveyed hospitals and implementation of prevention practices for specific event had low. To support and monitor progress in hospital's patient safety effort, national-level safety practices set is needed.

The Classification Using Probabilistic Neural Network and Redundancy Reduction on Very Large Scaled Chemical Gas Sensor Array (대규모 가스 센서 어레이에서 중복도의 제거와 확률신경회로망을 이용한 분류)

  • Kim, Jeong-Do;Lim, Seung-Ju;Park, Sung-Dae;Byun, Hyung-Gi;Persaud, K.C.;Kim, Jung-Ju
    • Journal of Sensor Science and Technology
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    • v.22 no.2
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    • pp.162-173
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    • 2013
  • The purpose of this paper is to classify VOC gases by emulating the characteristics found in biological olfaction. For this purpose, we propose new signal processing method based a polymeric chemical sensor array consisting of 4096 sensors which is created by NEUROCHEM project. To remove unstable sensors generated in the manufacturing process of very large scaled chemical sensor array, we used discrete wavelet transformation and cosine similarity. And, to remove the supernumerary redundancy, we proposed the method of selecting candidates of representative sensor representing sensors with similar features by Fuzzy c-means algorithm. In addition, we proposed an improved algorithm for selecting representative sensors among candidates of representative sensors to better enhance classification ability. However, Classification for very large scaled sensor array has a great deal of time in process of learning because many sensors are used for learning though a redundancy is removed. Throughout experimental trials for classification, we confirmed the proposed method have an outstanding classification ability, at transient state as well as steady state.

Analysis of pre-service teachers' cognition on a teacher education program in technology-friendly flipped classroom (공학 도구 친화적 거꾸로 수업에서 예비교사의 인식 분석)

  • Kim, Dong-Joong;Kim, Daesang;Choi, Sang-Ho
    • Communications of Mathematical Education
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    • v.32 no.4
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    • pp.455-475
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    • 2018
  • The purpose of this study is to investigate characteristics of pre-service teachers' cognition about learning through the use of technology by employing a teacher education program in the use of technology-friendly flipped classroom. For this purpose, 45 pre-service teachers participated in the study and they completed both pre- and post-surveys including questions about Technology Adopter Category Index(TACI) and Technological Pedagogical Content Knowledge(TPACK). They were also asked to write self-reflections on mathematics softwares(Geometer's Sketch Pad(GSP), Geogebra, Cabri 3D). Results show that the teacher education program in the use of technology-friendly flipped classroom affected pre-service teachers' cognitions of TACI and TPACK, and they perceived that technology integration helped students' mathematics learning process. Findings from this study indicate that ideas about how to develop a technology-friendly teacher education program are more specified..

Development of a Tool to Measure Math Anxiety Factors for High School Students and Validation of Validity (고등학생용 수학불안 요인 측정 도구 개발 및 타당도 검증)

  • Kang, Yanggu;Han, Sunyoung
    • Communications of Mathematical Education
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    • v.36 no.2
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    • pp.201-227
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    • 2022
  • The purpose of this study was to develop an instrument measuring mathematics anxiety suitable for Korean High school students. In order to achieve this study purpose, the study was conducted according to the procedure of setting components of mathematics anxiety, developing questions, and verifying validity and reliability. First, in order to set the components of mathematic anxiety, previous studies on mathematic anxiety. Through this, six factors of mathematic anxiety were derived. Next, new questions were developed for each of the six constituent factors. The 122 questions were revised and supplemented through two content validity tests, and the final instrument for mathematics anxiety consisted of 49 questions of 6 factors. Finally, to verify the validity and reliability of the measurement instrument for mathematics anxiety, a survey was conducted on 1,848 students from 16 universities in Seoul and the metropolitan area. Next, a validity analysis was conducted with the 1,645 responses, excluding students who answered that there was no mathematics anxiety. As a result of exploratory factor analysis, 15 out of 49 questions were removed. Six factors were named individual characteristics, pressure on achievement, abstraction in mathematics, teaching and learning style, parental attitudes, and cumulative mathematics subjects. As a result of confirmatory factor analysis, the model fit was found to be appropriate, and the convergence validity and discriminant validity were found to be good.

A Case Study of Lesson Design Based on Mathematical Modeling of Pre-Service Mathematics Teachers (중등 예비교사들의 수학적 모델링 기반 수업 설계 사례연구)

  • Choi, Heesun
    • Communications of Mathematical Education
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    • v.36 no.1
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    • pp.59-72
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    • 2022
  • The purpose of this study is to understand the characteristics of the mathematical modeling tasks and lesson designs developed by pre-service teachers based on the inherent awareness of mathematical modeling, considering the importance of creating a task to perform mathematical modeling activity and designing a lesson. As a result, the mathematical modeling tasks developed by pre-service teachers mainly presents an appropriate amount of information using real life contexts for the purpose of learning using concepts, and it showed a tendency to develop to the level of cognitive demand that required procedures with connections to understanding, meaning, or concepts. And most of the developed modeling task-based lessons showed a tendency to design warm-up activity, model-eliciting activity, and model-exploration activity. This result is due to the lack of experience of pre-service teachers in creating mathematical modeling tasks. Therefore, it is necessary to continuously provide opportunities for pre-service teachers to learn concepts or create mathematical modeling tasks intended for exploration according to various mathematical contents, thereby actively cultivating their ability to create modeling tasks in the course of training pre-service teachers. Furthermore, it is necessary to strengthen the expertise in mathematical modeling teaching and learning by providing opportunities to actually perform the mathematical modeling-based classes designed by pre-service teachers and to experience the process of reflecting on the lessons.

Effects of Learner Motivation and Teacher-student Interaction on Learner Satisfaction in Nursing Students (간호대학생의 학습동기와 교수학생 상호작용이 학습만족도에 미치는 영향)

  • Cho, Mi-Kyoung;Kim, Mi Young
    • The Journal of the Korea Contents Association
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    • v.17 no.4
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    • pp.468-477
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    • 2017
  • The purpose of this study was to exam nursing students to verify the effects of self-directed learning readiness, teacher-student interaction, educational performance, stress and learner motivation on learner satisfaction. The study population consisted of second and third year nursing students at E university located in S city. Data were collected between June 15, 2016 to June 24, 2016, and questionnaire comprised items to measure general characteristics, learner motivation, teacher-student interaction, self-directed learning readiness, educational performance, and learner satisfaction. A total of 132 students were included for the final analysis. Learner satisfaction was positively correlated with self-directed learning readiness (r= .21, p= .018), teacher-student interaction (r= .39, p<.001), educational performance (r= .21, p= .014), and learner motivation (r= .75, p<.001). In addition, learner motivation was positively correlated with self-directed learning readiness (r= .24, p= .005), teacher-student interaction (r= .38, p <.001), and educational performance (r= .21, p= .018). Finally, learner motivation and teacher-student interaction were found to explain 59.7% of the variance of learner satisfaction. Our findings suggest strategies and interventions that boost learner motivation and teacher-student interaction which are required to improve learner satisfaction in nursing education.

Development of Performance Indices for Agro-food Distribution Corporations Based on the AHP Method (AHP기법을 이용한 농식품 유통법인 경영진단지표 개발)

  • Kim, Dong-Hwan;Hyun, Jong-Ki
    • Journal of Distribution Science
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    • v.15 no.12
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    • pp.95-102
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    • 2017
  • Purpose - This study aims to develop diagnostic indices for managerial performance of agro-food distribution corporations. In particular, weights of diagnostic indices were estimated using the AHP method. Management diagnosis on agro-food distribution corporations is expected to increase their competitiveness in the domestic market as well as in international markets. Research design, data, and methodology - It develops weights or importance of the diagnostic indices based upon the survey of 21 experts in food distribution management. The survey was carried out using e-mail. Management diagnostic indices were developed based upon four BSC(Balanced Scorecard) perspectives of finance, learning/growth/leadership, customer, and internal process/technology. Results - Diagnostic indices on financial perspective consist on profitability, productivity, growth, stability and activity. Learning and leadership perspective indices consist of management will, CEO leadership, level of learning, innovation, and level of management information system. Customer perspective indices are branding, customer and channel management and internal process/technology indices consist of fourteen sub-indices representing technologies, efficiency, and dynamics. It was estimated that the weight of financial perspective index was 0.3, internal process/technology perspective index 0.248, customer category index 0.247, and learning, growth and leadership perspective index 0.205. This study also estimates weights of sub-indices for managerial diagnosis by four different perspectives. Estimated weight of profitability (0.085) is the greatest among financial perspective indices, followed by stability (0.072), growth (0.053), productivity (0.051), and activity (0.038). While estimated weights of leadership, capability, and information indices are 0.100, 0.061, and 0.044 respectively, weights of marketing, customer management, and quality and service indices are 0.104, 0.093, and 0.051, respectively. Among internal process/technology perspective, estimated weights of efficiency, technology, and innovation indices are 0.106, 0.088, and 0.054, respectively. Conclusions - The diagnostic indices for managerial performance of agro-food distribution corporations would be utilized by agro-food distribution corporations themselves, extension service institutions, and consultants. It is also expected that central and local governments use diagnostic indices developed in this study for the purpose of evaluating the effects of governmental support programs for agro-food distribution corporations. Futhermore researchers and consultants would modify diagnostic indices developed in this study, reflecting characteristics and situation of types of agro-food distribution corporations.

A Study on the Enhancing Recommendation Performance Using the Linguistic Factor of Online Review based on Deep Learning Technique (딥러닝 기반 온라인 리뷰의 언어학적 특성을 활용한 추천 시스템 성능 향상에 관한 연구)

  • Dongsoo Jang;Qinglong Li;Jaekyeong Kim
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.41-63
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    • 2023
  • As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.