• Journal of The Korean Association For Science Education
• /
• v.27 no.7
• /
• pp.623-630
• /
• 2007

The assessment affects the learning motivation of students. If we know what factors in assessment affect motivation, we could find the method for stimulating the motivation. In this study, we used two kinds of method, the recollection paper and the questionnaire. 54 undergraduates of a university in Seoul made the recollection paper about the science learning before, and 63 undergraduates also answered the question for the effect of factors in assessment on the science learning motivation. In result, the factors in assessment that affect the science learning motivation of high achieving students are the achievement, difficulty, validity, and preparation for science fair. This study suggests that difficulty and validity of assessments remarkably affects the science motivation and the science fair is more affective to the science motivation than regular examination in school. Therefore we suggest two methods for the science motivation of high achieving students. The first method is to make questions that can assess scientific thinking faculty and investigating faculty without pre-learning and memorizing. The second method is to encourage various activities in science to increase the number of chance for participating in them.

• Journal of The Korean Association For Science Education
• /
• v.28 no.6
• /
• pp.546-564
• /
• 2008

The purpose of this study was to examine the types and characteristics of the knowledge constructed by pre-service secondary science teachers. Data included 26 student-teachers' narratives regarding their experiences in teaching high school students who were enrolled in extra-curricular science classes. It was revealed that the pre-service teachers awoke to the importance of subject matter knowledge, and learned it themselves in the situation of their own teaching. Especially their concern about science content knowledge was strongly associated with the matter of didactic transposition of the knowledge. The result also showed that the pre-service teachers constructed knowledge about the relationship with students as well as pedagogical knowledge to help students learn, and that they newly realized the nature of science in the context of teaching science. In addition, the teaching experiences allowed for the student-teachers to develop knowledge of oneself as a teacher and knowledge about science education in schools. It was believed that the knowledge constructed personally by the pre-service teachers from their teaching experiences could be a platform for the development of teacher expertise. Implications of the present study for science teacher education and relevant research were discussed.

• Journal of Life Science
• /
• v.34 no.6
• /
• pp.434-441
• /
• 2024

Mammary gland tumors are the most common tumors detected in non-spayed female dogs and pose a significant clinical challenge. Due to the strong similarity between canine mammary tumors (CMT) and human breast cancer (HBC), biomarkers identified in HBC can also be detected in CMT. These biomarkers have been shown to offer valuable insights into early diagnosis, prognosis, and treatment strategies. The purpose of this article is to provide a concise overview of CMT biomarkers based on the current literature. Traditional treatments for CMT in dogs typically begin with surgery, followed by chemotherapy, radiotherapy, or hormonal therapy. However, these treatments alone are not always fully effective. A diagnostic biomarker can detect the presence of a disease or the characteristics of a disease and classify an individual's status. Prognostic biomarkers focus on predicting the expected progression, recurrence, or survival of the disease in patients. By utilizing advances in understanding the mechanism of canine-specific mammary gland tumors, the estimation of biomarkers offers hope for improved outcomes in cancer patients. Novel technologies, such as single-cell RNA sequencing analysis, could provide a valuable resource for deciphering intra- and inter-tumoral heterogeneity. This review paper explores current research on CMT biomarkers and suggests directions for their development.

• Journal of The Korean Association For Science Education
• /
• v.26 no.1
• /
• pp.58-67
• /
• 2006

Student understanding of the nature of science is necessary not only because it is helpful for solving everyday problems with growing science literacy, but also because it influences students' science learning. Therefore, it was necessary to investigate student views on the nature of science under the 7th national curriculum and compare with those before the 7th national curriculum in order to probe the elements which contribute to changes in student views on the nature of science. A significant number of differences were found between subdimensions of views on the nature of science through the comparison. High school students under the 7th national curriculum had more relativistic, instrumental, and deductive but less process-oriented views than high school students before the 7th national curriculum. The differences between mean values which showed high school student views on the nature of science under and before the 7th national curriculum were significant, except for the subdimension of instrumentanlism/realism. In particular, high school students under the 7th national curriculum possessed a contextual view, whereas those before the 7th national curriculum possessed a decontextual view. Although other factors might be the cause for differences found in this study, we argued by discussion that differences among textbook contents seemed to be the major factor.

• Membrane Journal
• /
• v.34 no.2
• /
• pp.87-95
• /
• 2024

Recent studies explore a wide array of desalination and water treatment methods, encompassing membrane processes such as reverse osmosis (RO), nanofiltration (NF), and electrodialysis (ED) to advanced capacitive deionization (CDI) and its membrane variant (MCDI). Comparative analyses reveal ED's cost-effectiveness in low-salinity scenarios, while hybrid systems (NF-MCDI, RO-NF-MCDI) show improved salt removal and energy efficiency. Novel ion separation methods (NF-CDI, NF-FCDI) offer enhanced efficacy and energy savings. These studies also highlight the efficiency of these methods in treating complex wastewater specific to various industries. Environmental impact assessments emphasize the need for sustainability in system selection. Additionally, the integration of microfabricated sensors into membranes allows real-time monitoring, advancing technology development. These studies underscore the variety and promise of emerging desalination and water treatment technologies. They provide valuable insights for enhancing efficiency, minimizing energy usage, tackling industry-specific issues, and innovating to surpass conventional method limitations. The future of sustainable water treatment appears bright, with continual advancements focused on improving efficiency, minimizing environmental impact, and ensuring adaptability across diverse applications.

• Information Systems Review
• /
• v.21 no.4
• /
• pp.69-97
• /
• 2019

Knowledge service firms are able to have higher 'Organizational Performance (OP)' by improving efficiency in management processes on customer problem solving. This study explores the role of inefficiency that has been overlooked up to now compared to the management process efficiency. We also suggest in this study 'Hierarchical Culture (HC)' and 'IT Relatedness (IR)' as the factors influencing the inefficiency of management processes, and propose the moderating effect of 'Task Difficulty (TD)' on the relationship between independent factors and 'Inefficiency of Business Process(IP)'. The results of analysis show that 'HC' has a positive effect on 'IP', and 'IR' has a negative effect on 'IP'. 'TD' was significant moderator of between independent variables and 'IP'. 'IP' was shown to play a full mediating role between independent factors and 'OP'. In conclusion, knowledge service firms are desired to reduce 'HC' and enhance 'IR' by minimizing unnecessary formal procedures, securing flexibility in decision making through appropriate empowerment, creating a smooth flow of knowledge, and enhancing the level of IT resource management and utilization. In addition, in order to effectively reduce 'IP', it is required that a company with a high degree of 'TD' to more reduce a 'HC' and a company with a low degree of 'TD' to more enhance a 'IR'.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.3
• /
• pp.199-216
• /
• 2024

This research examines the factors influencing consumer purchase intentions in e-commerce live streaming, set against the backdrop of the internet celebrity economy. The investigation serves as a pivotal inquiry into the dynamics of this economy, striving to uncover the extent of internet celebrities' influence, particularly in terms of their economic impact. Employing the Emotional Behavioral Cognitive (ABC) attitude theory and the Stimulus Organism Response (S-O-R) theory as foundational frameworks, this study scrutinizes internet celebrity live streaming sales. It incorporates direct observations and leverages existing scholarly work to devise a tailored measurement scale and questionnaire. From this, a research model and hypotheses are developed, leading to the establishment of an empirical model. This empirical model is instrumental in statistically analyzing how e-commerce live streaming, within the internet celebrity economy context, shapes consumer purchase intentions. By integrating theoretical insights and empirical findings, the research elucidates the strategic dimensions and consumer behavior aspects in digital commerce. It enhances understanding of how internet celebrity influence intersects with consumer purchasing processes. Overall, this study contributes to the academic discourse on digital marketing and consumer behavior, providing a nuanced perspective on the mechanisms through which internet celebrities affect e-commerce. It offers valuable implications for marketers, strategists, and policymakers aiming to navigate the complex landscape of the internet celebrity economy.

• Journal of Service Research and Studies
• /
• v.14 no.1
• /
• pp.77-90
• /
• 2024

This research aims to investigate methods of leveraging generative artificial intelligence in service sectors where consumer sentiment and experience are paramount, focusing on minimizing hallucination phenomena during usage and developing strategic services tailored to consumer sentiment and experiences. To this end, the study examined both mechanical approaches and user-generated prompts, experimenting with factors such as business item definition, provision of persona characteristics, examples and context-specific imperative verbs, and the specification of output formats and tone concepts. The research explores how generative AI can contribute to enhancing the accuracy of personalized content and user satisfaction. Moreover, these approaches play a crucial role in addressing issues related to hallucination phenomena that may arise when applying generative AI in real services, contributing to consumer service innovation through generative AI. The findings demonstrate the significant role generative AI can play in richly interpreting consumer sentiment and experiences, broadening the potential for application across various industry sectors and suggesting new directions for consumer sentiment and experience strategies beyond technological advancements. However, as this research is based on the relatively novel field of generative AI technology, there are many areas where it falls short. Future studies need to explore the generalizability of research factors and the conditional effects in more diverse industrial settings. Additionally, with the rapid advancement of AI technology, continuous research into new forms of hallucination symptoms and the development of new strategies to address them will be necessary.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.3
• /
• pp.189-198
• /
• 2024

In this papery, we study the diverse dynamics of human personality formation, examining the harmonious interplay between innate traits and the surrounding environment. Our focus is on Charles Dickens' renowned work, "Oliver Twist," where Dickens underscores the critical role of both the environment and innate traits in shaping personalities. We explore Dickens' unique perspective, emphasizing the deep insights gained through his work. The paper outlines the research background, stressing the topic's importance and explaining the necessity of addressing this crucial issue. The significance of choosing "Oliver Twist" as the research subject is highlighted, underscoring its special relevance. The main content thoroughly investigates how innate traits and the environment profoundly influence individual personality formation. Contrary to common assumptions, Dickens' perspective unequivocally highlights the greater importance of innate traits. Our analysis supports this claim, examining key scenes and characters in "Oliver Twist." By exploring his distinctive viewpoint on the environment's impact on personality formation, we enhance understanding of theinteraction between innate traits and the environment. Focused on "Oliver Twist," our goal is to provide contemporary readers with profound insights into how personal characteristics evolve and are shaped by environmental factors, utilizing Dickens' masterpiece as a central reference point.

• Journal of Internet Computing and Services
• /
• v.25 no.4
• /
• pp.47-56
• /
• 2024

This paper proposes a method for fine-tuning BERT-based natural language processing models to perform sentiment analysis on Korean review data. By varying the input sequence length during this process and comparing the performance, we aim to explore the optimal performance according to the input sequence length. For this purpose, text review data collected from the clothing shopping platform M was utilized. Through web scraping, review data was collected. During the data preprocessing stage, positive and negative satisfaction scores were recalibrated to improve the accuracy of the analysis. Specifically, the GPT-4 API was used to reset the labels to reflect the actual sentiment of the review texts, and data imbalance issues were addressed by adjusting the data to 6:4 ratio. The reviews on the clothing shopping platform averaged about 12 tokens in length, and to provide the optimal model suitable for this, five BERT-based pre-trained models were used in the modeling stage, focusing on input sequence length and memory usage for performance comparison. The experimental results indicated that an input sequence length of 64 generally exhibited the most appropriate performance and memory usage. In particular, the KcELECTRA model showed optimal performance and memory usage at an input sequence length of 64, achieving higher than 92% accuracy and reliability in sentiment analysis of Korean review data. Furthermore, by utilizing BERTopic, we provide a Korean review sentiment analysis process that classifies new incoming review data by category and extracts sentiment scores for each category using the final constructed model.