• 제목/요약/키워드: learning sources

검색결과 338건 처리시간 0.026초

공학교육에서 평가 횟수 증가와 학업 성취도 향상의 상관관계에 관한 사례연구 (A Case Study on the Improvement of Learning Performance by Increasing the Number of Tests in Engineering Education)

  • 백현덕;박진원
    • 공학교육연구
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    • 제19권6호
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    • pp.57-62
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    • 2016
  • In this work, we present a case study of using the assessments for the enhancement of students' learning motivation in engineering education. The assessments, given in between summative assessments such as midterms and finals, may have a component of formative evaluation, which are reported as very effective tools as the sources of feedback to improve teaching and learning. We studied how the students' performance is improved by additional tests in engineering education. Also, we examined the factors of successful results of the cooperative learning model, Student Teams-Achievement Division, which is based on imposing a number of tests, achieved in our previous work.

Collaboration in a Web-Based Learning Environment: Opportunities and Challenges

  • HAN, Seungyeon
    • Educational Technology International
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    • 제9권2호
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    • pp.123-142
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    • 2008
  • The purpose of this study was to examine how computer conferencing might facilitate collaborative learning for students to engage in meaningful discussion. The participants in this study consisted of the instructor and the students in a graduate level course. Different sources of evidence were used to triangulate the data: in-depth interviews, content analysis of transcripts of discussion, and other archival data including course syllabus, presentation materials, and lecture notes. Participants perceived web-based learning as collaborative process, providing opportunities to share the idea, respect and evaluate different perspectives, and co-construct new insights. Analysis of the data revealed several challenges related collaboration in a web-based learning environment: absence of a sense of community, technical problems, adaptability to different types of learner, and managing the discussion. The data also indicated that a variety of strategies were used to facilitate learning: building a sense of community, technical support, developing instructional methodologies, class size, and design of the content.

Artificial Neural Network Discrimination of Multi-PD Sources Detected by UHF Sensor

  • Lee, Kang-Won;Jang, Dong-Uk;Park, Jae-Yeol;Kang, Seong-Hwa;Lim, Kee-Joe
    • KIEE International Transactions on Electrophysics and Applications
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    • 제3C권1호
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    • pp.5-9
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    • 2003
  • The waveforms of partial discharges (PDs) imply physical and structural properties of PD sources, so analyzing them give us information on the kind of PD sources and the location. Waveforms of PD as a time series function have variable amplitudes but sustain a certain uniform shape, which shows well the characteristics of the waveforms and frequency region. They can also be used as parameters having time and frequency information of PD signals and applied to classification of multiple PDs sources via Artificial Neural Network with back propagation (BP) learning.

Classification of nuclear activity types for neighboring countries of South Korea using machine learning techniques with xenon isotopic activity ratios

  • Sang-Kyung Lee;Ser Gi Hong
    • Nuclear Engineering and Technology
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    • 제56권4호
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    • pp.1372-1384
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    • 2024
  • The discrimination of the source for xenon gases' release can provide an important clue for detecting the nuclear activities in the neighboring countries. In this paper, three machine learning techniques, which are logistic regression, support vector machine (SVM), and k-nearest neighbors (KNN), were applied to develop the predictive models for discriminating the source for xenon gases' release based on the xenon isotopic activity ratio data which were generated using the depletion codes, i.e., ORIGEN in SCALE 6.2 and Serpent, for the probable sources. The considered sources for the neighboring countries of South Korea include PWRs, CANDUs, IRT-2000, Yongbyun 5 MWe reactor, and nuclear tests with plutonium and uranium. The results of the analysis showed that the overall prediction accuracies of models with SVM and KNN using six inputs, all exceeded 90%. Particularly, the models based on SVM and KNN that used six or three xenon isotope activity ratios with three classification categories, namely reactor, plutonium bomb, and uranium bomb, had accuracy levels greater than 88%. The prediction performances demonstrate the applicability of machine learning algorithms to predict nuclear threat using ratios of xenon isotopic activity.

Using Kirkpatrick's Evaluation Model in a Multimedia-based Blended Learning Environment

  • Embi, Zarina Che;Neo, Tse-Kian;Neo, Mai
    • Journal of Multimedia Information System
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    • 제4권3호
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    • pp.115-122
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    • 2017
  • Over the years, there has been much research in blended learning. However, research regarding its use and evaluation is inconsistent, not following any specific evaluation method, and may not be applicable to local students. In this research, a case study was conducted to evaluate the environment based on three levels of Kirkpatrick's model. Methodological triangulation was the principle of data collection used in which multiple sources of evidence were triangulated to provide insights into this study. Instruments used include surveys, interviews, questionnaires and pre- and post-tests that are guided by Kirkpatrick's model. The results revealed that students were positive with the learning environment. Students enjoyed learning with multimedia and motivated to learn as well as engaged in the environment. The tests showed significant difference in their learning. Students also perceived that they have transferred their learning from face-to-face lecture into problem-based learning and learning outcome. This research contributes to the field by providing deeper insights into assessments in multimedia-based blended learning environment and empirical evidence on views, attitudes, learning and knowledge transfer of students in higher education.

주성분 분석을 이용한 블라인드 신호 분리 (B1ind Source Separation by PCA)

  • 이혜경;최승진;방승양
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2001년도 가을 학술발표논문집 Vol.28 No.2 (2)
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    • pp.304-306
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    • 2001
  • Various methods for blind source separation (BSS) are based on independent component analysis (ICA) which can be viewed as a nonlinear extension of principal component analysis (PCA). Most existing ICA methods require certain nonlinear functions, the shapes of which depend on the probability distributions of sources (which is not known in advance), whereas FCA is a linear learning method based on only second-order statistics. In this paper we show how BSS can be achieved by FCA, provided that sources are spatially uncorrelated but temporally correlated.

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한글 문자 인식에서의 오인식 문자 교정을 위한 단어 학습과 오류 형태에 관한 연구 (A Study on Word Learning and Error Type for Character Correction in Hangul Character Recognition)

  • 이병희;김태균
    • 한국정보처리학회논문지
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    • 제3권5호
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    • pp.1273-1280
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    • 1996
  • 본 논문에서는 문자 인식 과정을 거치고 난 후에 발생하게 되는 오인식된 문자들 을 언어적 지식을 이용하여 교정하는 문자 인식 후처리에 관하여 논한다. 문자 인식의 오인식 교정시스템의 경우 후보 단어가 많을 때 많은 후보 단어중에서 가장 적당한 단어를 후보 단어로 올려주기 위해서는 여러 가지 정보가 필요하다. 본 논문에서는 이러한 정보로 이용할 수 있는 것으로 단어들의 특성과, 문자 인식에 발생하는 오인식 형태, 단어 학습에 관하여 논한다. 이를 위한 실험으로 15 만여의 단어가 수록된 국어 사전을 이비력하고 초중고 국어교과서에 나타난 단어 들의 사용빈도를 조사하여 국어 사전에 등록된 단어 중에서 10.7%정도가 실제 초중고 국어교과서에 사용되고 있다는 것을 알 수 있었다. 또한 실제 문자 인식 시스템들을 가지고 여러 문서를 입력하고 인식하여 오인식이 자주 일어나는 글자들 의 형태를 분류하여 보았다. 그리고 한국어 처리 관련 서적이나 논문을 처리하고자 한국어에 관련된 책의 찾아보기에 나타난 단어 를 학습시켜 후보 단어들의 다른 인하여 정확한 단어를 예측하기 힘들던 문제를 해결 하고자 하였다.

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Underwater Acoustic Research Trends with Machine Learning: Passive SONAR Applications

  • Yang, Haesang;Lee, Keunhwa;Choo, Youngmin;Kim, Kookhyun
    • 한국해양공학회지
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    • 제34권3호
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    • pp.227-236
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    • 2020
  • Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

Students' Views of Science

  • Park, Hyun-Ju
    • 한국과학교육학회지
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    • 제24권1호
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    • pp.121-128
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    • 2004
  • This study was to investigate high students' conceptions of acids and bases, and their views on learning science. Multiple sources of data were collected over six months with a participation of sit tenth graders and their science teacher. The transcripts of interviews and other data were examined with an eye toward students' conceptions of acids and bases, and their views of learning science. Students' views of science are displayed the representative pattern. Each pattern is represented with an episode. Students' views of learning have been found to reflect the transmissive models of science educational practice. Students accept passive and difficult-to-modify views of the learner roles that they should play in the science classroom. Students identified science classes as conservative places, despite the introduction of science literacy as a goal of Korean science education since 1980. Behaviorism remains the major influence in their expectation, design, and practice in school science. Moreover, 'transmission' remains the persistent and dominant classroom cultural dynamic for both teaching and learning of science.

실내디자인 교육.실무에 있어서의 가상 교육 운영 전략 및 모형 연구 (Distance Learning for Interior Design: Strategies and Instructional Model)

  • 임영숙
    • 한국실내디자인학회논문집
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    • 제27호
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    • pp.12-19
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    • 2001
  • The purpose of this study is to develope instructional strategies and assessment model for distance learning in interior design education in Korea. Literature from various sources were examined to provide guidelines for instructional and technical strategies, communication system, and administrative process. Strategies and assessment model for transition to distance learning from goal setting to program evaluation were introduced. The results of this study indicated that distance learning in interior design education is optimized when applied in studio critique, portfolio production, and professional practice and with other traditional programs depending on the characteristics of the instructional materials. It is suggested for further studies that various distance learning programs based on instructional theories to be conducted and evaluated in different areas of interior design education for their maximum application as instructional tool.

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