• Title/Summary/Keyword: learning need

Search Result 2,490, Processing Time 0.029 seconds

A Survey on Dietary Habits in Gyeongnam and the Development of the Nutrition Education Curriculum with Teacher's Guide for Obese Elementary School Children (경남지역 일부 초등학교 비만아동의 식습관 분석 및 영양교육을 위한 교수학습과정안 개발)

  • Jo, Min-A;Lee, Kyung-Hea;Her, Eun-Sil;Kim, Jung-A
    • Journal of the Korean Dietetic Association
    • /
    • v.15 no.2
    • /
    • pp.97-112
    • /
    • 2009
  • The purpose of this study was to develop a nutrition education curriculum with teacher's guide which includes discretionary activities for obese children. A survey was carried out to investigate the recognition of body image and food behaviors according to the obesity index (mild, moderate, severe) in school children (4~6th grade, 158 boys and 60 girls) who were selected based on a physical examination in May, 2006 in the Gyeongnam province. Next, a nutrition education curriculum with teacher's guide was developed on the basis of the findings from the survey and from preceding researches. The results are summarized as follow. The results of this study showed the existence of some nutritional problems such as overeating, prejudice, skipping meals, snacking patterns, etc, which indicate the need for nutritional management for obese children. Most overweight children (80.3%) showed the most interest in the nutrition education program, particularly with regards to dieting for weight control (64.7%). The developed nutrition education curriculum consisted of 8 main subjects and 13 subtitles. The curriculum was prepared for 13 lessons and included songs and singing, making-up lyrics, games about nutrition, discussions of the experience of eating (satiety, thirst, hunger), debates on dietary habits, writing and others to promote the interest for learning. We aimed to develop this program in an attempt to improve the dietary habits of obese school children. This is very important because once a dietary habit is formed in adults, it is difficult to change and the best adjustable stage is during childhood. Therefore, early nutrition education during elementary school can change and build-up the awareness of health in young elementary school children.

  • PDF

An Analysis of the Relationship of Grit, Interest, Task-Commitment, Self-Regulation Ability, and Science Achievement of High School Students (고등학생의 투지, 흥미, 과제집착력, 자기조절능력 및 과학학업성취의 관계 분석)

  • Mun, Kongju;Ham, Eun Hye
    • Journal of The Korean Association For Science Education
    • /
    • v.36 no.3
    • /
    • pp.445-455
    • /
    • 2016
  • The purpose of this study is to identify the structural relationship among students' grit, interest, self-regulation ability, task-commitment and achievement within science learning. Our concern is understanding how grit is related to the other non-cognitive variables, i.e., interest, self-regulation ability, and task-commitment, which are widely known as significant predictors of science achievement. Based on literature review, we evaluated two hypothetical models in the frame of structural equation modeling as follows: first, grit was assumed to mediate relations of interest and self-regulation ability, and interest and task-commitment. Second, grit was assumed to have a direct effect on self-regulation ability and task-commitment independent of interest. In both models, grit was assumed to be indirectly associated with science achievement. A total number of 180 high school students (77 boys, 103 girls) participated in surveys on grit, interest, self-regulation ability, and task-commitment and reported their science test scores on mid-term/final exams. Results revealed that students' grit and interest were indirectly associated with their science achievement with the mediation of their self-regulation and task-commitment. We also found that task-commitment was highly correlated with interest and self-regulation. Furthermore, we found different patterns of correlations within the five variables between female and male students. From these results, we suggested that researchers need to investigate whether students' grit and task-commitment can explain their interest decreasing as they move to higher grade levels, how teachers can help students to maintain their interest in learning science from early childhood, and relationships of these non-cognitive variables and science achievement.

The moderating effects of ego-resilience on the effects of parents' child-rearing attitude perceived by adolescents and school life adaptation on problem behavior (청소년이 지각한 부모의 양육태도와 학교생활적응이 문제행동에 미치는 영향에서 자아탄력성의 조절효과)

  • Kim, Ji Hye;Yu, Nan Sook
    • Journal of Korean Home Economics Education Association
    • /
    • v.31 no.1
    • /
    • pp.1-19
    • /
    • 2019
  • The purposes of this study were to concretely reveal the effect of the parents' child-rearing attitude perceived by adolescents and the school life adaptation on the problem behavior, and to verify the moderating effect of the ego-resilience on the relationship between the parents' child-rearing attitude and the school life adaptation and the adolescent problem behavior. This study analyzed a total of 2,107 students in the first year of high school, which was the 4th year data(2013) of Korea Children Youth Panel Survey(KCYPS) 2010. The reliability, descriptive statistics, t-test, and hierarchical regression analysis were conducted using SPSS WIN 22.0. The results were as follows. First, the effect of the parents' child-rearing attitude(supervision, affection, reasonable explanation, excessive interference, excessive expectation, and inconsistency), school life adaptation(relationship with teacher, relationship with friend, school regulation, and learning activity), and ego-resilience on the adolescent problem behavior was analyzed. As a result, the relationship with friend(-) had the highest influence on the adolescent problem behavior, followed by learning activity(-), inconsistency(+), ego-resilience(-), excessive interference(+), and supervision(-). However, the remaining sub-variables did not have any significant influence on the adolescent problem behavior. Second, the moderating effect of the ego-resilience on the relationship among the parents' child-rearing attitude, adaptation to school life, and adolescent problem behavior. The ego-resilience was found to moderate the effects of parents' positive child-rearing attitude, interpersonal relationships, and school adaptation on the adolescent problem behavior. However, the moderating effect was not significant for the effect of negative child-rearing attitude on the adolescent problem behavior. Therefore, various ego-resilience enhancement programs need to be developed and researched as a part of the safety education through the home economics class.

Korean Word Sense Disambiguation using Dictionary and Corpus (사전과 말뭉치를 이용한 한국어 단어 중의성 해소)

  • Jeong, Hanjo;Park, Byeonghwa
    • Journal of Intelligence and Information Systems
    • /
    • v.21 no.1
    • /
    • pp.1-13
    • /
    • 2015
  • As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

Learning from the USA's Single Emergency Number 911: Policy Implications for Korea (미국 긴급번호 911 운영시스템에 관한 연구: 긴급번호 실질적 통합을 위한 정책 시사점 제시 중심으로)

  • Kim, Hak-Kyong;Lee, Sung-Yong
    • Korean Security Journal
    • /
    • no.43
    • /
    • pp.67-97
    • /
    • 2015
  • In Korea, a single emergency number, such as 911 of the USA and 999 of the UK, does not exist. This issue became highly controversial, when the Sewol Ferry Sinking disaster occurred last year. So, the Korean government has planned to adopt a single emergency number, integrating 112 of the Police, 119 of the Fire and Ambulance, 122 of the Korean Coast Guard, and many other emergency numbers. However, the integration plan recently proposed by the Ministry of Public Safety Security seems to be, what is called, a "partial integration model" which repeals the 122 number, but still maintains 112, 119, and 110 respectively. In this context, the study looks into USA's (diverse) 911 operating system, and subsequently tries to draw general features or characteristics. Further, the research attempts to derive policy implication from the general features. If the proposed partial integration model reflects the policy implications, the model can virtually operate like the 911 system -i.e. a single emergency number system - creating inter-operability between responding agencies such as police, fire, and ambulance, even though it is not a perfect integration model. The features drawn are (1) integration of emergency call-taking, (2) functional separation of call-taking and dispatching, (3) integration of physical facilities for call-taking and dispatching, and (4) professional call-takers and dispatchers. Moreover, the policy implications derived from the characteristics are (1) a user-friendly system - fast but accurate responses, (2) integrated responses to accidents, (3) professional call-taking and dispatching & objective and comprehensive risk assessment, and finally (4) active organizational learning in emergency call centers. Considering the policy implications, the following suggestions need to be applied to the current proposed plan: 1. Emergency services' systems should be tightly linked and connected in a systemic way so that they can communicate and exchange intelligence with one another. 2. Public safety answering points (call centers) of each emergency service should share their education and training modules, manuals, etc. Common training and manuals are also needed for inter-operability. 3. Personal management to enable-long term service in public safety answering points (call centers) should be established as one of the ways to promote professionalism.

  • PDF

Literary Text and the Cultural Interpretation - A Study of the Model of 「History of Spanish Literature」 (문학텍스트와 문학적 해석 -「스페인 문학사」를 통한 모델 연구)

  • Na, Songjoo
    • Cross-Cultural Studies
    • /
    • v.26
    • /
    • pp.465-485
    • /
    • 2012
  • Instructing "History of Spanish Literature" class faces various types of limits and obstacles, just as other foreign language literature history classes do. Majority of students enter the university without having any previous spanish learning experience, which means, for them, even the interpretation of the text itself can be difficult. Moreover, the fact that "History of Spanish Literature" is traced all the way back to the Middle Age, students encounter even more difficulties and find factors that make them feel the class is not interesting. To list several, such factors include the embarrassment felt by the students, antiquated expressions, literature texts filled with deliberately broken grammars, explanations written in pretentious vocabularies, disorderly introduction of many different literary works that ignores the big picture, in which in return, reduces academic interest in students, and finally general lack of interest in literate itself due to the fact that the following generation is used to visual media. Although recognizing such problem that causes the distortion of the value of our lives and literature is a very imminent problem, there has not even been a primary discussion on such matter. Thus, the problem of what to teach in "History of Spanish Literature" class remains unsolved so far. Such problem includes wether to teach the history of authors and literature works, or the chronology of the text, the correlations, and what style of writing to teach first among many, and how to teach to read with criticism, and how to effectively utilize the limited class time to teach. However, unfortunately, there has not been any sorts of discussion among the insructors. I, as well, am not so proud of myself either when I question myself of how little and insufficiently did I contemplate about such problems. Living in the era so called the visual media era or the crisis of humanity studies, now there is a strong need to bring some change in the education of literature history. To suggest a solution to make such necessary change, I recommended to incorporate the visual media, the culture or custom that students are accustomed to, to the class. This solution is not only an attempt to introduce various fields to students, superseding the mere literature reserch area, but also the result that reflects the voice of students who come from a different cultural background and generation. Thus, what not to forget is that the bottom line of adopting a new teaching method is to increase the class participation of students and broaden the horizon of the Spanish literature. However, the ultimate goal of "History of Spanish Literature" class is the contemplation about humanity, not the progress in linguistic ability. Similarly, the ultimate goal of university education is to train students to become a successful member of the society. To achieve such goal, cultural approach to the literature text helps not only Spanish learning but also pragmatic education. Moreover, it helps to go beyond of what a mere functional person does. However, despite such optimistic expectations, foreign literature class has to face limits of eclecticism. As for the solution, as mentioned above, the method of teaching that mainly incorporates cultural text is a approach that fulfills the students with sensibility who live in the visual era. Second, it is a three-dimensional and sensible approach for the visual era, not an annotation that searches for any ambiguous vocabularies or metaphors. Third, it is the method that reduces the burdensome amount of reading. Fourth, it triggers interest in students including philosophical, sociocultural, and political ones. Such experience is expected to stimulate the intellectual curiosity in students and moreover motivates them to continues their study in graduate school, because it itself can be an interesting area of study.

Development Process for User Needs-based Chatbot: Focusing on Design Thinking Methodology (사용자 니즈 기반의 챗봇 개발 프로세스: 디자인 사고방법론을 중심으로)

  • Kim, Museong;Seo, Bong-Goon;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
    • /
    • v.25 no.3
    • /
    • pp.221-238
    • /
    • 2019
  • Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

A Study on the Effect of the Document Summarization Technique on the Fake News Detection Model (문서 요약 기법이 가짜 뉴스 탐지 모형에 미치는 영향에 관한 연구)

  • Shim, Jae-Seung;Won, Ha-Ram;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
    • /
    • v.25 no.3
    • /
    • pp.201-220
    • /
    • 2019
  • Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

Prediction of Air Temperature and Relative Humidity in Greenhouse via a Multilayer Perceptron Using Environmental Factors (환경요인을 이용한 다층 퍼셉트론 기반 온실 내 기온 및 상대습도 예측)

  • Choi, Hayoung;Moon, Taewon;Jung, Dae Ho;Son, Jung Eek
    • Journal of Bio-Environment Control
    • /
    • v.28 no.2
    • /
    • pp.95-103
    • /
    • 2019
  • Temperature and relative humidity are important factors in crop cultivation and should be properly controlled for improving crop yield and quality. In order to control the environment accurately, we need to predict how the environment will change in the future. The objective of this study was to predict air temperature and relative humidity at a future time by using a multilayer perceptron (MLP). The data required to train MLP was collected every 10 min from Oct. 1, 2016 to Feb. 28, 2018 in an eight-span greenhouse ($1,032m^2$) cultivating mango (Mangifera indica cv. Irwin). The inputs for the MLP were greenhouse inside and outside environment data, and set-up and operating values of environment control devices. By using these data, the MLP was trained to predict the air temperature and relative humidity at a future time of 10 to 120 min. Considering typical four seasons in Korea, three-day data of the each season were compared as test data. The MLP was optimized with four hidden layers and 128 nodes for air temperature ($R^2=0.988$) and with four hidden layers and 64 nodes for relative humidity ($R^2=0.990$). Due to the characteristics of MLP, the accuracy decreased as the prediction time became longer. However, air temperature and relative humidity were properly predicted regardless of the environmental changes varied from season to season. For specific data such as spray irrigation, however, the numbers of trained data were too small, resulting in poor predictive accuracy. In this study, air temperature and relative humidity were appropriately predicted through optimization of MLP, but were limited to the experimental greenhouse. Therefore, it is necessary to collect more data from greenhouses at various places and modify the structure of neural network for generalization.

A Checklist to Improve the Fairness in AI Financial Service: Focused on the AI-based Credit Scoring Service (인공지능 기반 금융서비스의 공정성 확보를 위한 체크리스트 제안: 인공지능 기반 개인신용평가를 중심으로)

  • Kim, HaYeong;Heo, JeongYun;Kwon, Hochang
    • Journal of Intelligence and Information Systems
    • /
    • v.28 no.3
    • /
    • pp.259-278
    • /
    • 2022
  • With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.