• Journal of the International Relations & Interdisciplinary Education
• /
• v.4 no.1
• /
• pp.85-111
• /
• 2024

Since the release of the 2000 PISA results, Finland's education has consistently been regarded as a competitor or benchmark for South Korea's educational system. However, recent indicators of division, opposition, and discontent within our educational sphere suggest a considerable departure from Finland's ethos of happiness in education. Against this backdrop, this study aims to analyze the trends in Finnish education-related research appearing in Korean academic journals. Utilizing network text analysis, we examined 160 papers indexed in RISS with titles containing "Finland" and "education". Key findings are as follows. Firstly, research on Finnish education has been steadily increasing, albeit showing recent signs of decline. Secondly, the majority of research topics were micro-level, with literature review-based methodologies predominating. Thirdly, a minority of researchers accounted for one-third of the total research output. Fourthly, countries compared with Finland predominantly included neoliberal states such as Japan, the United States, the United Kingdom, Australia, and Singapore. Fifthly, research themes and subjects primarily focused on primary and secondary education, particularly in domains such as mathematics and science, influenced by PISA. Future research on Finnish education should transcend localized and fragmented areas of inquiry, undertaking comprehensive investigations into the processes and history of Finland's happiness-oriented education. Such endeavors are essential for deriving insights crucial for our learning. Particularly, consideration should be given to moving beyond literature-based methodologies, fostering international collaborative discussions facilitated online, and linking the Finnish education community with educators, parents, students, local councils, and governmental stakeholders to collectively discuss and research.

• The Korean Journal of Elementary Counseling
• /
• v.8 no.1
• /
• pp.33-50
• /
• 2009

The purpose of this study was to develop a PBL-based career education program and to examine its effectiveness on school children's career maturity. It's specifically meant to prepare a career education program to assist students to get an accurate grip on their aptitude, interest and personality and explore various sorts of occupations in the course of solving authentic and contextual career-related problems. After children's developmental characteristics and needs were analyzed, task analysis was implemented, and the objectives were defined. And then the core of the program, PBL problems were developed, and the validity of the problems were verified Evaluation plans and tools were prepared to assess children's problem-solving process and presentation, and an online learning space was designed. The program that consisted of 10-minute 21 sessions was provided to fifth-grade elementary schoolers for eight weeks. The findings of the study were as follows: The experimental group that participated in the PBL-based career education program showed a more significant improvement than the control group that didn't in career attitude and three career attitude subfactors involving planness, disposition and compromise. And the former made a more significant progress than the latter in career ability and its subfactors including vocational comprehension, self-understanding and decision-making skills as well. As a result of making a content analysis to make up for the survey, the students reported that they were able to get an objective understanding of themselves and acquire diverse and profound knowledge on work and the business world in the middle of solving the given PBL problems related to different areas in group and giving a presentation. In conclusion, a PBL based career education program developed by this researcher encouraged the students to have an objective self-understanding, to have a dynamic interactive discussion with their group members. Therefore the program had a positive impact on boosting the career attitude and career ability of the elementary schoolers. The findings suggested that in the field of elementary career education, autonomous learning attitude and subjecthood are the crucial factors to stimulate school children to explore and create their own future.

• Journal of the International Relations & Interdisciplinary Education
• /
• v.2 no.1
• /
• pp.57-82
• /
• 2022

This study aims to investigate and analyze the perception of communication capability which is one of the sub-competencies of NCS vocational substructure basic competence, and then seek the direction of prospective courses. To do this, the researcher conducts a non-face-to-face survey by creating five questions under the following five categories: The importance and necessity of communicative competence, students and educators of communicative competence classes, contents and methods of curriculum and teaching and learning, communicative competence and writing skills and operation of extracurricular programs. This researcher has been teaching basic education even before the communication skills curriculum was created in college, now, in a situation where communication skills have become selective education, it is intended to grasp the perception of college students about communication skills for first graders. This study attempted to analyze the survey area in more depth through group FGI after conducting an online survey by dividing it into several items. As a result, students felt that communication skills became motktkre important through COVID-19. Among the bottom five communication skills, speaking skills were found to be the most important, reading ability was recognized as the least important. On the other hand, there was a strong hope to know about the level of communication ability, type of communication, and method of communication about oneself. In addition, they recognized that communication skills should be learned in their first year of college, and hoped to be operated at all times as a non-disciplinary program. In particular, in the bottom five areas of communication skills, the expectations and actual hopes for speaking skills were the highest compared to the rest, and in terms of teaching and learning methods, they wanted to improve their skills through feedback and practice rather than theory. These research results have great implications for setting the direction of operation of classes, such as the content and method of classes in communication skills, in the future.

• Education of Primary School Mathematics
• /
• v.27 no.2
• /
• pp.111-137
• /
• 2024

The purpose of this study is to identify the expected difficulties and necessary support when applying the 2022 revised mathematics curriculum to elementary schools, and to support the establishment of the field. To this end, we explored the major changes in the 2022 revised mathematics curriculum, and based on this, we conducted a survey of elementary school teachers to identify the expected difficulties and necessary support when applying it in the field. In particular, when analyzing the results, we also examined whether there were any differences in the expected difficulties and necessary support depending on the size of the school where it is located and the teaching experience of the teacher. The research results are as follows. First, the proportion of teachers who expect difficulties in applying the 2022 revised mathematics curriculum was mostly below 50%, but the proportion of teachers who demand support was much higher, at around 80%. Second, the difficulty of elementary school teachers in applying the 2022 revised mathematics curriculum was found to be the greatest in evaluation. Third, in relation to the use of edutech, teachers in elementary schools are also expected to have difficulties in teaching and learning methods to foster students' digital literacy, assessment using teaching materials or engineering tools, and assessment in online environments. Fourth, the difficulty of elementary school teachers in applying the 2022 revised mathematics curriculum was also significant in relation to mathematics subject competencies. Fifth, it was found that there is also difficulty in understanding the major changes of the achievement standards, including the addition, deletion, and adjustment of the achievement standards, and the impact on the learning of other achievement standards. Finally, the responses of elementary school teachers to the expected difficulties and necessary support in applying the 2022 revised mathematics curriculum did not differ depending on the size of the school where it is located, but statistically significant differences were found in a number of items depending on the teaching experience of the teacher. Based on these research results, we hope that various support will be provided for the 2022 revised mathematics curriculum, which will be applied annually from 2024.

• Journal of Intelligence and Information Systems
• /
• v.17 no.1
• /
• pp.53-69
• /
• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.71-90
• /
• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of The Korean Association For Science Education
• /
• v.37 no.2
• /
• pp.359-370
• /
• 2017

The purpose of this study is to explore the changes caused by using smart technology in school science inquiry. For this, we investigated 12 elementary school teachers' perceptions by using an open-ended questionnaire, group discussions, classroom discussions, and participant interviews. The results of this study indicate that the introduction of technology into classroom inquiry can open up the various possibilities and can cause additional burdens as well. First, teachers explained that smart technology can expand the opportunities to observe natural phenomena such as constellations and changing phases of the moon. However, some teachers insisted that, sometimes, learning how to use new devices disrupts students' concentration on the inquiry process itself. Second, teachers introduced the way of digital measurement using smart phone sensors in inquiry activities. They said that digital measurement is useful in terms of the reduction of errors and of the simplicity to measure. However, other teachers insisted that using new devices in classroom inquiry can entail additional variables and confuse the students' focus of inquiry. Communication about inquiry process can also be improved by using digital media. However, some teachers emphasized that they always talked about both the purpose of using SNS and online etiquettes with their students before using SNS. Based on these results, we discussed the necessity of additional analysis on the various ways of using digital devices depending on teachers' perceptions, the types of digital competency required in science inquiry using smart technology, and the features of norms shaped in inquiry activities using smart technology.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.10 no.6
• /
• pp.69-80
• /
• 2015

This can be promoted collaboration environment for the system and the system is very important for competitiveness, it is equipped. If so, could work in collaboration with members of the organization to promote collaboration what factors? Organizational collaboration and cooperation of many people working, or worth pursuing common goals by sharing information and processes to improve labor productivity, defined as collaboration. Factors that promote collaboration are shared visions, the organization's principles and rules that reflect the visions, on-line system developments, and communication methods. First, it embodies the vision shared by the more sympathetic members are active and voluntary participation in the activities of the organization can be achieved. Second, the members are aware of all the rules and principles of a united whole is accepted and leads to good performance. In addition, the ability to share sensitive business activities for self-development and also lead to work to make this a regular activity to create a team that can collaborate to help the environment and the atmosphere. Third, a systematic construction of the online collaboration system is made efficient and rapid task. According to Student team and A corporation we knew that Cloud services and social media, low-cost, high-efficiency services could achieve. The introduction of the latest information technology changes, the members of the organization's systems and active participation can take advantage of continuing education must be made. Fourth, the company to inform people both inside and outside of the organization to communicate actively to change the image of the company activities, the creation of corporate performance is very important to figure. Reflects the latest trend to actively use social media to communicate the effort is needed. For development of systematic collaboration promoting model steps to meet the organizational role. First, the Chief Executive Officer to make a firm and clear vision of the organization members to propagate the faith, empathy gives a sense of belonging should be able to have. Second, middle managers, CEO's vision is to systematically propagate the organizers rules and principles to establish a system would create. Third, general operatives internalize the vision of the company stating that the role of outside companies must adhere. The purpose of this study was well done in collaboration organizations promoting factors for strategic alignment model based on the golden circle and collaboration to understand and reflect the latest trends in information technology tools to take advantage of smart work and business know how student teams through case analysis will derive the success factors. This is the foundation for future empirical studies are expected to be present.

• Management & Information Systems Review
• /
• v.36 no.3
• /
• pp.131-150
• /
• 2017

The purpose of this study is to observe the spread pattern of open source software (OSS) while establishing relations with surrounding actors during its operation period. In order to investigate the change pattern of participants in the OSS, we use a netnography on the basis of online data, which can trace the change patterns of the OSS depending on the passage of time. For this, the cases of three OSSs (e.g. jQuery, MooTools, and YUI), which are JavaScript frameworks, were compared, and the corresponding data were collected from the open application programming interface (API) of GitHub as well as blog and web searches. This research utilizes the translation process of the actor-network theory to categorize the stages of the change patterns on the OSS translation process. In the project commencement stage, we identified the type of three different OSS-related actors and defined associated relationships among them. The period, when a master commences a project at first, is refined through the course for the maintenance of source codes with persons concerned (i.e. project growth stage). Thereafter, the period when the users have gone through the observation and learning period by being exposed to promotion activities and codes usage respectively, and becoming to active participants, is regarded as the 'leap of participants' stage. Our results emphasize the importance of promotion processes in participants' selection of the OSS for participation and confirm the crowding-out effect that the rapid speed of OSS development retarded the emergence of participants.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.119-142
• /
• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.