• 실천공학교육논문지
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• 제15권1호
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• pp.183-192
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• 2023

본 연구는 학위연계형 일학습병행제에서 진행하는 오프라인 수업방식인 플립러닝의 성과에 대해서 분석한다. 직업능력향상의 일환으로 수행되는 일학습병행제의 훈련은 철저히 오프라인 방식을 견지해 왔으나, COVID-19와 맞물려 이전과는 달리 보다 적극적으로 온라인 방식을 혼용하는 방향으로 바뀌고 있다. 하지만 학위연계형의 운영은 대학의 학사시스템과 교육방식에 적용을 받으며 실질적으로 일반대학교육과 같은 형태이기 때문에 플립러닝과 같은 교육방식은 새로운 것이 아니다. 따라서 최근 학위연계형 일학습병행제에서 확대적용되고 있는 플립러닝의 교육성과와 보완점을 주말에만 수업이 진행되는 본 제도의 특성을 고려하여 분석해 보는 것이 필요하다. 설문에 기반한 통계분석결과 플립러닝의 성과가 일부 확인되었으며, 그 성과를 높이기 위해서 학습독려와 교수자-학생 간의 커뮤니케이션을 확대하는 구체적인 방안을 지속적으로 찾아가는 것이 필요하다.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• Computers and Concrete
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• 제32권3호
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• pp.263-286
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• 2023

Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.39-48
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• 2023

Breast cancer screening makes extensive utilization of mammography. Even so, there has been a lot of debate with regards to this application's starting age as well as screening interval. The deep learning technique of transfer learning is employed for transferring the knowledge learnt from the source tasks to the target tasks. For the resolution of real-world problems, deep neural networks have demonstrated superior performance in comparison with the standard machine learning algorithms. The architecture of the deep neural networks has to be defined by taking into account the problem domain knowledge. Normally, this technique will consume a lot of time as well as computational resources. This work evaluated the efficacy of the deep learning neural network like Visual Geometry Group Network (VGG Net) Residual Network (Res Net), as well as inception network for classifying the mammograms. This work proposed optimization of ResNet with Teaching Learning Based Optimization (TLBO) algorithm's in order to predict breast cancers by means of mammogram images. The proposed TLBO-ResNet, an optimized ResNet with faster convergence ability when compared with other evolutionary methods for mammogram classification.

• 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.

• 산업융합연구
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• 제17권3호
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• pp.1-8
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• 2019

본 연구는 스포츠센터 지도자들의 일터 학습(work place learning)과 관련하여 구성주의 관점 및 무형식 학습의 특성에 대해 이론적인 접근을 통한 고찰을 하였다. 이에 무형식 학습을 기반으로 하는 스포츠센터 지도자는 그 성장과정과 학습을 촉진 시키는 과정에서 경험과 실천적 측면에서의 일터 학습을 통한 전문성 신장이 될 수 있도록 하기 때문에 무형식 학습은 중요한 학습적 의미를 갖는다고 할 수 있다. 또한, 스포츠센터 지도 현장에서의 지도자는 일반적인 기업의 사무직 근로자에 비해 상대적으로 일터 학습에서 형식적인 학습의 기회가 부족하다고 할 수 있다. 따라서 무형식 학습의 유형 및 학습 향상에 대한 방안의 제시가 이루어져야 할 것이며 이러한 부분은 스포츠센터 지도자의 전문성 신장을 위한 중요한 요소로서 교육적 의미가 있다고 판단된다. 아울러 개인적, 환경적, 제도적, 조직적 측면에서 직장 내 학습 환경의 구축이 이루어진다면 스포츠센터 지도자들의 전문성 신장에 큰 도움이 될 것이라 생각된다.

• 한국빅데이터학회지
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• 제7권1호
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• pp.1-14
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• 2022

대부분의 블록체인이 사용하는 작업증명 합의 알고리즘은 채굴이라는 형태로 대규모의 컴퓨팅리소스 낭비를 초래하고 있다. 작업증명의 컴퓨팅리소스 낭비를 줄이기 위해 유용한 작업증명 합의 알고리즘이 연구 되었으나 여전히 블록 생성 시 리소스 낭비와 채굴의 중앙화 문제가 존재한다. 본 논문에서는 블록생성을 위한 상대적으로 비효율적인 연산 과정을 분산 인공지능 모델 학습으로 대체하여 블록생성 시 리소스 낭비문제를 해결하였다. 또한 학습 과정에 참여한 노드들에게 공평한 보상을 제공함으로써 컴퓨팅파워가 약한 노드의 참여 동기를 부여했고, 기존 중앙 집중 인공지능 학습 방식에 근사한 성능은 유지하였다. 제안된 방법론의 타당성을 보이기 위해 분산 인공지능 학습이 가능한 블록체인 네트워크를 구현하여 리소스 검증을 통한 보상 분배를 실험 하였고, 기존 중앙 학습 방식과 블록체인 분산 인공지능 학습 방식의 결과를 비교하였다. 또한 향후 연구로 블록체인 메인넷과 인공지능 모델 확장 시 발생 할 수 있는 문제점과 개발 방향성을 제시함으로서 논문을 마무리 하였다.

• 한국건설관리학회논문집
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• 제24권6호
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• pp.3-11
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• 2023

건설산업의 높은 재해율을 줄이고자, VR 기반 건설안전교육의 도입이 장려되고 있다. 그러나 학습자의 특성을 고려하지 않은 교육방식으로 인해, 학습자의 개인특성에 맞는 효과적인 교육을 수행하지 못하는 한계가 있다. 본 연구에서는, VR 기반 건설안전교육에서 학습성과에 영향을 미치는 개인특성을 분석하는 것으로 목표로 하였고, 이를 위해 머신러닝과 SHAP 기법을 활용하였다. SHAP 분석 결과, 연령이 학습성과에 가장 많은 영향을 미치는 것으로 나타났고, 경력이 가장 작은 영향을 미치는 것으로 나타났다. 또한, 연령은 학습성과와 음(-)의 상관관계를 보이고 있어, VR 기반 건설안전교육의 도입은 낮은 연령에게 더 효과적일 수 있는 것으로 나타났다. 반면, 학력, 자격, 경력은 양(+)의 상관관계를 보였다. 학력이 낮은 학습자에게 더욱 이해하기 쉬운 컨텐츠를 제공함으로써, 학습성과를 향상시킬 필요가 있다. 또한, 자격과 경력이 낮은 학습자의 특성은 학습성과에 영향을 거의 미치지 않으므로, 그 이외의 학습자 특성에 집중함으로써, 학습자 맞춤형 교육 컨텐츠를 제공할 수 있을 것으로 기대된다. 본 연구를 통해, 여러 개인특성이 학습성과에 서로 다른 영향을 미칠 수 있음을 확인했고, 이러한 결과를 활용함으로써, 건설근로자의 개인특성을 고려한 효과적인 안전교육의 기회를 제공할 수 있을 것으로 기대된다.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.359-366
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• 2013

Although many research efforts have been conducted to address the effect of crew members' work skills (e.g., technical and planning skills) on work performance (e.g., work duration and quality) in construction projects, the relationship between skill and performance has generated a great deal of controversy in the field of management (Inkpen and Crossan 1995). This controversy can lead to under- or over-estimations of the overall project schedule, and can make it difficult for project managers to implement appropriate managerial policies for enhancing project performance. To address this issue, the following aspects need to be considered: (a) work performances are determined not only by individual-level work skill but also by the group-level work skill affected by work team members, each member's role, and any working behavior pattern; (b) work planning has significant effects on to what extent work skill enhances performance; and (c) different types of activities in construction require different types of work, skill, and team composition. This research, therefore, develops a system dynamics (SD) model to analyze the effects of both individual-and group-level (i.e., multi-level) skill on performances by utilizing the advantages of SD in capturing a feedback process and state changes, especially in human factors (e.g., attitude, ability, and behavior). The model incorporates: (a) a multi-level skill evolution and relevant behavior development mechanism within a work group; (b) the interaction among work planning, a crew's skill-learning, skill manifestation, and performances; and (c) the different work characteristics of each activity. This model can be utilized to implement appropriate work planning (e.g., work scope and work schedule) and crew management policies (e.g., work team composition and decision of each worker's role) with an awareness of crew's skill and work performance. Understanding the different characteristics of each activity can also support project managers in applying strategic work planning and crew management for a corresponding activity, which may enhance each activity's performance, as well as the overall project performance.

• 한국초등과학교육학회지:초등과학교육
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• 제21권1호
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• pp.111-125
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• 2002

The aim of this study is to make it sure how pupils' science inquiry skills and attitude are influenced when they are taught by using the work-sheets for the differentiated learning according to their ability. In order to accomplish this aim, two classes of the fourth grade in the elementary school were distinguished into two groups: one was the experimental class and the other, the comparative class. The experimental class was given 52 hours of science lessons using the above sheets, and the comparative class, the general method of teaching. In order to compare their scientific interest and learning ability of the two groups each other, pupils were tested the standardized achievement in advance. The two groups were also given "ex post facto test" to measure the variation of their inquiry skills and attitude after the lessons. In addition, the experimental class was tested to measure their learning attitude after they are teamed the science with the sheets. The results of this study are as follows: 1. According to the percentile statistics of the science inquiry skills test between the two groups, the work-sheets for the differentiated teaming helped pupils develope their inquiry skills remarkably. 2. The work-sheets did not lead to significant difference between the learning ability of boys and girls. 3. The science lesson using the work-sheets showed positive influences in increasing pupils' scientific attitude. 4. About 77.2 percent of pupils accepted the excellent records of the evaluation in the science lesson using the sheets. It can be, therefore, concluded that the science lesson using the work-sheets for differentiated teaming is one of effective science lessons to increasing pupils' science inquiry skills, compared with the general teaching method.