• Title/Summary/Keyword: Emotional learning

검색결과 582건 처리시간 0.03초

The Effect of Game-Based Student Response System(GSRS) on Nursing Education : Focusing on Learning Engagement (간호교육에서의 게임기반 학생응답시스템(GSRS) 적용 효과: 학습몰입을 중심으로)

  • Hwang, Ji-Won;Kim, Jung-Ae;Hwang, Seul-Gi
    • Journal of Convergence for Information Technology
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    • 제11권1호
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    • pp.156-166
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    • 2021
  • The purpose of this study is to find out the impact of classes using a game-based student response system on learning engagement. It is an experimental study that compares learning engagement in classes (experimental groups) and lecture-style classes (comparative groups) that utilize GSRS in nursing education. A total of 211 nursing students participated from October 2019 to December 2019. The differences in learning engagement between the two groups were analyzed as t-test and correlation analysis was conducted on related factors. There was a difference between the comparison group and the experimental group in overall learning engagement(p=.013) and emotional engagement(p=.002). This is meaningful in that it has verified the learning engagement effect of the GSRS for the first time in Korea.

Generative AI parameter tuning for online self-directed learning

  • Jin-Young Jun;Youn-A Min
    • Journal of the Korea Society of Computer and Information
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    • 제29권4호
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    • pp.31-38
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    • 2024
  • This study proposes hyper-parameter settings for developing a generative AI-based learning support tool to facilitate programming education in online distance learning. We implemented an experimental tool that can set research hyper-parameters according to three different learning contexts, and evaluated the quality of responses from the generative AI using the tool. The experiment with the default hyper-parameter settings of the generative AI was used as the control group, and the experiment with the research hyper-parameters was used as the experimental group. The experiment results showed no significant difference between the two groups in the "Learning Support" context. However, in other two contexts ("Code Generation" and "Comment Generation"), it showed the average evaluation scores of the experimental group were found to be 11.6% points and 23% points higher than those of the control group respectively. Lastly, this study also observed that when the expected influence of response on learning motivation was presented in the 'system content', responses containing emotional support considering learning emotions were generated.

A Successful Old Age and Learning : Focusing on the Article an Encore My Life in Chosun IIbo (신문을 통해 본 '은퇴' 이후 성공적인 노년기와 학습 : 『조선일보』의 《앙코르 내 인생》 기사를 중심으로)

  • Park, Sin-Young;Oh, Kyoung-Hee
    • Journal of Fisheries and Marine Sciences Education
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    • 제27권1호
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    • pp.18-28
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    • 2015
  • This study aims to understand the meaning that learning of the old age has, through old age learners who augustly live after retirement-life so called successful silver years. Qualitative research methods is used for analyzing the contents of articles about 15 old age learners and the results are follows below. First, the retirement has dual meaning for the old learners. One is they experienced psychological and emotional insecurity after retirement and the other is it is a turning point for them to realize their longtime dream. Second, the old age learners showed enthusiasm about learning and they voluntarily found the way of success in their silver years. Finally, the old age learners working in new career with provocative and enthusiastic attitude work as a role model of successful old age life and show how they progress. This study argued that we need to consider the old as active agents and the old age as the time when productive and continuous learning can be done. In addition, this study strongly insisted that we need to realize the importance of 'education by the elderly' and social and other relevant conditions are needed to be established immediately.

A Study on the Learnablity of Routing Algorithm in Elementary School Computer Education (초등학교 컴퓨터교육에서 라우팅알고리즘 학습가능성에 관한 연구)

  • Park, Yeon;Kim, Ji-Na;Han, Byoung-Rae
    • Journal of The Korean Association of Information Education
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    • 제11권3호
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    • pp.267-279
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    • 2007
  • The purpose of this study is to design and practice teaching and learning method for routing algorithm among computer science principle which is difficult to be taught to elementary school students and understood by students. And we find out whether elementary school students can understand those learning contents. Intellectual area was assessed through equivalent test paper before and after the test and emotional area was assessed through students' impressions after class. The test showed that routing algorithm could be taught to children. Therefore, this study presents the learnability of routing algorithm as a learning element of elementary school computer education.

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Analysis of Social Interaction Process in Science Teachers' Learning Community (과학교사 학습공동체에서 나타나는 사회적 상호작용 과정의 분석)

  • Cha, Gahyun;Jang, Shinho
    • Journal of Korean Elementary Science Education
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    • 제33권4호
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    • pp.784-794
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    • 2014
  • In this study, we operated science teacher learning community to enhance professionality of elementary science teachers. 8 participants with various background, which include their science content knowledge, teaching experience and beliefs about teaching, were involved in this study. Bales(1950)'s social interaction process framework was mainly used to understand the members' interaction, focusing particularly on process aspects not on contents aspects. The data analysis shows that the members in the science teacher learning community tried their best to maintain the positive reaction to other members in most occasions in the community meetings. On the other hand, there were also negative reaction process due to their different ideas and views, causing their emotional conflicts in some social relations and dialogical situations. Nevertheless, the results also imply that the dual reaction processes, which are positive and negative processes, are equally important to facilitate science teachers' professional knowledge and experience. The educational meanings are discussed in the aspects of science teacher education.

Use of Innovation and Information Technologies In Music Lessons

  • Potapchuk, Tetiana;Fabryka-Protska, Olga;Gunder, Liubov;Dutchak, Violetta;Osypenko, Yaroslav;Fomin, Kateryna;Shvets, Nataliia
    • International Journal of Computer Science & Network Security
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    • 제21권12호
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    • pp.300-308
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    • 2021
  • The processes of informatization of the modern educational space are inextricably linked with the active introduction of innovative information technologies, which diversify the forms of education and upbringing. The use of these technologies in education due to their specific properties significantly enhances the clarity of learning, emotional impact on students, helps to deepen interdisciplinary links, intensifies students' work, and improves the organization of educational activities. Innovative information technologies offer new opportunities for the use of text, audio, graphic, and video information in lessons, enriching the methodological possibilities of the lesson. Today, the use of these technologies is becoming an integral part of the study of any subject. Using multimedia presentations, publications, and websites created by students in the learning process, they can develop learning skills. According to researchers, there are many multimedia programs for working with a computer in a music lesson, namely: a music player, a program for singing karaoke, a music constructor, music encyclopedias, and training programs. The introduction of innovative information technologies in the system of music education allows expanding learning opportunities.

Language Matters: A Systemic Functional Linguistics-Enhanced Machine Learning Framework for Cyberbullying Detection

  • Raghad Altowairgi;Ala Eshamwi;Lobna Hsairi
    • International Journal of Computer Science & Network Security
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    • 제23권9호
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    • pp.192-198
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    • 2023
  • Cyberbullying is a growing problem among adolescents and can have serious psychological and emotional consequences for the victims. In recent years, machine learning techniques have emerged as promising approach for detecting instances of cyberbullying in online communication. This research paper focuses on developing a machine learning models that are able to detect cyberbullying including support vector machines, naïve bayes, and random forests. The study uses a dataset of real-world examples of cyberbullying collected from Twitter and extracts features that represents the ideational metafunction, then evaluates the performance of each algorithm before and after considering the theory of systemic functional linguistics in terms of precision, recall, and F1-score. The result indicates that all three algorithms are effective at detecting cyberbullying with 92% for naïve bayes and an accuracy of 93% for both SVM and random forests. However, the study also highlights the challenges of accurately detecting cyberbullying, particularly given the nuanced and context-dependent nature of online communication. This paper concludes by discussing the implications of these findings for future research and the development of practical tool for cyberbullying prevention and intervention.

Emotion Recognition in Arabic Speech from Saudi Dialect Corpus Using Machine Learning and Deep Learning Algorithms

  • Hanaa Alamri;Hanan S. Alshanbari
    • International Journal of Computer Science & Network Security
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    • 제23권8호
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    • pp.9-16
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    • 2023
  • Speech can actively elicit feelings and attitudes by using words. It is important for researchers to identify the emotional content contained in speech signals as well as the sort of emotion that resulted from the speech that was made. In this study, we studied the emotion recognition system using a database in Arabic, especially in the Saudi dialect, the database is from a YouTube channel called Telfaz11, The four emotions that were examined were anger, happiness, sadness, and neutral. In our experiments, we extracted features from audio signals, such as Mel Frequency Cepstral Coefficient (MFCC) and Zero-Crossing Rate (ZCR), then we classified emotions using many classification algorithms such as machine learning algorithms (Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)) and deep learning algorithms such as (Convolution Neural Network (CNN) and Long Short-Term Memory (LSTM)). Our Experiments showed that the MFCC feature extraction method and CNN model obtained the best accuracy result with 95%, proving the effectiveness of this classification system in recognizing Arabic spoken emotions.

How Long Will Your Videos Remain Popular? Empirical Study with Deep Learning and Survival Analysis

  • Min Gyeong Choi;Jae Hong Park
    • Asia pacific journal of information systems
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    • 제33권2호
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    • pp.282-297
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    • 2023
  • One of the emerging trends in the marketing field is digital video marketing. Online videos offer rich content typically containing more information than any other type of content (e.g., audible or textual content). Accordingly, previous researchers have examined factors influencing videos' popularity. However, few studies have examined what causes a video to remain popular. Some videos achieve continuous, ongoing popularity, while others fade out quickly. For practitioners, videos at the recommendation slots may serve as strong communication channels, as many potential consumers are exposed to such videos. So,this study will provide practitioners important advice regarding how to choose videos that will survive as long-lasting favorites, allowing them to advertise in a cost-effective manner. Using deep learning techniques, this study extracts text from videos and measured the videos' tones, including factual and emotional tones. Additionally, we measure the aesthetic score by analyzing the thumbnail images in the data. We then empirically show that the cognitive features of a video, such as the tone of a message and the aesthetic assessment of a thumbnail image, play an important role in determining videos' long-term popularity. We believe that this is the first study of its kind to examine new factors that aid in ensuring a video remains popular using both deep learning and econometric methodologies.

The Effect of Learner's Characteristics on the Student's Achievement in ICT Teaching-Learning Environment (정보통신기술(ICT)을 활용한 교수-학습에서 학습자 특성이 학업성취도에 미치는 영향)

  • Kim, Jung-Gyeom
    • The Journal of Korean Association of Computer Education
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    • 제7권2호
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    • pp.47-56
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    • 2004
  • The purpose of this study was to investigate the effect of learner's characteristics on the student's achievement in Information Communication Technology (ICT) teaching-learning environment. The subjects of this study were a total of 140 8th students in middle school in Taejeon province. The methods of teaching were the ICT teaching-learning, Academic achievement test. the learning style inventory. self-concept test and cognitive style test were used as the instruments to determine the effect. Such statistical analyses as the pearson co-relation, multi regression and t-test through SPSS WIN version 11.0 were used to determine the relationship between learner's characteristics and student's achievement. The results of this study were as follows: first, learner's emotional and social factor of learning style influenced positively the student's academic achievement in ICT teaching-learning environment. Second. learner's academic factor of self-concept had an positive influence on the student's academic achievement in ICT teaching-learning environment. Third, there were differences of student's academic achievements according to the student's cognitive style in ICT teaching-learning environment.

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