• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.185-200
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• 2024

This study explored the changes in the elementary science teaching expertise of teachers who participated in an in-school professional learning community for elementary science instructional research. Six elementary school teachers from grades 4, 5, and 6 at an 18-class S elementary school in a medium-sized city in Chungcheongbuk-do conducted collaborative instructional research on elementary science lessons as part of an in-school professional learning community, which was held 26 times over 7 months in 2020. During the professional learning community, video and audio recordings of the activities, research lessons, course materials, and professional learning community reflection activities were collected for analysis. The collected data were analyzed using qualitative research methods; data processing, reading, note-taking, description, classification, interpretation, reporting, and visualization; and the instructional professionalism elements were extracted based on the instructional professionalism framework. In the early professional learning community activity stages, the participating teachers first discussed their teaching perspectives, their experiences, and their goals for teaching science, which resulted in a selection of research questions. The teachers then collaboratively designed and implemented research lessons for each grade level, after which lesson reflections were conducted. The teachers' abilities to engage in qualitative reflection on the research questions improved after each reflection iteration. It was found that this professional learning community collaborative lesson study experience positively contributed to teaching expertise development. Based on the study findings, the implications for using professional learning communities to improve elementary teachers' science teaching expertise are given.

• Information Systems Review
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• v.23 no.3
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• pp.127-158
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• 2021

Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

• Information Systems Review
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• v.23 no.3
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• pp.25-50
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• 2021

Though there have been a lot of studies about online product review, the effects of highlighted reviewhave not been examined enough. Highlighted review is a type of review that the platform designer changes its size or position in order to highlight without any sponsorship or incentive. The main subject of this study is about how highlighted review type affects consumer's perception and behavior in online information acquisition. We collected data from 171 subjects to test hypotheses. Using three different types of screen captures, we compared three groups - general review group, positive highlighted review only group, and both positive and negative highlighted review group. As a result, disclosing both of positiveand negative highlighted review was perceived more useful than disclosing only positive highlighted review. However, correlation between highlighted review type and review skepticism was not statistically significant. The impacts of review usefulness and skepticism on platform credibility were statistically significant, and the correlation between platform credibility and usage intention was also significant. All of results is almost similar across two product types, search goods and experiential goods. This research provides practical implications to online shopping platform designers when they design review systems to make people use their platforms.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.1-9
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• 2024

This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.

• Journal of The Korean Association For Science Education
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• v.27 no.7
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• pp.547-558
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• 2007

The purpose of this study is to compare inquiry activities in science textbooks' physics contents for Korean secondary schools with those of Singapore in order to provide a reference for further improvement of inquiry activities in Korean science textbooks. We analyzed inquiry activities using the framework of Millar et al.(1998) and Chinn & Malhotra (2002). The results of this study are as follows: There are differences between Korean and Singaporean inquiry activities in the area of 'learning objectives', 'students' thinking activities' and 'degree of openness'. In the area of 'learning objectives', the Korean textbooks have more activities associated with the learning of science content than those in Singaporean, whereas the Singaporean textbooks have more activities associated with the processes of scientific inquiry than in Korean textbooks. In the area of 'students' thinking activities', the Singaporean textbooks have activities like 'test a prediction', which Korean textbooks lack. The 'degree of openness' is higher in Singaporean textbooks than in Korean textbooks. And some differences in the area of 'authentic scientific inquiry' between Korean and Singaporean textbooks were also found. While the Korean textbooks do not have any activities associated with 'generating research questions', the Singaporean ones feature such activities. In the area of 'designing studies', the Singaporean textbooks have activities corresponding to 'selecting variables' and 'controlling variables', while the Korean ones never have such activities. The results of this study imply that it is necessary to balance inquiry activities in the area of 'learning objectives', 'students' thinking activities' and 'degree of openness', and to present activities close to authentic scientific inquiry in inquiry activities in textbooks.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.1
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• pp.303-328
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• 2024

In this study, we designed and verified a research model in order to determine whether ESG management for public libraries affects the perception of libraries, user satisfaction, and the intention to revisit. A survey was conducted among the users of six public libraries in the Gyeonggi region and 25 libraries in Seoul, and 247 valid responses from the survey were analyzed. The analysis revealed that the environment and society factors of ESG management had a positive effect on the perception of libraries and user satisfaction. It also showed that the libraries' perception had a positive impact on user satisfaction and the intention to revisit, and user satisfaction showed a positive correlation for the intention to revisit. From the analysis, we can infer that the effects of ESG management were reflected in everyday life via public libraries as ESG management of the public libraries influenced the perception of libraries, user satisfaction, and the intention to revisit. We confirmed that users showed the intention to revisit if the library provides positive and sincere satisfaction through ESG management, due to public libraries having ethical and moral significance to users. We have also put forward practical marketing strategies and identified areas for enhancement that can prove beneficial to public libraries.

• Knowledge Management Research
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• v.24 no.4
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• pp.87-102
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• 2023

Awe is recognized as an emotion linked to enhancing openness to new experiences and broadening one's cognitive perspective through the acquisition of new knowledge. This research aimed to investigate awe's impact on consumer behavior in advertising, using a 2 (emotion: awe/control) × 2 (product type: innovative/non-innovative) experimental design with 118 undergraduate students in Seoul, Korea. Findings revealed that awe-inducing advertising significantly increases product preference and positive technology readiness, particularly for innovative products compared to non-innovative ones or when awe is not elicited. The analysis of moderated mediation showed that positive technology readiness plays a mediating role in the relationship between awe induction and product preference. Notably, in the case of innovative products, awe-inducing advertising heightens positive technology readiness, subsequently increasing consumer preference for these products. These results reinforce existing literature on awe's positive effects, demonstrating its role in augmenting consumers' favorable attitudes toward innovative products. The study offers valuable insights for marketing strategies of companies promoting innovative products or services, highlighting the effectiveness of awe-inducing emotional appeals in shaping consumer attitudes towards innovation.

• Convergence Security Journal
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• v.24 no.1
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• pp.51-57
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• 2024

Although industrial control systems (ICSs) recently keep evolving with the introduction of Industrial IoT converging information technology (IT) and operational technology (OT), it also leads to a variety of threats and vulnerabilities, which was not experienced in the past ICS with no connection to the external network. Since various control command messages are sent to field devices of the ICS for the purpose of monitoring and controlling the operational processes, it is required to guarantee the message integrity as well as control center authentication. In case of the conventional message integrity codes and signature schemes based on symmetric keys and public keys, respectively, they are not suitable considering the asymmetry between the control center and field devices. Especially, compromised node attacks can be mounted against the symmetric-key-based schemes. In this paper, we propose message authentication scheme based on double hash chains constructed from cryptographic hash function without introducing other primitives, and then propose extension scheme using Merkle tree for multiple uses of the double hash chains. It is shown that the proposed scheme is much more efficient in computational complexity than other conventional schemes.

• Convergence Security Journal
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• v.24 no.2
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• pp.89-104
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• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.137-142
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• 2024

Recently, deep learning technology has become those methods as de facto standards in the area of medical data representation. But, deep learning inherently requires a large amount of training data, which poses a challenge for its direct application in the medical field where acquiring large-scale data is not straightforward. Additionally, brain signal modalities also suffer from these problems owing to the high variability. Research has focused on designing deep neural network structures capable of effectively extracting spectro-spatio-temporal characteristics of brain signals, or employing self-supervised learning methods to pre-learn the neurophysiological features of brain signals. This paper analyzes methodologies used to handle small-scale data in emerging fields such as brain-computer interfaces and brain signal-based state prediction, presenting future directions for these technologies. At first, this paper examines deep neural network structures for representing brain signals, then analyzes self-supervised learning methodologies aimed at efficiently learning the characteristics of brain signals. Finally, the paper discusses key insights and future directions for deep learning-based brain signal analysis.